Reducing Asymmetry in Countering Unmanned Aerial Systems

Abstract

Current Counter Unmanned Aerial Systems (C-UAS) rely heavily on low-e ciency techniques such as broadband radio frequency (RF) jamming and high-intensity lasers. Not only do such techniques come at the cost of second and third order e ects-such as collateral jamming risks to operational systems, a large RF footprint, and high energy use-but they also present an asymmetry between threat and response. Many commercial, o-the-shelf UAS devices are inexpensive compared to the C-UAS systems historically under focus in DoD acquisition. is work argues for leveling that asymmetry by exploring C-UAS autonomy-on-autonomy options by using cyberattack payload capabilities residing on a UAS. By reducing the attack surface to focus on a particular target, these cyber techniques provide scalpel-edged control to the operator, reducing risk to own systems, RF footprint, and collateral damage.

Full text

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Reducing Asymmetry in Countering
Unmanned Aerial Systems
CAPT Christian M. Thiessen, USMC, Dr. Douglas L. Van Bossuyt1, Dr. Britta Hale1
1 Naval Postgraduate School
Abstract
Current Counter Unmanned Aerial Systems (C-UAS) rely
heavily on low-e ciency techniques such as broadband
radio frequency (RF) jamming and high-intensity lasers.
Not only do such techniques come at the cost of second
and third order e ects—such as collateral jamming risks to
operational systems, a large RF footprint, and high energy
use—but they also present an asymmetry between threat
and response. Many commercial, o -the-shelf UAS devices
are inexpensive compared to the C-UAS systems historically
under focus in DoD acquisition.  is work argues for
leveling that asymmetry by exploring C-UAS autonomy-on-
autonomy options by using cyberattack payload capabilities
residing on a UAS. By reducing the attack surface to focus on
a particular target, these cyber techniques provide scalpel-
edged control to the operator, reducing risk to own systems,
RF footprint, and collateral damage.
Introduction
In the past decade, unmanned aircra systems (UAS) have
proliferated on the battle eld, giving technologically inferior
combatants an advantage over their more sophisticated and
numerically superior competitors.  is was never more evident
than in 2014 when ISIS used consumer UASs to surveil and
target coalition forces during  ghting in Raqqa, Syria (Almo-
hammad & Speckhard, 2017).  en in the 2017 battle to retake
the city of Mosul, the terrorist group leveraged their Facebook
and Twitter presence to record and post jaw-dropping videos of
their ambushes using UASs retro tted with grenades (Warrick,
2017). Several years later, the 2020 Nagorno-Karabakh War
between Armenia and Azerbaijan, further demonstrated the
need for robust short-range air-defense to counter-unmanned
aircra systems (C-UAS) when the numerically inferior
Azeri military dismantled the Armenian army and destroyed
over 350 armored vehicles (Sukhankin, 2021a, 2021b). More
recently, the Ukraine achieved remarkable success against the
Russians using the same tactics and equipment as the Azeris
(Perrigo, 2022).  ese examples show how poor and techno-
logically inferior combatants can employ inexpensive technol-
ogy in a sophisticated manner to negate an opponent’s center
of gravity.
 is is telling given what is known about asymmetric
warfare: by engaging in a war of asymmetry, where an actor’s
interests and political vulnerability are inversely proportion-
al, strong actors are more likely to lose opposite approach
interactions (Arreguin-To , 2005). Taking the lessons from
Ivan Arreguin-To ’s research as well as the initial results of the
American war in Afghanistan, it is clear that the best way for
a stronger combatant to counter asymmetry is by taking an
indirect approach of their own.
In this work we consider the current C-UAS approach and
technologies and assert that instituting a constellation of aerial
security patrols tasked with UAS interdiction will provide
installation commanders a more robust method for countering
the asymmetric threat posed by UASs. Networking stand-in
TECHNICAL ARTICLE
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Reducing Asymmetry in Countering Unmanned Aerial Systems
serious incursion or multi-wave attack using only unmanned
systems.  e current method for defending military installa-
tions and critical infrastructure from UAS incursions mirrors
the static defense of forts and castles rather than the maneu-
verable defenses of the 21st Century. If defensive positions are
supposed to be designed for maneuver and  exibility, a defense
in the current C-UAS landscape is anything but. Instead of ad-
hering to traditional escalation of force procedures, the current
C-UAS architecture uses the most capable weapons  rst, like
the CACI Skytracker (Pitsky, 2021) and Anduril Sentry Tower
(Anduril, 2021)  rst. As a metaphor for defensive operations,
this is more akin to opening  re with crew-served weapons
instead of beginning an engagement with security patrols and
harassing  res. Ultimately, the lack of defensive layers allows
an attacker increased mobility to target the defender’s most
lethal assets.
With an understanding of the current systems and how
they match, or do not match, customary planning guidance,
the DOD and DHS should incorporate the concept of aerial
security patrols into the C-UAS framework. To fully realize
this, friendly unmanned platforms can be terrestrially or ae-
rially deployed to act as patrols, giving installations a forward
presence to assist in the full gamut of C-UAS kill-chain actions.
Because many of the kill-chain functions can be o oaded and
stripped away to the main sentry tower, these C-UAS devices
can be modular and customizable enough to meet the form,  t,
and function of the host device.
Electronic Warfare in the C-UAS Kill-Chain
To limit collateral damage and to increase e ectiveness in
countering unmanned systems, the DOD and DHS have
focused their e orts on the non-kinetic electronic warfare
technology built by Anduril, CACI, Sierra Nevada Corpo-
ration, and Lockheed Martin. Electronic warfare has three
subcomponents: electronic attack, electronic support, and
electronic protection, the  rst two being the most important
to the purpose of this paper. Electronic support in C-UAS
consists of the techniques conducted in the  rst three steps of
the kill-chain: “Detect, Track, and Identify,” while electronic
attack consists of the techniques to “Mitigate” an adversarial
UAS.  is section will primarily focus on the electronic attack
techniques contained within radio frequency (RF) jamming.
RF jamming is designed to sever the communication link
between an UAS and its ground control station (GCS) by in-
jecting substantial amounts of electromagnetic energy, referred
to as noise, into a receiving antenna (Parlin et al., 2018). Uplink
jamming disrupts the receiving antenna of the target UAS,
while downlink jamming interferes with the receiving antenna
of the GCS (Lichtman et al., 2016). Uplink and downlink jam-
ming can be accomplished by two types of jammers: stand-o
and stand-in. Stand-o jammers are devices that exist among
friendly forces, typically employed as terrestrial or aerial plat-
forms (e.g., the MADIS and EA-18G Growler). Stand-o jam-
mers are notorious for consuming copious amounts of power
to overcome the free-space path loss associated with their
use. Stand-in jammers exist amongst their targets but must be
located closer to their target, requiring a host-device or person
to decrease the distance to their target (Brown et al., 2007).
RF jamming, also referred to as noise jamming, uses a jam-
ming carrier signal modulated with a random noise waveform
to disrupt the communication by inserting Gaussian noise
into the receiver.  e bandwidth of the jamming signal can be
as wide as the entire spectrum width used by the target or as
narrow as a single channel (Poisel, 2011).  e former refers
to broadband, full-band, or barrage jamming to place noise
energy across the entire width of the frequency spectrum used
by the target.  is technique is useful against all communica-
tions by placing the jammer between an adversary’s commu-
nication links. To mitigate fratricide, directional antennas are
used to avoid interference with friendly communications in
the same frequency band (Stutzman &  iele, 2013). Because
broadband jamming generates a signal like broadband noise,
the jamming power is lowered to meet the needs of the entire
frequency band. Additionally, since broadband jamming raises
background noise levels, it can attack the synchronization
and tracking processes of the communication scheme it is
going a er (Poisel, 2011). It may be obvious, but the primary
limitation with broadband jamming is its ine cient consump-
tion of power, which necessitates a large system size, and the
likelihood to in ict unintentional collateral damage to adjacent
communication systems.
Communications engineers are constantly designing and
employing techniques to lower the probability of communi-
cations detection (LPD), interception (LPI), and exploitation
(LPE), while expanding access to multiple users (Sklar, 2001).
 is led to engineers and system designers to spread spectrum
signal modulation techniques through two primary techniques:
Direct Sequence Spread Spectrum (DSSS) and Frequency
Hopping Spread Spectrum (FHSS) (Sklar, 2001). Both FHSS
and DSSS are considered “anti-jam” communications schemes
because they vary the frequencies used, use time hopping,
and implement narrow-beam antennas to put the jammer at a
signi cant disadvantage.
However, just because the signal has anti-jam properties,
does not mean the signal is impervious to disruption.  is is
due to the notion that the intelligibility of information transfer
Reducing Asymmetry in Countering Unmanned Aerial Systems
electronic warfare (EW) and cyber-attack devices provides
a layered perimeter to augment the current systems with
persistent deterrence that mimics the security patrols used in
modern defensive operations.
 is paper will begin with a discussion on what makes a
modern defense-in-depth approach successful, then move
onto a more technical discussion on electronic warfare and
cyber-attack methods. Additionally, this paper will cover the
countermeasures currently in procurement by the Department
of Defense (DOD) and Department of Homeland Security
(DHS). Finally, this paper will conclude with two examples sce-
narios in which this framework could be adopted by the DOD
and DHS acquisition communities to create the most e ective
means of countering unmanned aircra .
Defense-in-Depth
Marine Corps War ghting Publication 3-01, O ensive and De-
fensive Tactics, de nes a defensive operation as “an operation
conducted to defeat an enemy attack, gain time, economize
forces, and develop conditions favorable to o ensive or stability
operations (U.S. Marine Corps, 2019).” Defensive operations
create the conditions that allow a friendly force to recover and
regain operational initiative by denying an enemy’s access to
vital areas or by eroding an enemy’s ability to concentrate  re-
power in an attack. While there are myriad defensive positions
to analyze, they are designed to defend-in-depth using a main
engagement area, a support area, and a security area where
forward positioned troops gather information and interdict the
enemy. In the example shown in Figure 1, the defenders use the
perimeter defense to give 360-degree coverage of a vital asset,
which in the case of C-UAS would be the defense of a military
base or installation.
Defensive operations are characterized by maneuver,
preparation,  exibility, mutual support, and surprise to disrupt
an adversary’s attack momentum. In a defense in depth, this
is achieved by engaging the enemy at the earliest opportunity
with security forces as well as moving reserve and  re support
units to a position of advantage (U.S. Marine Corps, 2002).
 is gives the defense a bu er against an attacker’s main
thrust, ensuring the attacker commits their forces in piecemeal
fashion, and preventing them from massing  repower where
they intend.
In the context of defending infrastructure against adversar-
ial UAS, the goal of the defense is to maintain normal oper-
ations without interruption or degradation from an attack. Giv-
en that most bases and critical infrastructure in the continental
U.S. have de ned physical perimeters with restricted operating
zones for aircra to  y in and out of, the main engagement
area in the C-UAS  ght becomes a matter of procedure based
on local environmental restrictions (Air Land Sea Application
Center, 2019). In defensive operations, this engagement area
development establishes control measures and trigger lines
to outline speci c weapons and actions to be taken given a
set of circumstances.  ese escalation of force procedures are
well-de ned for human incursions onto a military facility, yet
they remain immature in the C-UAS  ght.
In the planning process for carrying out defense-in-depth,
the Marine Corps teaches its o cers seven steps of engagement
area development (U.S. Marine Corps, 2017). One of the  rst
actions taken is to gain depth in the battle space by launching
security patrols to interdict would-be attackers.  ese security
patrols are designed to increase the situational awareness of the
ground force commander and are given with several guiding
principles: observe, report, and protect against enemy in ltra-
tion or ambush (U.S. Marine Corps, 2000).  is may, or may
not, require a security patrol to engage the enemy kinetically,
making it an essential tool for the successful execution of a
ground commander’s mission.
 is begs the question, why is there not a similar process
for defending U.S. bases and infrastructure against adversar-
ial UASs? We believe the answer is that there has yet to be a
Weak Actor Strategic Approach
Direct Indirect
Strong Actor Direct Strong Wins Weak Wins
Strategic
Approach Indirect Weak Wins Strong Wins
FIGURE 1.STRATEGIC Approach Model.
Source: [Arreguin-To , 2005; Figure 3]
FIGURE 2- Sample Perimeter Defense
[Source: Figure 9-1; (U.S. Marine Corps, 2019)]
84 | March 2023 | No. 135-1 NAVAL ENGINEERS JOURNAL

Delivered by Ingenta
Date : Wed, 12 Apr 2023 20:53:12 IP : 205.155.65.226
Reducing Asymmetry in Countering Unmanned Aerial Systems
serious incursion or multi-wave attack using only unmanned
systems.  e current method for defending military installa-
tions and critical infrastructure from UAS incursions mirrors
the static defense of forts and castles rather than the maneu-
verable defenses of the 21st Century. If defensive positions are
supposed to be designed for maneuver and  exibility, a defense
in the current C-UAS landscape is anything but. Instead of ad-
hering to traditional escalation of force procedures, the current
C-UAS architecture uses the most capable weapons  rst, like
the CACI Skytracker (Pitsky, 2021) and Anduril Sentry Tower
(Anduril, 2021)  rst. As a metaphor for defensive operations,
this is more akin to opening  re with crew-served weapons
instead of beginning an engagement with security patrols and
harassing  res. Ultimately, the lack of defensive layers allows
an attacker increased mobility to target the defender’s most
lethal assets.
With an understanding of the current systems and how
they match, or do not match, customary planning guidance,
the DOD and DHS should incorporate the concept of aerial
security patrols into the C-UAS framework. To fully realize
this, friendly unmanned platforms can be terrestrially or ae-
rially deployed to act as patrols, giving installations a forward
presence to assist in the full gamut of C-UAS kill-chain actions.
Because many of the kill-chain functions can be o oaded and
stripped away to the main sentry tower, these C-UAS devices
can be modular and customizable enough to meet the form,  t,
and function of the host device.
Electronic Warfare in the C-UAS Kill-Chain
To limit collateral damage and to increase e ectiveness in
countering unmanned systems, the DOD and DHS have
focused their e orts on the non-kinetic electronic warfare
technology built by Anduril, CACI, Sierra Nevada Corpo-
ration, and Lockheed Martin. Electronic warfare has three
subcomponents: electronic attack, electronic support, and
electronic protection, the  rst two being the most important
to the purpose of this paper. Electronic support in C-UAS
consists of the techniques conducted in the  rst three steps of
the kill-chain: “Detect, Track, and Identify,” while electronic
attack consists of the techniques to “Mitigate” an adversarial
UAS.  is section will primarily focus on the electronic attack
techniques contained within radio frequency (RF) jamming.
RF jamming is designed to sever the communication link
between an UAS and its ground control station (GCS) by in-
jecting substantial amounts of electromagnetic energy, referred
to as noise, into a receiving antenna (Parlin et al., 2018). Uplink
jamming disrupts the receiving antenna of the target UAS,
while downlink jamming interferes with the receiving antenna
of the GCS (Lichtman et al., 2016). Uplink and downlink jam-
ming can be accomplished by two types of jammers: stand-o
and stand-in. Stand-o jammers are devices that exist among
friendly forces, typically employed as terrestrial or aerial plat-
forms (e.g., the MADIS and EA-18G Growler). Stand-o jam-
mers are notorious for consuming copious amounts of power
to overcome the free-space path loss associated with their
use. Stand-in jammers exist amongst their targets but must be
located closer to their target, requiring a host-device or person
to decrease the distance to their target (Brown et al., 2007).
RF jamming, also referred to as noise jamming, uses a jam-
ming carrier signal modulated with a random noise waveform
to disrupt the communication by inserting Gaussian noise
into the receiver.  e bandwidth of the jamming signal can be
as wide as the entire spectrum width used by the target or as
narrow as a single channel (Poisel, 2011).  e former refers
to broadband, full-band, or barrage jamming to place noise
energy across the entire width of the frequency spectrum used
by the target.  is technique is useful against all communica-
tions by placing the jammer between an adversary’s commu-
nication links. To mitigate fratricide, directional antennas are
used to avoid interference with friendly communications in
the same frequency band (Stutzman &  iele, 2013). Because
broadband jamming generates a signal like broadband noise,
the jamming power is lowered to meet the needs of the entire
frequency band. Additionally, since broadband jamming raises
background noise levels, it can attack the synchronization
and tracking processes of the communication scheme it is
going a er (Poisel, 2011). It may be obvious, but the primary
limitation with broadband jamming is its ine cient consump-
tion of power, which necessitates a large system size, and the
likelihood to in ict unintentional collateral damage to adjacent
communication systems.
Communications engineers are constantly designing and
employing techniques to lower the probability of communi-
cations detection (LPD), interception (LPI), and exploitation
(LPE), while expanding access to multiple users (Sklar, 2001).
 is led to engineers and system designers to spread spectrum
signal modulation techniques through two primary techniques:
Direct Sequence Spread Spectrum (DSSS) and Frequency
Hopping Spread Spectrum (FHSS) (Sklar, 2001). Both FHSS
and DSSS are considered “anti-jam” communications schemes
because they vary the frequencies used, use time hopping,
and implement narrow-beam antennas to put the jammer at a
signi cant disadvantage.
However, just because the signal has anti-jam properties,
does not mean the signal is impervious to disruption.  is is
due to the notion that the intelligibility of information transfer
Reducing Asymmetry in Countering Unmanned Aerial Systems
electronic warfare (EW) and cyber-attack devices provides
a layered perimeter to augment the current systems with
persistent deterrence that mimics the security patrols used in
modern defensive operations.
 is paper will begin with a discussion on what makes a
modern defense-in-depth approach successful, then move
onto a more technical discussion on electronic warfare and
cyber-attack methods. Additionally, this paper will cover the
countermeasures currently in procurement by the Department
of Defense (DOD) and Department of Homeland Security
(DHS). Finally, this paper will conclude with two examples sce-
narios in which this framework could be adopted by the DOD
and DHS acquisition communities to create the most e ective
means of countering unmanned aircra .
Defense-in-Depth
Marine Corps War ghting Publication 3-01, O ensive and De-
fensive Tactics, de nes a defensive operation as “an operation
conducted to defeat an enemy attack, gain time, economize
forces, and develop conditions favorable to o ensive or stability
operations (U.S. Marine Corps, 2019).” Defensive operations
create the conditions that allow a friendly force to recover and
regain operational initiative by denying an enemy’s access to
vital areas or by eroding an enemy’s ability to concentrate  re-
power in an attack. While there are myriad defensive positions
to analyze, they are designed to defend-in-depth using a main
engagement area, a support area, and a security area where
forward positioned troops gather information and interdict the
enemy. In the example shown in Figure 1, the defenders use the
perimeter defense to give 360-degree coverage of a vital asset,
which in the case of C-UAS would be the defense of a military
base or installation.
Defensive operations are characterized by maneuver,
preparation,  exibility, mutual support, and surprise to disrupt
an adversary’s attack momentum. In a defense in depth, this
is achieved by engaging the enemy at the earliest opportunity
with security forces as well as moving reserve and  re support
units to a position of advantage (U.S. Marine Corps, 2002).
 is gives the defense a bu er against an attacker’s main
thrust, ensuring the attacker commits their forces in piecemeal
fashion, and preventing them from massing  repower where
they intend.
In the context of defending infrastructure against adversar-
ial UAS, the goal of the defense is to maintain normal oper-
ations without interruption or degradation from an attack. Giv-
en that most bases and critical infrastructure in the continental
U.S. have de ned physical perimeters with restricted operating
zones for aircra to  y in and out of, the main engagement
area in the C-UAS  ght becomes a matter of procedure based
on local environmental restrictions (Air Land Sea Application
Center, 2019). In defensive operations, this engagement area
development establishes control measures and trigger lines
to outline speci c weapons and actions to be taken given a
set of circumstances.  ese escalation of force procedures are
well-de ned for human incursions onto a military facility, yet
they remain immature in the C-UAS  ght.
In the planning process for carrying out defense-in-depth,
the Marine Corps teaches its o cers seven steps of engagement
area development (U.S. Marine Corps, 2017). One of the  rst
actions taken is to gain depth in the battle space by launching
security patrols to interdict would-be attackers.  ese security
patrols are designed to increase the situational awareness of the
ground force commander and are given with several guiding
principles: observe, report, and protect against enemy in ltra-
tion or ambush (U.S. Marine Corps, 2000).  is may, or may
not, require a security patrol to engage the enemy kinetically,
making it an essential tool for the successful execution of a
ground commander’s mission.
 is begs the question, why is there not a similar process
for defending U.S. bases and infrastructure against adversar-
ial UASs? We believe the answer is that there has yet to be a
Weak Actor Strategic Approach
Direct Indirect
Strong Actor Direct Strong Wins Weak Wins
Strategic
Approach Indirect Weak Wins Strong Wins
FIGURE 1.STRATEGIC Approach Model.
Source: [Arreguin-To , 2005; Figure 3]
FIGURE 2- Sample Perimeter Defense
[Source: Figure 9-1; (U.S. Marine Corps, 2019)]
NAVAL ENGINEERS JOURNAL March 2023 | No. 135-1 | 85

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Date : Wed, 12 Apr 2023 20:53:12 IP : 205.155.65.226
Reducing Asymmetry in Countering Unmanned Aerial Systems
integrating most sensor types with
several mitigation methods. Addition-
ally, these systems can have an auton-
omous mode that allows the platform
to move through the kill-chain with a
human-on-, -in-, or -out-of-the-loop.
Unfortunately, these platforms require
enormous amounts of shore power to
operate the various sensor packages
onboard (Wang et al., 2021). Addition-
ally, because they are in static positions,
they become easier targets for adversar-
ies to attack or sabotage. Lastly, because
the sensors on  xed and terrestrial sites
use the high-end solutions, they are ex-
tremely expensive to acquire, maintain,
and sustain throughout their product life
cycle (Wang et al., 2021).
Ground-based, mobile platforms are
designed to be mounted on vehicles and
operated while moving. Depending on
the transportation vehicle, they can be
very capable in austere environments by
carrying a modest amount of power and
sustainment before needing to return to
base for rest and re t. However, despite
their mobility, these C-UAS systems
like the Marine Air Defense Integrated
System (MADIS), built by Sierra Nevada
Corporation and Lockheed Martin,
have several glaring limitations (Barrett,
2019). First o , they are human operated
which requires extensive operator train-
ing on the system. Second, because they
are general-purpose EW systems, the
ground-based mobile systems require
signi cant amounts of power that have a
large RF signature.  is power con-
sumption means that the ground-based,
mobile C-UAS cannot conduct persistent
sensing without nearby resupply.  ird,
they are extremely expensive.  e MAD-
IS is a $150 million dollar program of
record, and as it seeks to bring in more
capabilities, it will increasingly become
more expensive (Missile Defense Advo-
cacy Alliance, 2020). Finally, because the
MADIS is expensive, bulky, has signi -
cant power requirements, and contains
sensitive equipment, it must be carefully
protected. Loss of such an aerial defense
system could itself be catastrophic,
such as the fate of the Russian surface-
to-air missile convoy under Ukrainian
Bayraktar TB-2 attack (Ukraine Armed
Forces, 2022).
Handheld C-UAS systems are
operated by a single individual or team
of individuals.  e Dedrone DroneDe-
fender is a good example of a lightweight
handheld system that resembles a small
arms weapon with a highly directional
antennas (Dedrone, n.d.).  e hand-
held devices are cheaper than the  xed,
mobile, or UAS-based devices. Addi-
tionally, the low power and portability
of these systems gives another advantage
over their larger counterparts; handheld
systems can jam an entire frequency
band with minimal collateral damage to
friendly communications farther a eld
because of signal attenuation over longer
distances. However, there are downsides
to the lower power settings. Namely, they
only operate on 1 or 2 frequency bands
and lack a smart library, necessitating a
broadband jam of e.g., the 2.4 or 5.8GHz
frequency bands.  ey are only e ective
over shorter distances to a target, and
the broadband jamming can lead to the
unintended disruption of friendly or
civilian communications nearby.  us, in
high-density electromagnetic spectrum
environments like airports and border
crossings, using e.g., the DroneDefend-
er becomes precarious. Finally, even
though they are more portable than their
mobile or  xed counterparts, handheld
systems are still bulky and unwieldy;
Dedrone’s DroneDefender weighs 15.8
lbs., making it a cumbersome piece of
gear for operators to carry for sustained
periods of time.  e DroneDefender is a
 ne piece of equipment for the close-in
 ght where collateral damage does not
matter, but at high-altitudes it fails to be
e ective against adversarial aircra .
By and large, the current systems
procured have met the needs of the
DOD and DHS for the initial wave of
UAS usage.  e systems have proven
records of operational success around
the world and will continue to work
well against singular incursions like the
FIGURE 3. C-UAS Kill Chain
[Source: Figure 3-1; (Patel & Rizer, 2019)]
Current Systems Current C-UAS Pros Current C-UAS Cons
Ground to Air
MADIS
Compact Laser Weapon
DroneDefender
CACI Skytracker
Anduril Sentry Tower
Shotguns
Mobility
Small Form Factor
Handheld
Purpose-Built for COTS UAS
Exquisite AI Backbone
Close-Range
High-Powered Consumption
Easily Disrupted
BBN Jamming Only
Fixed Position
Expensive
Potential Fratricide
Air to Air
Nets
Anduril's Anvil
Explosives
Capture Target
Kinetic Kill w/o Fratricide
Target Destruction
Short-Range
Extensive Flight Path Metrics
Damages Friendly Device
TABLE 1. Pros and Cons of Current C-UAS Technology
Reducing Asymmetry in Countering Unmanned Aerial Systems
can be su ciently degraded by partial jamming, e.g., jamming
only 30% of a voice transmission degrades the transfer (Poisel,
2008).  erefore, to negate anti-jam properties, a jammer can
use an unmodulated carrier signal centered on the transmit-
ting frequency can be modulated with tone signals, or with
a variable-bandwidth noise signal.  ese tones are placed on
speci ed frequencies identi ed from prior target knowledge to
raise the noise  oor and prevent signal reception (Poisel, 2011).
 e goal of jamming a communications signal is no trivial
matter. In seeking to deny reliable connection between two
hosts, there are signi cant tradeo s made with the jamming
device’s size, power, antenna, and development cost. To make
matters harder, the spread spectrum techniques seek to create
jam-resistant waveforms to “force a jammer to expend its
resources over a wide-frequency band, for a maximum amount
of time, and from a diversity of sites” (Sklar, 2001).
 e most e cient means of jamming FHSS signals is with a
follower jammer where only a portion of each dwell is jammed,
meaning the jammer must ascertain the newly detected energy
and determine if it is the correct signal to jam (Poisel, 2011).
A follower jammer is best employed a speci c protocol in
mind, and with signi cant reverse engineering of the intend-
ed signal. Protocol aware or smart jamming algorithms then
become most e ective way to jam a signal without deleterious
e ects to the surrounding environment by disrupt portions of
a digitized signal based on their necessity to deny the intended
communications link.  is requires extensive synchronization
and knowledge about the target signal to track the timing and
phase of the transmitted signal. Another major limitation in
protocol aware jamming is the time delay from initial signal
acquisition to predicting the next frequency the signal hops
to—this is done in milliseconds and the frequency hopping
pattern can be non-deterministic (Poisel, 2011).
Historically, RF jamming has been the most common
C-UAS mitigation technique and is limited by terrain, weath-
er, equipment cost, and potential disruption of friendly and
civilian devices (Wang et al., 2021). Due to the clutter in the
frequency bands where most UAS communicate, RF detection
and mitigation becomes incredibly complicated.  e LPD,
LPI, and LPE characteristics of FHSS and DSSS signals enable
them to hide amongst the background clutter, making it harder
for attackers to identify and disrupt signals of interest. Many
modern devices are hardened against rudimentary RF jam-
ming techniques, which has led to new jamming techniques
and high-power consumption that increase complexity of the
C-UAS device.
It should be reiterated; regardless of which RF jamming
technique is used, there is a requirement for substantial
amounts of power which increases the physical parameters
of a system.  is has a detrimental e ect on the form,  t, and
function of a modular payload to interface with other systems.
Additionally, RF jamming has negative e ects on the other
sensors integrated on a host aircra . Because of the collateral
damage and SWaP considerations, integrating RF jamming
on manned and unmanned aircra becomes a more complex
problem to solve (Brown et al., 2007). As drones continue to
operate in commonly utilized frequency bands and in urban
environments, high power output and digital signal processing
will continue to be the norm.
Profi ling Current C-UAS Technology
Size, weight, power, and development cost are among the many
constraints that companies developing C-UAS technology have
to contend with.  ese companies must design systems that
not only work properly—a technological feat in and of itself—
but they must also contend with societal and legal limitations
as well. In a 2019 survey on current drone technologies, the
authors identi ed 537 C-UAS technologies designed to counter
unmanned aircra through kinetic or non-kinetic actions
(Michel, 2019). Despite the market density, the main trend of
this study showed that unmanned countermeasures are getting
increasingly bulky and expensive to procure and sustain, while
the targets they are supposed to thwart are only getting smaller
and more expendable.  e asymmetry in threat versus counter-
measure is much like the asymmetry in tactics and strategy.
 us, where such asymmetry exists, reducing asymmetry can
be achieved through rethinking the problem.  is leads to an
in ection point where the SWaP requirements of a host device
and non-kinetic electronic warfare and cyber-attack techniques
can be utilized to mitigate threats from small UASs.
For the purposes of understanding the C-UAS kill-chain,
the technology used in detecting, locating, and classifying UAS
can be parsed separately from the mitigation measures.  e
digital signal processing required for the  rst three-quarters of
the kill-chain are the most complex problems for C-UAS com-
panies to tackle because of a UAS’s low-energy output physical
characteristics that make them appear as small birds. Com-
panies like CACI and Anduril have created robust platforms
to meet the needs of the  rst three-quarters of the kill-chain
by building target libraries to help in building digital signal
processing and computer-vision algorithms for their sensor
packages.
Static, ground-based C-UAS sites are typically employed
aboard military bases, secure facilities, and other strategic
points of interest. Because they have access to shore pow-
er, they contain the most robust suite of countermeasures,
86 | March 2023 | No. 135-1 NAVAL ENGINEERS JOURNAL

Delivered by Ingenta
Date : Wed, 12 Apr 2023 20:53:12 IP : 205.155.65.226
Reducing Asymmetry in Countering Unmanned Aerial Systems
integrating most sensor types with
several mitigation methods. Addition-
ally, these systems can have an auton-
omous mode that allows the platform
to move through the kill-chain with a
human-on-, -in-, or -out-of-the-loop.
Unfortunately, these platforms require
enormous amounts of shore power to
operate the various sensor packages
onboard (Wang et al., 2021). Addition-
ally, because they are in static positions,
they become easier targets for adversar-
ies to attack or sabotage. Lastly, because
the sensors on  xed and terrestrial sites
use the high-end solutions, they are ex-
tremely expensive to acquire, maintain,
and sustain throughout their product life
cycle (Wang et al., 2021).
Ground-based, mobile platforms are
designed to be mounted on vehicles and
operated while moving. Depending on
the transportation vehicle, they can be
very capable in austere environments by
carrying a modest amount of power and
sustainment before needing to return to
base for rest and re t. However, despite
their mobility, these C-UAS systems
like the Marine Air Defense Integrated
System (MADIS), built by Sierra Nevada
Corporation and Lockheed Martin,
have several glaring limitations (Barrett,
2019). First o , they are human operated
which requires extensive operator train-
ing on the system. Second, because they
are general-purpose EW systems, the
ground-based mobile systems require
signi cant amounts of power that have a
large RF signature.  is power con-
sumption means that the ground-based,
mobile C-UAS cannot conduct persistent
sensing without nearby resupply.  ird,
they are extremely expensive.  e MAD-
IS is a $150 million dollar program of
record, and as it seeks to bring in more
capabilities, it will increasingly become
more expensive (Missile Defense Advo-
cacy Alliance, 2020). Finally, because the
MADIS is expensive, bulky, has signi -
cant power requirements, and contains
sensitive equipment, it must be carefully
protected. Loss of such an aerial defense
system could itself be catastrophic,
such as the fate of the Russian surface-
to-air missile convoy under Ukrainian
Bayraktar TB-2 attack (Ukraine Armed
Forces, 2022).
Handheld C-UAS systems are
operated by a single individual or team
of individuals.  e Dedrone DroneDe-
fender is a good example of a lightweight
handheld system that resembles a small
arms weapon with a highly directional
antennas (Dedrone, n.d.).  e hand-
held devices are cheaper than the  xed,
mobile, or UAS-based devices. Addi-
tionally, the low power and portability
of these systems gives another advantage
over their larger counterparts; handheld
systems can jam an entire frequency
band with minimal collateral damage to
friendly communications farther a eld
because of signal attenuation over longer
distances. However, there are downsides
to the lower power settings. Namely, they
only operate on 1 or 2 frequency bands
and lack a smart library, necessitating a
broadband jam of e.g., the 2.4 or 5.8GHz
frequency bands.  ey are only e ective
over shorter distances to a target, and
the broadband jamming can lead to the
unintended disruption of friendly or
civilian communications nearby.  us, in
high-density electromagnetic spectrum
environments like airports and border
crossings, using e.g., the DroneDefend-
er becomes precarious. Finally, even
though they are more portable than their
mobile or  xed counterparts, handheld
systems are still bulky and unwieldy;
Dedrone’s DroneDefender weighs 15.8
lbs., making it a cumbersome piece of
gear for operators to carry for sustained
periods of time.  e DroneDefender is a
 ne piece of equipment for the close-in
 ght where collateral damage does not
matter, but at high-altitudes it fails to be
e ective against adversarial aircra .
By and large, the current systems
procured have met the needs of the
DOD and DHS for the initial wave of
UAS usage.  e systems have proven
records of operational success around
the world and will continue to work
well against singular incursions like the
FIGURE 3. C-UAS Kill Chain
[Source: Figure 3-1; (Patel & Rizer, 2019)]
Current Systems Current C-UAS Pros Current C-UAS Cons
Ground to Air
MADIS
Compact Laser Weapon
DroneDefender
CACI Skytracker
Anduril Sentry Tower
Shotguns
Mobility
Small Form Factor
Handheld
Purpose-Built for COTS UAS
Exquisite AI Backbone
Close-Range
High-Powered Consumption
Easily Disrupted
BBN Jamming Only
Fixed Position
Expensive
Potential Fratricide
Air to Air
Nets
Anduril's Anvil
Explosives
Capture Target
Kinetic Kill w/o Fratricide
Target Destruction
Short-Range
Extensive Flight Path Metrics
Damages Friendly Device
TABLE 1. Pros and Cons of Current C-UAS Technology
Reducing Asymmetry in Countering Unmanned Aerial Systems
can be su ciently degraded by partial jamming, e.g., jamming
only 30% of a voice transmission degrades the transfer (Poisel,
2008).  erefore, to negate anti-jam properties, a jammer can
use an unmodulated carrier signal centered on the transmit-
ting frequency can be modulated with tone signals, or with
a variable-bandwidth noise signal.  ese tones are placed on
speci ed frequencies identi ed from prior target knowledge to
raise the noise  oor and prevent signal reception (Poisel, 2011).
 e goal of jamming a communications signal is no trivial
matter. In seeking to deny reliable connection between two
hosts, there are signi cant tradeo s made with the jamming
device’s size, power, antenna, and development cost. To make
matters harder, the spread spectrum techniques seek to create
jam-resistant waveforms to “force a jammer to expend its
resources over a wide-frequency band, for a maximum amount
of time, and from a diversity of sites” (Sklar, 2001).
 e most e cient means of jamming FHSS signals is with a
follower jammer where only a portion of each dwell is jammed,
meaning the jammer must ascertain the newly detected energy
and determine if it is the correct signal to jam (Poisel, 2011).
A follower jammer is best employed a speci c protocol in
mind, and with signi cant reverse engineering of the intend-
ed signal. Protocol aware or smart jamming algorithms then
become most e ective way to jam a signal without deleterious
e ects to the surrounding environment by disrupt portions of
a digitized signal based on their necessity to deny the intended
communications link.  is requires extensive synchronization
and knowledge about the target signal to track the timing and
phase of the transmitted signal. Another major limitation in
protocol aware jamming is the time delay from initial signal
acquisition to predicting the next frequency the signal hops
to—this is done in milliseconds and the frequency hopping
pattern can be non-deterministic (Poisel, 2011).
Historically, RF jamming has been the most common
C-UAS mitigation technique and is limited by terrain, weath-
er, equipment cost, and potential disruption of friendly and
civilian devices (Wang et al., 2021). Due to the clutter in the
frequency bands where most UAS communicate, RF detection
and mitigation becomes incredibly complicated.  e LPD,
LPI, and LPE characteristics of FHSS and DSSS signals enable
them to hide amongst the background clutter, making it harder
for attackers to identify and disrupt signals of interest. Many
modern devices are hardened against rudimentary RF jam-
ming techniques, which has led to new jamming techniques
and high-power consumption that increase complexity of the
C-UAS device.
It should be reiterated; regardless of which RF jamming
technique is used, there is a requirement for substantial
amounts of power which increases the physical parameters
of a system.  is has a detrimental e ect on the form,  t, and
function of a modular payload to interface with other systems.
Additionally, RF jamming has negative e ects on the other
sensors integrated on a host aircra . Because of the collateral
damage and SWaP considerations, integrating RF jamming
on manned and unmanned aircra becomes a more complex
problem to solve (Brown et al., 2007). As drones continue to
operate in commonly utilized frequency bands and in urban
environments, high power output and digital signal processing
will continue to be the norm.
Profi ling Current C-UAS Technology
Size, weight, power, and development cost are among the many
constraints that companies developing C-UAS technology have
to contend with.  ese companies must design systems that
not only work properly—a technological feat in and of itself—
but they must also contend with societal and legal limitations
as well. In a 2019 survey on current drone technologies, the
authors identi ed 537 C-UAS technologies designed to counter
unmanned aircra through kinetic or non-kinetic actions
(Michel, 2019). Despite the market density, the main trend of
this study showed that unmanned countermeasures are getting
increasingly bulky and expensive to procure and sustain, while
the targets they are supposed to thwart are only getting smaller
and more expendable.  e asymmetry in threat versus counter-
measure is much like the asymmetry in tactics and strategy.
 us, where such asymmetry exists, reducing asymmetry can
be achieved through rethinking the problem.  is leads to an
in ection point where the SWaP requirements of a host device
and non-kinetic electronic warfare and cyber-attack techniques
can be utilized to mitigate threats from small UASs.
For the purposes of understanding the C-UAS kill-chain,
the technology used in detecting, locating, and classifying UAS
can be parsed separately from the mitigation measures.  e
digital signal processing required for the  rst three-quarters of
the kill-chain are the most complex problems for C-UAS com-
panies to tackle because of a UAS’s low-energy output physical
characteristics that make them appear as small birds. Com-
panies like CACI and Anduril have created robust platforms
to meet the needs of the  rst three-quarters of the kill-chain
by building target libraries to help in building digital signal
processing and computer-vision algorithms for their sensor
packages.
Static, ground-based C-UAS sites are typically employed
aboard military bases, secure facilities, and other strategic
points of interest. Because they have access to shore pow-
er, they contain the most robust suite of countermeasures,
NAVAL ENGINEERS JOURNAL March 2023 | No. 135-1 | 87

Delivered by Ingenta
Date : Wed, 12 Apr 2023 20:53:12 IP : 205.155.65.226
Reducing Asymmetry in Countering Unmanned Aerial Systems
this type of attack is unpreventable and can only be mitigated
through  rewall strengthening and  ltering protections.
GNSS spoo ng is an attack method where a spoofer gen-
erates a counterfeit signal for each authentic signal received to
distort the relative true location of a target in favor of a coun-
terfeit location that is more favorable for the spoofer (Kerns et
al., 2014). For an attacker to su ciently exert control of a target
device via GNSS spoo ng, the attacker must capture the GNSS
signal of interest dynamically or through a priori knowledge.
GNSS spoo ng requires the insertion of a MITM but can be
especially e ective in negating an adversary’s use of waypoints
for UAS movement and control.
 e cyber-attack techniques outlined in the preceding para-
graphs provide a baseline for attack vectors against adversarial
UASs. To make this a fully realized e ort, a library of attacks
is needed speci cally designed to mitigate the threats posed
by commercial UASs and integrated with a menu of options
on a user interface.  is interface could be fully automated,
giving the operator-on-the-loop a common operating picture
of local threats and actions taken that the operator needs to be
alerted to.
While this was only lightly touched on in the introduction,
cyber-attacks notably consume less power than RF jamming.
Each attack type exploits a di erent protocol vulnerability than
the other and, while some can be patched easily, many UAS
manufacturers continue to design and build UASs with known
vulnerabilities. For many consumers, a fully optimized prod-
uct at a low price point is more important than data privacy
and security.  e cyber-attack techniques discussed in this
section are not meant to be a one-size  ts all approach like RF
jamming, but instead they are meant to give a variety of attack
solutions for escalation of force procedures in countering
unmanned systems.
Progression of Counter-Aerial
System Development
In aerial defense for standard enemy aircra , there has been a
historic progression where ground-based anti-aircra artillery
was avoidable by aircra use of the wider airspace (obstacles
or altitude) until aerial interdiction patrols were introduced to
either intercept the enemy or force them into lower altitudes
and the kill-zone.  e  exibility a orded by aircra designed
for air-combat extended the e ectiveness of a defense.
 us, it is easy to extend this same natural progression to
aerial combat with unmanned systems. Whereas we current-
ly use centralized, ground-based systems, the right type of
2 Data-sheet for Intel Drone Light Shows states, current max-speed up to 17 m/s (38 mph) (Intel, 2021)
friendly UASs using low-SWaP payloads could make aerial
interdiction patrol and improved airspace control a reality.
Instead of designing only general-purpose EW platforms like
the MADIS, Sentry Tower, and Skytracker, the DOD and DHS
can develop a suite of aerial interdiction platforms designed
for purpose-built EW and cyber-attacks. Just as aircra have
speci c mission sets, the same should be said for C-UAS.  ere
is a reason, the A-10 does not do the job of the F-22 or vice
versa. While the A-10 can  ght against an aerial threat, it does
not have the speed, maneuverability, or weaponry like the F-22
to  ght e ectively. Similarly, the F-22 is not designed for the
close-air support a orded by the A-10’s 30mm Gatlin gun (Air
Combat Command, Public A airs O ce, 2020).
 e maneuverability a orded by decentralization of
technology is essential to counteract the current centralized
methods. Instead of static towers with limited, or no mobility,
networking a family of mobile devices designed to tackle each
subset of the C-UAS problem leads to maneuverability. For ex-
ample, an airborne C-UAS device designed to  t in the payload
bay of a  xed-wing Group 2 UAS can e ectively mitigate ene-
my UASs for over 24-hours by overcoming the signal attenua-
tion that occurs in ground-to-air systems like the Sentry Tower,
MADIS, and DroneDefender.
Case Study—Defending a Hydro-Electric
Power Facility
Example Scenario:
Consider the following case study of defense of a hydro-electric
power facility on the Paci c west coast as the target.
Begin Scenario:
At the hydro-electric facility, the guard on watch receives
noti cation from the northeast tower’s radar sensor that there
is a 95% chance of the presence of multiple UASs moving at
20 miles-per-hour towards the tower. A few seconds later, the
guard receives another noti cation, this time of 10 UASs  ying
at 25 miles-per-hour2 directly at the southwest tower located
on the dam’s primary entry way.  e guard has a system of typ-
ical and current mitigation measures available at his disposal
via a display.  e display shows a heterogeneous swarm operat-
ing on the 2.4 GHz band. Due to the swarms’ rapid speed and
multi-directional attack, the guard chooses to jam the entire
2.4 GHz band using the northeast and south tower’s omnidi-
rectional antenna suites.
 e jamming e ect causes the UAS devices to act as if they
Reducing Asymmetry in Countering Unmanned Aerial Systems
ones experienced over the past decade.
However, as this section has noted, and
Table 1 summarizes, there are serious
limitations associated with the current
technology.  erefore, it is necessary
to look to the past to the initial stages
of aerial warfare, and how we might
introduce the same lessons learned to
countering unmanned aircra .
Cyber
Cyber mitigation measures are the
ultimate compliment to traditional elec-
tronic attack mitigation measures like RF
jamming. Instead of putting broadband
noise into the ether like broadband noise
jamming, cyber-attacks o er a scalpel’s
edge approach to C-UAS. Because UASs
operate using the same digital modula-
tion principles as terrestrial information
systems, they are also vulnerable to the
same attacks conducted over the past
few decades. While there are inherent
technical limitations to each cyber-attack
technique, this methodology typically re-
quires less power because of the a priori
knowledge about an information system.
Second, cyber-attacks lower the risk of
collateral damage to surrounding infra-
structure. And  nally, because there are
lower SWaP requirements in comparison
to RF jamming, delivering cyber-attacks
against adversarial UASs from a friendly
UAS becomes reality.  is section will
discuss cyber-attack techniques that
gained prominence in the past two
decades and how the attacks can be used
to target UASs.
A Man-in-the-Middle (MITM)
occurs when an adversary intercepts the
communication between two commu-
nicating devices, allowing the attacker
to alter or obtain information in the
exchange (Conti et al., 2016).  is attack
compromises the integrity, con den-
tiality, and access control of a given
security scheme without ever notifying
the server or the client. By subverting
access controls and intercepting the communications, an attacker can subsequently
alter and manipulate the information transmission between devices at their dis-
cretion—including the hijacking a target or spoo ng Global Navigation Satellite
System (GNSS) navigation (Common Attack Pattern Enumeration and Classi cation
(CAPEC), 2021). Figure 4 represents an impersonation attack where Eve maliciously
spoofs messages, i.e., sends forged messages to Bob, who believes he is speaking with
Alice. Meanwhile, Alice cannot regain connection to Bob because Eve has blocked
her ability to communicate.
According to the CAPEC, a cyber-attack community resource operated by the
government contracted MITRE Corporation, a MITM has the following prereq-
uisites:  rst, two entities must be communicating with insu cient cybersecurity
protections, allowing an attacker to eavesdrop on the communication exchange
with or without the target’s knowledge. Second, there is a lack of su cient mutual
authentication between the targets giving way to attacker interposition. From this
point, an attacker can subsequently manipulate the actions of its target (Common
Attack Pattern Enumeration and Classi cation (CAPEC), 2021). Given that a MITM
is reliant upon the exploitation of protocol or system vulnerabilities, it can be viewed
as more of an end state vice an attack vector as seen in Figure 4. In this  gure, Eve
is the MITM seeking to intercept the network tra c between Alice and Bob. Once
Eve can establish a network connection either between her targets, or spoo ng one
to the other, she can then conduct a variety of attacks, including the hijacking of the
network tra c.
While much di erent from a MITM, Denial-of-Service (DoS) protocol attacks
such as UDP (CERT Division, 1997) and TCP/SYN  oods (CERT Division, 2000),
or deauthentication (Bellardo & Savage, 2003) attacks can be an integral part of
achieving that end state. Both the UDP and TCP/SYN  ood are examples of DoS
attacks that are more e ective when multiple systems are used as sources of attack
tra c (Douligeris & Mitrokotsa, 2004).  is creates a Distributed-DoS (DDoS) using
computers and other networked devices to create a surreptitious botnet that prevents
normal communications from occurring as planned (Mirkovic & Reiher, 2004). Both
 ood attacks are easy to carry out using open-source tools like Low-Orbit Ion Can-
non (Nagpal et al., 2015) or hping3 (San lippo, 2006) to  ood a target server with
TCP or UDP packets to disrupt the service connection. DDoS attacks gained partic-
ular prominence in the late 2000s and early 2010s when the hacktivist group Anon-
ymous used these vulnerabilities to shut down the service connections at Visa and
Mastercard a er the payments companies removed their support for the WikiLeaks
website (Olson, 2012).  e DDoS is particularly sinister if implemented properly as
FIGURE 4. Impersonation Attack
88 | March 2023 | No. 135-1 NAVAL ENGINEERS JOURNAL

Delivered by Ingenta
Date : Wed, 12 Apr 2023 20:53:12 IP : 205.155.65.226
Reducing Asymmetry in Countering Unmanned Aerial Systems
this type of attack is unpreventable and can only be mitigated
through  rewall strengthening and  ltering protections.
GNSS spoo ng is an attack method where a spoofer gen-
erates a counterfeit signal for each authentic signal received to
distort the relative true location of a target in favor of a coun-
terfeit location that is more favorable for the spoofer (Kerns et
al., 2014). For an attacker to su ciently exert control of a target
device via GNSS spoo ng, the attacker must capture the GNSS
signal of interest dynamically or through a priori knowledge.
GNSS spoo ng requires the insertion of a MITM but can be
especially e ective in negating an adversary’s use of waypoints
for UAS movement and control.
 e cyber-attack techniques outlined in the preceding para-
graphs provide a baseline for attack vectors against adversarial
UASs. To make this a fully realized e ort, a library of attacks
is needed speci cally designed to mitigate the threats posed
by commercial UASs and integrated with a menu of options
on a user interface.  is interface could be fully automated,
giving the operator-on-the-loop a common operating picture
of local threats and actions taken that the operator needs to be
alerted to.
While this was only lightly touched on in the introduction,
cyber-attacks notably consume less power than RF jamming.
Each attack type exploits a di erent protocol vulnerability than
the other and, while some can be patched easily, many UAS
manufacturers continue to design and build UASs with known
vulnerabilities. For many consumers, a fully optimized prod-
uct at a low price point is more important than data privacy
and security.  e cyber-attack techniques discussed in this
section are not meant to be a one-size  ts all approach like RF
jamming, but instead they are meant to give a variety of attack
solutions for escalation of force procedures in countering
unmanned systems.
Progression of Counter-Aerial
System Development
In aerial defense for standard enemy aircra , there has been a
historic progression where ground-based anti-aircra artillery
was avoidable by aircra use of the wider airspace (obstacles
or altitude) until aerial interdiction patrols were introduced to
either intercept the enemy or force them into lower altitudes
and the kill-zone.  e  exibility a orded by aircra designed
for air-combat extended the e ectiveness of a defense.
 us, it is easy to extend this same natural progression to
aerial combat with unmanned systems. Whereas we current-
ly use centralized, ground-based systems, the right type of
2 Data-sheet for Intel Drone Light Shows states, current max-speed up to 17 m/s (38 mph) (Intel, 2021)
friendly UASs using low-SWaP payloads could make aerial
interdiction patrol and improved airspace control a reality.
Instead of designing only general-purpose EW platforms like
the MADIS, Sentry Tower, and Skytracker, the DOD and DHS
can develop a suite of aerial interdiction platforms designed
for purpose-built EW and cyber-attacks. Just as aircra have
speci c mission sets, the same should be said for C-UAS.  ere
is a reason, the A-10 does not do the job of the F-22 or vice
versa. While the A-10 can  ght against an aerial threat, it does
not have the speed, maneuverability, or weaponry like the F-22
to  ght e ectively. Similarly, the F-22 is not designed for the
close-air support a orded by the A-10’s 30mm Gatlin gun (Air
Combat Command, Public A airs O ce, 2020).
 e maneuverability a orded by decentralization of
technology is essential to counteract the current centralized
methods. Instead of static towers with limited, or no mobility,
networking a family of mobile devices designed to tackle each
subset of the C-UAS problem leads to maneuverability. For ex-
ample, an airborne C-UAS device designed to  t in the payload
bay of a  xed-wing Group 2 UAS can e ectively mitigate ene-
my UASs for over 24-hours by overcoming the signal attenua-
tion that occurs in ground-to-air systems like the Sentry Tower,
MADIS, and DroneDefender.
Case Study—Defending a Hydro-Electric
Power Facility
Example Scenario:
Consider the following case study of defense of a hydro-electric
power facility on the Paci c west coast as the target.
Begin Scenario:
At the hydro-electric facility, the guard on watch receives
noti cation from the northeast tower’s radar sensor that there
is a 95% chance of the presence of multiple UASs moving at
20 miles-per-hour towards the tower. A few seconds later, the
guard receives another noti cation, this time of 10 UASs  ying
at 25 miles-per-hour2 directly at the southwest tower located
on the dam’s primary entry way.  e guard has a system of typ-
ical and current mitigation measures available at his disposal
via a display.  e display shows a heterogeneous swarm operat-
ing on the 2.4 GHz band. Due to the swarms’ rapid speed and
multi-directional attack, the guard chooses to jam the entire
2.4 GHz band using the northeast and south tower’s omnidi-
rectional antenna suites.
 e jamming e ect causes the UAS devices to act as if they
Reducing Asymmetry in Countering Unmanned Aerial Systems
ones experienced over the past decade.
However, as this section has noted, and
Table 1 summarizes, there are serious
limitations associated with the current
technology.  erefore, it is necessary
to look to the past to the initial stages
of aerial warfare, and how we might
introduce the same lessons learned to
countering unmanned aircra .
Cyber
Cyber mitigation measures are the
ultimate compliment to traditional elec-
tronic attack mitigation measures like RF
jamming. Instead of putting broadband
noise into the ether like broadband noise
jamming, cyber-attacks o er a scalpel’s
edge approach to C-UAS. Because UASs
operate using the same digital modula-
tion principles as terrestrial information
systems, they are also vulnerable to the
same attacks conducted over the past
few decades. While there are inherent
technical limitations to each cyber-attack
technique, this methodology typically re-
quires less power because of the a priori
knowledge about an information system.
Second, cyber-attacks lower the risk of
collateral damage to surrounding infra-
structure. And  nally, because there are
lower SWaP requirements in comparison
to RF jamming, delivering cyber-attacks
against adversarial UASs from a friendly
UAS becomes reality.  is section will
discuss cyber-attack techniques that
gained prominence in the past two
decades and how the attacks can be used
to target UASs.
A Man-in-the-Middle (MITM)
occurs when an adversary intercepts the
communication between two commu-
nicating devices, allowing the attacker
to alter or obtain information in the
exchange (Conti et al., 2016).  is attack
compromises the integrity, con den-
tiality, and access control of a given
security scheme without ever notifying
the server or the client. By subverting
access controls and intercepting the communications, an attacker can subsequently
alter and manipulate the information transmission between devices at their dis-
cretion—including the hijacking a target or spoo ng Global Navigation Satellite
System (GNSS) navigation (Common Attack Pattern Enumeration and Classi cation
(CAPEC), 2021). Figure 4 represents an impersonation attack where Eve maliciously
spoofs messages, i.e., sends forged messages to Bob, who believes he is speaking with
Alice. Meanwhile, Alice cannot regain connection to Bob because Eve has blocked
her ability to communicate.
According to the CAPEC, a cyber-attack community resource operated by the
government contracted MITRE Corporation, a MITM has the following prereq-
uisites:  rst, two entities must be communicating with insu cient cybersecurity
protections, allowing an attacker to eavesdrop on the communication exchange
with or without the target’s knowledge. Second, there is a lack of su cient mutual
authentication between the targets giving way to attacker interposition. From this
point, an attacker can subsequently manipulate the actions of its target (Common
Attack Pattern Enumeration and Classi cation (CAPEC), 2021). Given that a MITM
is reliant upon the exploitation of protocol or system vulnerabilities, it can be viewed
as more of an end state vice an attack vector as seen in Figure 4. In this  gure, Eve
is the MITM seeking to intercept the network tra c between Alice and Bob. Once
Eve can establish a network connection either between her targets, or spoo ng one
to the other, she can then conduct a variety of attacks, including the hijacking of the
network tra c.
While much di erent from a MITM, Denial-of-Service (DoS) protocol attacks
such as UDP (CERT Division, 1997) and TCP/SYN  oods (CERT Division, 2000),
or deauthentication (Bellardo & Savage, 2003) attacks can be an integral part of
achieving that end state. Both the UDP and TCP/SYN  ood are examples of DoS
attacks that are more e ective when multiple systems are used as sources of attack
tra c (Douligeris & Mitrokotsa, 2004).  is creates a Distributed-DoS (DDoS) using
computers and other networked devices to create a surreptitious botnet that prevents
normal communications from occurring as planned (Mirkovic & Reiher, 2004). Both
 ood attacks are easy to carry out using open-source tools like Low-Orbit Ion Can-
non (Nagpal et al., 2015) or hping3 (San lippo, 2006) to  ood a target server with
TCP or UDP packets to disrupt the service connection. DDoS attacks gained partic-
ular prominence in the late 2000s and early 2010s when the hacktivist group Anon-
ymous used these vulnerabilities to shut down the service connections at Visa and
Mastercard a er the payments companies removed their support for the WikiLeaks
website (Olson, 2012).  e DDoS is particularly sinister if implemented properly as
FIGURE 4. Impersonation Attack
NAVAL ENGINEERS JOURNAL March 2023 | No. 135-1 | 89

Delivered by Ingenta
Date : Wed, 12 Apr 2023 20:53:12 IP : 205.155.65.226
Reducing Asymmetry in Countering Unmanned Aerial Systems
Designers of aerial C-UAS systems
should focus on the technological
advancements of the past three decades
and develop low-size, weight, and power
(SWaP) EW and cyber-attack techniques
for UAS mitigation. While we recognize
(and Table 2 represents) the limitations
with UASs as stand-in EW and cyber-at-
tack platforms, these aerial systems o er
 exibility and maneuverability on the
battle eld with a targeted interdiction
to overcome the limitations of ground-
based technologies. Finally, the lack of
interference from telephone poles, trees,
and buildings a ords aerial systems the
ability to extend the operational range of
non-kinetic countermeasures. With an
aerial variant, this operational range is
only limited by the output power of the
transmitting C-UAS device, which can
be varied by using host power or its own
power source.
Current systems and methods for
countering UAS have found many
successes in the past decade. However,
because the Sentry Tower, Skytracker,
and MADIS are terrestrial systems, they
only provide limited robustness and
depth as a solution set. Additionally, the
research and development of C-UAS
emerging technologies fails to address
the asymmetry posed by UAS threats.
Instead of getting smaller and cheaper,
tomorrow’s directed energy weapons
and lasers are increasingly expensive to
build, manufacture, and sustain over the
product lifecycle.
 us, reconsideration of C-UAS
methods and how such systems are
procured and integrated within the
DOD and DHS is advised. By devel-
oping a family of networked systems
that focuses on cyber-attack method-
ologies, the current systems on hand
will be able to withstand a multi-wave
and multi-frequency attack.  e use
of UASs during the ISIS insurgency, in
the Nagorno-Karabakh war, and in the
Ukrainian con ict prove that any state,
or non-state, actor with modest funding
can build an air force to cripple their
adversary.  e framework proposed
herein seeks to address and mitigate that
asymmetry by leveraging the techno-
logical expertise and intelligence of the
defense industrial base.
AUTHOR BIOGRAPHIES
CAPTAIN CHRISTIAN THIESSEN is an
Infantry O cer in the Marine Corps.
He received a dual Master of Science
degree in Information Warfare Systems
Engineering and Applied Design for
Innovation at the Naval Postgraduate
School. He currently serves as the
Technical Information Operations O cer
with the 13th Marine Expeditionary Unit.
DR. BRITTA HALE is a cryptographer and
Assistant Professor in Computer Science
at the Naval Postgraduate School in
Computer Science. Dr. Hale has a PhD
from the Norwegian University of Science
and Technology (NTNU), and a Master of
Science from Royal Holloway University
of London (RHUL). Her focus areas
include cryptography and cryptographic
applications, extending to security
applications for uncrewed systems and
counter-uncrewed systems, and other
emerging environments and technologies.
She has experience in industry research on
security for critical systems. Dr. Hale is a
member of the Internet Engineering Task
Force (IETF) and International Association
for Cryptologic Research (IACR).
DR. DOUGLAS L. VAN BOSSUYT is
an Assistant Professor in the Systems
Engineering Department at the Naval
Postgraduate School in Monterey,
California. His research focuses on
the nexus of failure and risk analysis,
functional modeling and conceptual
system design, trade-o studies and
decision-making, and resilient systems.
He has published over 60 peer reviewed
technical journal articles and conference
papers on these and related topics and
holds 2 U.S. patents. He holds a Ph. D
in mechanical engineering with a minor
in industrial engineering from Oregon
State University.
Future Systems Future C-UAS Pros Future C-UAS Cons
Ground to Air
AFRL NINJA
MADIS/FWS
Inter-Networked Systems
mmWave Directed Energy
Reliability, Fully Funded
Mobility
Small Form Factor
Handheld
Bulky
High-Power Consumption
Easily Disrupted
BBN Jamming Only
Air to Air
Autonomous Stand-in
Hijackers
Cryptographic Protocol
Attacks
DDoS Attacks
Stand-in GNSS Jammers
Stand-in RF Jammers
Usurp Control of Target
Precision
E ective against Swarms
Easier to Implement
Close Proximity to Target
Requires Target RE
Requires Target Pro le
Spreading Complexity
Attack Pro le Modi cation
Potential Communication
Fratricide
TABLE 2. Pros and Cons of Future C-UAS Technology
Reducing Asymmetry in Countering Unmanned Aerial Systems
have hit an invisible wall—a few collide and drop out of the
sky, and the swarm stops in place and continues to hover. At
this point several more UASs self-land. Meanwhile, back at
the command center, the guard receives an updated situation
report from his heads-up display, showing the targeted UASs
returning to their point of origin causing the guard to assume
that the system is working. As the jamming system resets
and the guard is about to send in a report on the attack, the
tracking system identi es another UAS swarm approaching
the southwest tower, this time operating on the 5GHz band.
Since the system is resetting, the guard is unable to re-start the
broadband jam, and the UAS deliver shape charge, a er shape
charge to the walls of the dam, causing explosions along the
dam’s center. As the guard contacts local authorities to inform
the need for evacuation, the dam bursts, and tens of thousands
of tons of water pour out.
 e dam  nally disintegrates, and power immediately goes
out in the nearby metropolitan city as well as signi cant parts
of the surrounding region, because of their reliance on the
power generated by the dam. Airplanes trying to land in the
city airport lose connection with the air tra c control station
and while the ground crews work to get the backup generators
operational, many  ights are diverted.  e larger aircra can
make it to other airports, but smaller planes with dwindling
fuel supplies are forced to  nd open clearings for emergency
landings in the heavily wooded Paci c Northwest.
A er the UAS attack, large-scale physical infrastructure
damage is identi ed, including roads, power grids, buildings,
and the dam itself. Power loss disrupted businesses, transport,
and security systems. Moreover, back-up generator function-
ality does not cover the months needed to restabilize power,
leading to power grid blackouts and interruptions in normal
operations. In comparison, the entire attack was executed by
low-cost commercial devices.
Example Scenario (new version):
In the ensuing scenario, we will revisit the same attack, but the
C-UAS protections are enhanced with a security patrol of UASs
armed with drone hijacker devices.
Begin Scenario:
At the hydro-electric facility, each tower was augmented with
a new type of UAS security patrols: drone hijackers (“Alphas”).
 is was a signi cant upgrade in the defense as the Alphas are
deployed forward of the sentry towers on a patrol schedule and
can receive mid- ight updates from the towers to guide their
attack methods. Additionally, given their small form-factor
and low-power consumption, the Alphas can patrol for an
hour a piece, giving the watch o cers a persistent presence to
augment the sentry towers.
 e guard on watch receives noti cation from the northeast
tower’s radar sensor that there is a 95% chance of the presence
of multiple UAS moving at 20 miles-per-hour towards the tow-
er. A few seconds later, the guard receives another noti cation,
this time of 10 UASs  ying at 25 miles-per-hour directly at the
southwest tower located on the dam’s primary entry way.  e
guard’s display shows a heterogeneous swarm operating on the
2.4 GHz band. Due to the swarms’ rapid speed and multi-di-
rectional attack, the guard chooses to deploy the Alphas against
the approaching swarm for mid-air interdiction.  e guard
reserves the capability to jam the entire 2.4 GHz band using the
northeast and south tower’s omnidirectional antenna suites as
a back-up.
 e Alphas begin to issue a  ood UDP packets and deau-
thentication frames. As with the centralized system, the two
swarms function as if they have hit an invisible wall and a few
drop out of the sky, and the swarm stops in place and continues
to hover. Several more UASs begin to-self land.
Meanwhile, back at the command center, the guard receives
situation updates from his heads-up display, showing several
UASs dropping out and the guard assumes the system is work-
ing. As the guard is about to send in a report on the attack, the
tracking system identi es another UAS swarm approaching the
southwest tower.  e guard sends an updated instruction set to
the Alphas before activating the jamming system, sending RF
noise out of the tower’s omnidirectional antennas to broadband
jam the entire 5 GHz band.  e new UAS swarm stops, and
the Alphas take a forward position for preemptively mitigating
any new incoming threats. In the ensuing 10 minutes, a ground
team is dispatched and captures  ve suspects on all-terrain
vehicles carrying several large briefcases  lled with small UASs
and explosives.
Framework Comparison and Conclusion
In summary, the current framework, while su cient for the
C-UAS  ght in the late-2010s and early 2020s, will likely be
outpaced by emerging drone technologies in the coming
decades. More speci cally, when drone swarms become more
readily available, they will increasingly be a threat to criti-
cal infrastructure and military installations.  e proposed
ground-to-air C-UAS systems under development by Northrup
Grumman (Northrup Grumman, 2020) and other defense
industrial base companies may be necessary additions for the
high-end C-UAS  ght. However, there are inherent technical
limitations to overcome using terrestrial systems, creating
an opportunity to use UASs as aerial interdiction platforms.
90 | March 2023 | No. 135-1 NAVAL ENGINEERS JOURNAL

Delivered by Ingenta
Date : Wed, 12 Apr 2023 20:53:12 IP : 205.155.65.226
Reducing Asymmetry in Countering Unmanned Aerial Systems
Designers of aerial C-UAS systems
should focus on the technological
advancements of the past three decades
and develop low-size, weight, and power
(SWaP) EW and cyber-attack techniques
for UAS mitigation. While we recognize
(and Table 2 represents) the limitations
with UASs as stand-in EW and cyber-at-
tack platforms, these aerial systems o er
 exibility and maneuverability on the
battle eld with a targeted interdiction
to overcome the limitations of ground-
based technologies. Finally, the lack of
interference from telephone poles, trees,
and buildings a ords aerial systems the
ability to extend the operational range of
non-kinetic countermeasures. With an
aerial variant, this operational range is
only limited by the output power of the
transmitting C-UAS device, which can
be varied by using host power or its own
power source.
Current systems and methods for
countering UAS have found many
successes in the past decade. However,
because the Sentry Tower, Skytracker,
and MADIS are terrestrial systems, they
only provide limited robustness and
depth as a solution set. Additionally, the
research and development of C-UAS
emerging technologies fails to address
the asymmetry posed by UAS threats.
Instead of getting smaller and cheaper,
tomorrow’s directed energy weapons
and lasers are increasingly expensive to
build, manufacture, and sustain over the
product lifecycle.
 us, reconsideration of C-UAS
methods and how such systems are
procured and integrated within the
DOD and DHS is advised. By devel-
oping a family of networked systems
that focuses on cyber-attack method-
ologies, the current systems on hand
will be able to withstand a multi-wave
and multi-frequency attack.  e use
of UASs during the ISIS insurgency, in
the Nagorno-Karabakh war, and in the
Ukrainian con ict prove that any state,
or non-state, actor with modest funding
can build an air force to cripple their
adversary.  e framework proposed
herein seeks to address and mitigate that
asymmetry by leveraging the techno-
logical expertise and intelligence of the
defense industrial base.
AUTHOR BIOGRAPHIES
CAPTAIN CHRISTIAN THIESSEN is an
Infantry O cer in the Marine Corps.
He received a dual Master of Science
degree in Information Warfare Systems
Engineering and Applied Design for
Innovation at the Naval Postgraduate
School. He currently serves as the
Technical Information Operations O cer
with the 13th Marine Expeditionary Unit.
DR. BRITTA HALE is a cryptographer and
Assistant Professor in Computer Science
at the Naval Postgraduate School in
Computer Science. Dr. Hale has a PhD
from the Norwegian University of Science
and Technology (NTNU), and a Master of
Science from Royal Holloway University
of London (RHUL). Her focus areas
include cryptography and cryptographic
applications, extending to security
applications for uncrewed systems and
counter-uncrewed systems, and other
emerging environments and technologies.
She has experience in industry research on
security for critical systems. Dr. Hale is a
member of the Internet Engineering Task
Force (IETF) and International Association
for Cryptologic Research (IACR).
DR. DOUGLAS L. VAN BOSSUYT is
an Assistant Professor in the Systems
Engineering Department at the Naval
Postgraduate School in Monterey,
California. His research focuses on
the nexus of failure and risk analysis,
functional modeling and conceptual
system design, trade-o studies and
decision-making, and resilient systems.
He has published over 60 peer reviewed
technical journal articles and conference
papers on these and related topics and
holds 2 U.S. patents. He holds a Ph. D
in mechanical engineering with a minor
in industrial engineering from Oregon
State University.
Future Systems Future C-UAS Pros Future C-UAS Cons
Ground to Air
AFRL NINJA
MADIS/FWS
Inter-Networked Systems
mmWave Directed Energy
Reliability, Fully Funded
Mobility
Small Form Factor
Handheld
Bulky
High-Power Consumption
Easily Disrupted
BBN Jamming Only
Air to Air
Autonomous Stand-in
Hijackers
Cryptographic Protocol
Attacks
DDoS Attacks
Stand-in GNSS Jammers
Stand-in RF Jammers
Usurp Control of Target
Precision
E ective against Swarms
Easier to Implement
Close Proximity to Target
Requires Target RE
Requires Target Pro le
Spreading Complexity
Attack Pro le Modi cation
Potential Communication
Fratricide
TABLE 2. Pros and Cons of Future C-UAS Technology
Reducing Asymmetry in Countering Unmanned Aerial Systems
have hit an invisible wall—a few collide and drop out of the
sky, and the swarm stops in place and continues to hover. At
this point several more UASs self-land. Meanwhile, back at
the command center, the guard receives an updated situation
report from his heads-up display, showing the targeted UASs
returning to their point of origin causing the guard to assume
that the system is working. As the jamming system resets
and the guard is about to send in a report on the attack, the
tracking system identi es another UAS swarm approaching
the southwest tower, this time operating on the 5GHz band.
Since the system is resetting, the guard is unable to re-start the
broadband jam, and the UAS deliver shape charge, a er shape
charge to the walls of the dam, causing explosions along the
dam’s center. As the guard contacts local authorities to inform
the need for evacuation, the dam bursts, and tens of thousands
of tons of water pour out.
 e dam  nally disintegrates, and power immediately goes
out in the nearby metropolitan city as well as signi cant parts
of the surrounding region, because of their reliance on the
power generated by the dam. Airplanes trying to land in the
city airport lose connection with the air tra c control station
and while the ground crews work to get the backup generators
operational, many  ights are diverted.  e larger aircra can
make it to other airports, but smaller planes with dwindling
fuel supplies are forced to  nd open clearings for emergency
landings in the heavily wooded Paci c Northwest.
A er the UAS attack, large-scale physical infrastructure
damage is identi ed, including roads, power grids, buildings,
and the dam itself. Power loss disrupted businesses, transport,
and security systems. Moreover, back-up generator function-
ality does not cover the months needed to restabilize power,
leading to power grid blackouts and interruptions in normal
operations. In comparison, the entire attack was executed by
low-cost commercial devices.
Example Scenario (new version):
In the ensuing scenario, we will revisit the same attack, but the
C-UAS protections are enhanced with a security patrol of UASs
armed with drone hijacker devices.
Begin Scenario:
At the hydro-electric facility, each tower was augmented with
a new type of UAS security patrols: drone hijackers (“Alphas”).
 is was a signi cant upgrade in the defense as the Alphas are
deployed forward of the sentry towers on a patrol schedule and
can receive mid- ight updates from the towers to guide their
attack methods. Additionally, given their small form-factor
and low-power consumption, the Alphas can patrol for an
hour a piece, giving the watch o cers a persistent presence to
augment the sentry towers.
 e guard on watch receives noti cation from the northeast
tower’s radar sensor that there is a 95% chance of the presence
of multiple UAS moving at 20 miles-per-hour towards the tow-
er. A few seconds later, the guard receives another noti cation,
this time of 10 UASs  ying at 25 miles-per-hour directly at the
southwest tower located on the dam’s primary entry way.  e
guard’s display shows a heterogeneous swarm operating on the
2.4 GHz band. Due to the swarms’ rapid speed and multi-di-
rectional attack, the guard chooses to deploy the Alphas against
the approaching swarm for mid-air interdiction.  e guard
reserves the capability to jam the entire 2.4 GHz band using the
northeast and south tower’s omnidirectional antenna suites as
a back-up.
 e Alphas begin to issue a  ood UDP packets and deau-
thentication frames. As with the centralized system, the two
swarms function as if they have hit an invisible wall and a few
drop out of the sky, and the swarm stops in place and continues
to hover. Several more UASs begin to-self land.
Meanwhile, back at the command center, the guard receives
situation updates from his heads-up display, showing several
UASs dropping out and the guard assumes the system is work-
ing. As the guard is about to send in a report on the attack, the
tracking system identi es another UAS swarm approaching the
southwest tower.  e guard sends an updated instruction set to
the Alphas before activating the jamming system, sending RF
noise out of the tower’s omnidirectional antennas to broadband
jam the entire 5 GHz band.  e new UAS swarm stops, and
the Alphas take a forward position for preemptively mitigating
any new incoming threats. In the ensuing 10 minutes, a ground
team is dispatched and captures  ve suspects on all-terrain
vehicles carrying several large briefcases  lled with small UASs
and explosives.
Framework Comparison and Conclusion
In summary, the current framework, while su cient for the
C-UAS  ght in the late-2010s and early 2020s, will likely be
outpaced by emerging drone technologies in the coming
decades. More speci cally, when drone swarms become more
readily available, they will increasingly be a threat to criti-
cal infrastructure and military installations.  e proposed
ground-to-air C-UAS systems under development by Northrup
Grumman (Northrup Grumman, 2020) and other defense
industrial base companies may be necessary additions for the
high-end C-UAS  ght. However, there are inherent technical
limitations to overcome using terrestrial systems, creating
an opportunity to use UASs as aerial interdiction platforms.
NAVAL ENGINEERS JOURNAL March 2023 | No. 135-1 | 91

Delivered by Ingenta
Date : Wed, 12 Apr 2023 20:53:12 IP : 205.155.65.226
Reducing Asymmetry in Countering Unmanned Aerial Systems
Sklar, B. (2001). Digital Communications:
Fundamentals and Applications (Second).
Prentic Hall Professional Technical Reference.
Stutzman, W. L., &  iele, G. A. (2013). Antenna
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Sukhankin, S. (2021a).  e Second Karabakh
War: Lessons and Implications for Russia (Part
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Sukhankin, S. (2021b).  e Second Karabakh
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Байрактари в роботі. Наші оператори
ювелірно криють колони ворожих військ.
Знищено російський БУК в районі Малина
Житомирської області. Бійтеся, вороги!
Не буде вам спокою на нашій землі!
Https://facebook.com/100068564836091/
posts/257372956558197/ https://t.co/
dH2UEUbKST [Twitter]. @ArmedForcesUkr.
https://twitter.com/ArmedForcesUkr/
status/1497997019515961347
U.S. Marine Corps. (2000). Marine Corps
War ghting Publication 3-11.3: Scouting and
Patrolling. Headquarters Marine Corps.
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U.S. Marine Corps. (2017). Ri e Platoon in the
Defense B3J0435XQ Student Handout.  e
Basic O cers Course, Marine Corps Training
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War ghting Publication 3-01: O ensive and
Defensive Tactics. Headquarters Marine Corps.
Wang, J., Liu, Y., & Song, H. (2021). Counter-
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MAES.2020.3015537
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use-of-weaponized-drones-by-isis-spurs-
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11e6-8d72-263470bf0401_story.html
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counter-unmanned-aerial-systems-c-uas
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92 | March 2023 | No. 135-1 NAVAL ENGINEERS JOURNAL

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Date : Wed, 12 Apr 2023 20:53:12 IP : 205.155.65.226
Reducing Asymmetry in Countering Unmanned Aerial Systems
Sklar, B. (2001). Digital Communications:
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Байрактари в роботі. Наші оператори
ювелірно криють колони ворожих військ.
Знищено російський БУК в районі Малина
Житомирської області. Бійтеся, вороги!
Не буде вам спокою на нашій землі!
Https://facebook.com/100068564836091/
posts/257372956558197/ https://t.co/
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https://twitter.com/ArmedForcesUkr/
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War ghting Publication 3-11.3: Scouting and
Patrolling. Headquarters Marine Corps.
U.S. Marine Corps. (2002). Marine Corps
War ghting Publication 3-1: Ground Combat
Operations. Headquarters Marine Corps.
U.S. Marine Corps. (2017). Ri e Platoon in the
Defense B3J0435XQ Student Handout.  e
Basic O cers Course, Marine Corps Training
Command.
U.S. Marine Corps. (2019). Marine Corps
War ghting Publication 3-01: O ensive and
Defensive Tactics. Headquarters Marine Corps.
Wang, J., Liu, Y., & Song, H. (2021). Counter-
Unmanned Aircra System(s) (C-UAS): State
of the Art, Challenges, and Future Trends.
IEEE Aerospace and Electronic Systems
Magazine, 36(3), 4–29. https://doi.org/10.1109/
MAES.2020.3015537
Warrick, J. (2017, February 21). Use of
weaponized drones by ISIS spurs terrorism
fears. Washington Post. https://www.
washingtonpost.com/world/national-security/
use-of-weaponized-drones-by-isis-spurs-
terrorism-fears/2017/02/21/9d83d51e-f382-
11e6-8d72-263470bf0401_story.html
REGISTER NOW!
www.navalengineers.org/Symposia/ISS2023
Reducing Asymmetry in Countering Unmanned Aerial Systems
REFERENCES
Air Combat Command, Public A airs
O ce. (2020, December). A-10C
 underbolt II. Air Force. https://www.
af.mil/About-Us/Fact-Sheets/Display/
Article/104490/a-10c-thunderbolt-ii/
Almohammad, A., & Speckhard, A. (2017).
ISIS Drones: Evolution, Leadership, Bases,
Operations and Logistics (ICSVE Research
Reports). International Center for the Study of
Violent Extremism. https://www.icsve.org/isis-
drones-evolution-leadership-bases-operations-
and-logistics/
Anduril. (2021). Anduril—Sentry Tower
[Defense Technology]. Anduril.Com. https://
www.anduril.com/hardware/sentry/
Arreguin-To , I. (2005). How the Weak Win
Wars: A  eory of Asymmetric Con ict.
Cambridge University Press.
Barrett, B. (2019, July 22).  e Marines’
New Drone-Killer Aces Its First Test.
Wired. https://www.wired.com/story/
iran-drone-marines-energy-weapon-lmadis/
Bellardo, J., & Savage, S. (2003, May 16). 802.11
Denial-of-Service Attacks: Real Vulnerabilities
and Practical Solutions. 12th USENIX
Security Symposium. USENIX Security 2003,
Washington D.C. https://www.usenix.org/
legacy/events/sec03/tech/full_papers/bellardo/
bellardo_html/
Brown, K., Drake, S., Mason, K., Piotrowski,
A., & Swierkowski, L. (2007). A distributed
stand-in EW hunter-killer system. 2007 10th
International Conference on Information
Fusion, 1–8. https://doi.org/10.1109/
ICIF.2007.4407985
CERT Division. (1997). CA-1996-01: UDP
Port Denial-of-Service Attack (CERT
Advisory REV-03.18.2016.0; 1996 CERT
Advisories, pp. 1–4). Carnegie Mellon
University So ware Engineering Institute.
https://resources.sei.cmu.edu/asset_ les/
WhitePaper/1996_019_001_496172.
pdf#page=123
CERT Division. (2000). CA-1996-21: TCP
SYN Flooding and IP Spoo ng Attacks
(CERT Advisory REV-03.18.2016.0; 1996
CERT Advisories, pp. 119–127). Carnegie
Mellon University So ware Engineering
Institute. https://resources.sei.cmu.edu/
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pdf#page=123
Common Attack Pattern Enumeration and
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Carry-O GPS Attack (CAPEC Report
CAPEC-628).  e MITRE Corporation.
https://capec.mitre.org/data/de nitions/628.
html
Conti, M., Dragoni, N., & Lesyk, V. (2016).
A Survey of Man In  e Middle Attacks.
IEEE Communications Surveys Tutorials,
18(3), 2027–2051. https://doi.org/10.1109/
COMST.2016.2548426
Dedrone. (n.d.). Data Sheet—DroneDefender
Counter-UAS Device. Dedrone.
Retrieved January 3, 2022, from https://
gdmissionsystems.com/-/media/General-
Dynamics/Ground-Systems/PDF/
Counter-UAS---Dedrone/DroneDefender-
DataSheet.ashx?la=en&hash=516300C425
D3CDA5C69CBAD29C1886EEFD9EA54A
Douligeris, C., & Mitrokotsa, A. (2004). DDoS
attacks and defense mechanisms: Classi cation
and state-of-the-art. Computer Networks,
44(5), 643–666. https://doi.org/10.1016/j.
comnet.2003.10.003
Intel. (2021). Intel Drone Light Show Premium
Fact Sheet. Intel. https://inteldronelightshows.
com/wp-content/uploads/sites/3/2021/01/
Intel-Drone-Light-Show-Premium-Fact-
Sheet-23112020.pdf
Kerns, A. J., Shepard, D. P., Bhatti, J. A., &
Humphreys, T. E. (2014). Unmanned Aircra
Capture and Control Via GPS Spoo ng.
Journal of Field Robotics, 31(4), 617–636.
https://doi.org/10.1002/rob.21513
Lichtman, M., Jover, R. P., Labib, M., Rao, R.,
Marojevic, V., & Reed, J. H. (2016). LTE/
LTE-A jamming, spoo ng, and sni ng:
 reat assessment and mitigation. IEEE
Communications Magazine, 54(4), 54–61.
https://doi.org/10.1109/MCOM.2016.7452266
Michel, A. H. (2019). Counter-Drone Systems,
2nd Edition (p. 45). Center for the Study of the
Drone, Bard College. https://dronecenter.bard.
edu/ les/2019/12/CSD-CUAS-2nd-Edition-
Web.pdf
Mirkovic, J., & Reiher, P. (2004). A Taxonomy of
DDoS Attack and DDoS Defense Mechanisms.
Association of Computing Machinery, 34(2).
https://doi.org/10.1145/997150.997156
Missile Defense Advocacy Alliance. (2020, July
8). Marine Air Defense Integrated System
(MADIS)—Missile Defense Advocacy
Alliance. Missile Defense Advocacy Alliance:
U.S. - Air Defense, Intercept. https://
missiledefenseadvocacy.org/defense-systems/
marine-air-defense-integrated-system-madis/
Multi-Service Tactics, Techniques, and Procedures
for Air and Missile Defense. (2019). Air Land
Sea Application Center. https://armypubs.
army.mil/epubs/DR_pubs/DR_d/ARN15491-
ATP_3-01.15-000-WEB-1.pdf
Nagpal, B., Sharma, P., Chauhan, N., & Panesar,
A. (2015). DDoS tools: Classi cation, analysis
and comparison. 2015 2nd International
Conference on Computing for Sustainable
Global Development (INDIACom), 342–346.
Northrup Grumman. (2020, July 8). De ning
Possible Against Unmanned Aerial Systems
[Defense Contractor]. Counter Unmanned
Aerial Systems (C-UAS). https://www.
northropgrumman.com/what-we-do/land/
counter-unmanned-aerial-systems-c-uas
Olson, P. (2012). We Are Anonymous: Inside the
Hacker World of LulzSec, Anonymous, and the
Global Cyber Insurgency. Little, Brown. https://
books.google.com/books?id=ncGVPtoZPHcC
Parlin, K., Mahtab Alam, M., & Le Moullec,
Y. (2018). Jamming of UAV remote control
systems using so ware de ned radio.
2018 International Conference on Military
Communications and Information Systems
(ICMCIS), 1–6.
Perrigo, B. (2022, March 1). Ukraine’s
Secret Weapon Against Russia: Turkish
Drones. Time. https://time.com/6153197/
ukraine-russia-turkish-drones-bayraktar/
Pitsky, P. (2021). SkyTracker® Technology Suite
[Defense Contractor]. CACI. https://www.caci.
com/sites/default/ les/2021-06/F424_2106_
Corian%20Flyer.pdf
Poisel, R. (2008). Introduction to Communication
Electronic Warfare Systems (Second).
Artech House, Inc. http://pws.npru.ac.th/
sartthong/data/ les/Introduction%20
to%20Communication%20Electronic%20
Warfare%20Systems.pdf
Poisel, R. (2011). Modern Communication
Jamming Principles and Techniques (Second).
Artech House, Inc.
San lippo, S. (2006). Hping. Hping. http://www.
hping.org/documentation.php
NAVAL ENGINEERS JOURNAL March 2023 | No. 135-1 | 93