Spear Watch: A Thorough Examination to Identify Spear Phishing Attacks

Abstract

A form of cybersecurity assault known as phishing involves hostile actors sending messages while posing as a reliable individual or organization. Spear-phishing assaults target a particular victim, and communications that pretend to be from someone they know and contain personal information are updated to directly address that victim. Spear-phishing takes more planning and effort to complete than phishing. Because these attacks are so skillfully customized, conventional security frequently cannot stop them. They are consequently getting harder to find. The spear phishing emails generally require a sophisticated security protocol, deploying threat detection and response tools. There are many research works with newer techniques applied for such systems. Most of them use AI, ML algorithms in identifying the threat and taking necessary actions. This paper emphasizes the importance of having much more enhanced techniques by means of research & development. To start with, the research this work focuses on exploring various detection techniques, where machine learning, natural language processing algorithms are used especially on behaviour analysis, and anomaly detection. This paper lays a foundation for future research in this area.

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International Journal of Innovative Technology and Exploring Engineering (IJITEE)
ISSN: 2278-3075 (Online), Volume-12 Issue-8, July 2023
46
Published By:
Blue Eyes Intelligence Engineering
and Sciences Publication (BEIESP)
© Copyright: All rights reserved.
Retrieval Number: 100.1/ijitee.H96800712823
DOI: 10.35940/ijitee.H9680.0712823
Journal Website: www.ijitee.org
Spear Watch: A Thorough Examination to Identify
Spear Phishing Attacks
Anjali Shrikant Shukla, Sameer Rajendra Chavan, Srivaramangai R
Abstract: A form of cybersecurity assault known as phishing
involves hostile actors sending messages while posing as a reliable
individual or organization. Spear-phishing assaults target a
particular victim, and communications that pretend to be from
someone they know and contain personal information are updated
to directly address that victim. Spear-phishing takes more
planning and effort to complete than phishing. Because these
attacks are so skillfully customized, conventional security
frequently cannot stop them. They are consequently getting harder
to find. The spear phishing emails generally require a
sophisticated security protocol, deploying threat detection and
response tools. There are many research works with newer
techniques applied for such systems. Most of them use AI, ML
algorithms in identifying the threat and taking necessary actions.
This paper emphasizes the importance of having much more
enhanced techniques by means of research & development. To
start with, the research this work focuses on exploring various
detection techniques, where machine learning, natural language
processing algorithms are used especially on behaviour analysis,
and anomaly detection. This paper lays a foundation for future
research in this area.
Keywords: Spear Phishing, Social Engineering, Email
Analysis, Link Analysis, Email Content Analysis, Attack
Detection, Malicious Emails, Fraudulent Emails.
I. INTRODUCTION
Phishing is one of the types of cyber-attacks in which an
attacker acts as a reliable firm or an individual to mislead
people into disclosing confidential information, such as
passwords, credit card numbers, etc. Phishing attacks
commonly occur through email, but they are also possible via
text messages, phone calls, or even through social media
platforms. Phishing is a method to trick individuals so that
they provide their personal information or ends up clicking
on malicious links that resulted in fake websites.
Spear phishing is a type of cyber-attack that aims
individuals or organizations with personalized and highly
targeted emails or messages.
Manuscript received on 30 June 2023 | Revised Manuscript
received on 08 July 2023 | Manuscript Accepted on 15 July 2023
| Manuscript published on 30 July 2023.
*Correspondence Author(s)
Anjali Shrikant Shukla, Department of Information Technology,
University of Mumbai, Mumbai (Maharashtra), India. E-mail:
anjalis2414@gmail.com
Sameer Rajendra Chavan, Department of Information Technology,
University of Mumbai, Mumbai (Maharashtra), India. E-mail:
sameerrchavan16@gmail.com
Srivaramangai R*, Department of Information Technology, University
of Mumbai, Mumbai (Maharashtra), India. E-mail: rsrimangai@gmail.com,
ORCID ID: 0000-0003-2723-6067
© The Authors. Published by Blue Eyes Intelligence Engineering and
Sciences Publication (BEIESP). This is an open access article under the
CC-BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0/
Unlike regular phishing attacks that are typically sent to
extensive recipients in a generic manner, spear phishing
attacks are carefully crafted to trick specific individuals or
groups by exploiting their personal information, interests, or
relationships.
The term spear phishing is derived from the concept of using
a spear to target a specific victim. Attackers frequently
exhibit extensive research on their targets to gather
information from various sources such as social media
profiles, public databases, or company websites. This
information enables them to produce effective and
customized messages that seem genuine and trustworthy.
Spear phishing attacks can take different forms, including
emails, instant messages, or even phone calls.
The messages may appear to be from a trusted source, such
as a colleague, a superior, a bank, or a reputable company,
making it complicated for the recipient to identify them as
malicious. The ultimate purpose of spear phishing attacks is
to deceive the individuals targeted into performing particular
activities, such as clicking on a malicious link, downloading
a malware-infected attachment, or opening up sensitive
information like login credentials or financial details. By
gaining access to such information, attackers may penetrate
systems, steal data, commit identity theft, launch further
attacks, or compromise the security of an entire organization.
To protect from spear phishing attacks, individuals and
organizations should be cautious and follow the steps given
by cybersecurity experts. This includes being aware of
opening emails or messages from unknown sources, verifying
the authenticity of requests for sensitive information,
regularly updating and patching software and systems, using
strong and unique passwords, and implementing multi-factor
authentication. Additionally, cybersecurity awareness
training can help educate individuals about the risks of spear
phishing on an individual & organization by teaching them
how to recognize and respond to suspicious messages. It’s
important to define that while technology can help mitigate
spear phishing attacks, human awareness and diligence play
a critical role in preventing successful attacks.
Email Phishing has become the primary method for gaining
data, unauthorized access & distributing malware. The figure
1 provided below illustrates a rise in the usage of different
archive file formats, as malicious individuals try to hide
harmful payloads, etc.

Spear Watch: A Thorough Examination to Identify Spear Phishing Attacks
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Published By:
Blue Eyes Intelligence Engineering
and Sciences Publication (BEIESP)
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Retrieval Number: 100.1/ijitee.H96800712823
DOI: 10.35940/ijitee.H9680.0712823
Journal Website: www.ijitee.org
Figure 1: Graph showing Trend of Email Attack
II. RELATED WORK
One of the most dangerous fraudulent activities that affect
everyday financial transactions is phishing, which involves
using social engineering tactics to deceive people and obtain
sensitive data such as credit card details, usernames, and
passwords. The various ways in which phishing affects online
banking and the implementation of effective safety measures.
S. Kumudha et.al [1], found that scams in the e-banking
sector fall under the category of cyber-deception. Cyber-
deception encompasses malicious behaviours like theft,
intellectual property infringement, and credit card fraud. The
study provides an overview of e-banking and delves into
different cybercrimes specifically identified in the banking
sector. The financial system is the backbone of the economy,
and nowadays, it heavily relies on information technology.
The financial system serves as the backbone of the economy,
and its reliance on information technology highlights the need
to prevent cybercrime through robust authentication,
identification, and verification techniques in electronic
banking transactions. Though completely eliminating
cybercrime from the internet may seem impossible, it is
feasible to closely monitor banking transactions and activities
on a regular basis. It is essential for individuals to remain
highly vigilant when conducting online banking transactions
involving money transfers. Dhruv Rathee et.al [2], present an
overview and analysis of several perspectives on the
identification of legitimate phishing emails. We found the
objective of this research is to explore machine learning (ML)
and deep learning (DL) methodologies for effectively
identifying phishing emails. Criminals often put significant
effort into making their emails appear authentic by using
believable wording, graphical interfaces, and logos.
However, phishing emails can be distinguished from genuine
ones as they are specifically crafted to achieve their malicious
goals. The literature describes various types and variations of
phishing emails. Machine learning-based approaches prove
to be more effective in recognizing phishing attacks, as they
offer lower false-positive rates and higher precision
compared to other strategies. The findings suggest that further
advancements are needed to leverage modernized DL
techniques in studies on detecting phishing emails, such as
Convolutional Neural Networks (CNNs), Recurrent Neural
Networks (RNNs), and Deep Reinforcement Learning
models. Among the various risks that are associated with
online banking, phishing attacks pose significant harm to both
banks and users who neglect security precautions. Phishing
hackers employ sophisticated methods, ranging from
deceptive tactics to DNS attacks, necessitating regular
updates to security measures by banks. Numerous research
studies have identified security issues like "phishing attacks"
as tools employed by hackers to compromise e-banking
customers' accounts Alhuseen O. Alsayed et.al [3].
Defending against phishing attacks involves strategies such
as personalized emails and websites, utilization of security
software, implementing two-factor authentication, and
enhancing customer awareness. The significant impact of
phishing compared to other similar methods, emphasizes the
potential severe losses it can cause to clients and institutions.
N.P. Singh [4] investigates global trends in phishing
activities, particularly in the financial sector. The author also
examines the reasons behind the increase in phishing attacks,
various types of phishing methods, and the process of
phishing. Online banking frauds include hoax emails, job
scams, computer viruses, spyware, identity theft, phishing,
vishing & smishing. Phishing techniques are categorized into
four main methods they are Dragnet Method, Lobsterpot
Method, Rod-and-Reel method and Gillnet phishing. Kara
Ilker [5], Focuses on phishing attacks, which aims to swiftly
and conveniently extract necessary information from victims
through deception, fear, curiosity, or excitement. This study
focuses on detecting and analyzing phishing attempts in the
context of e-banking, and proposes a methodology for doing
so. The aim of the author is to combat such crimes targeting
e-banking through these detection efforts. The analysis
findings in the paper indicated that the attacker's information
was accessible. Additionally, the analysis of the selected real
sample for the study unveiled the obtainability of the phishing
website's content, the attack strategy, and information about
the attacker. The approach followed in this paper
demonstrates a viable alternative technique that can be
applied to e-banking research and the detection of phishing
attacks. Deep learning methods, specifically Convolutional
Neural Networks (CNN), can contribute to the detection and
analysis of large-scale phishing attacks in the field. Providing
a clear understanding of phishing as a form of cybercrime that
aims to deceive individuals into revealing personal and/or
financial information or transferring money directly to the
attacker. The analysis of the attack vector considers both
social engineering and technical aspects. A typical phishing
attack involves three main elements: the lure, the hook, and
the catch. To address the issue of phishing, a heuristic
approach is recommended, which involves user education,
technological advancements, and process engineering.
Method of detection is classified in to two categories: human
detection, machine detection Junaid Ahsenali Chaudhry et.al
[6]. Phishing has emerged as a significant concern in network
security, leading to billions of dollars in financial losses for
both consumers and e-commerce companies. As a result, trust
in e-commerce has diminished among regular consumers. To
respond to this issue Mr. N. Revathy et.al [7] have proposed
an anti-phishing algorithm called Link-Guard which was
developed on identified characteristics.

International Journal of Innovative Technology and Exploring Engineering (IJITEE)
ISSN: 2278-3075 (Online), Volume-12 Issue-8, July 2023
48
Published By:
Blue Eyes Intelligence Engineering
and Sciences Publication (BEIESP)
© Copyright: All rights reserved.
Retrieval Number: 100.1/ijitee.H96800712823
DOI: 10.35940/ijitee.H9680.0712823
Journal Website: www.ijitee.org
The primary objective of the Link-Guard algorithm is to
identify phishing emails sent by attackers in order to
safeguard end user information. The algorithm was created
after carefully analyzing the attributes of phishing hyperlinks
as per author says. One of the key advantages of Link-Guard
is its characteristic-based approach, which allows it to detect
not only known phishing attacks but also unknown ones.
Additionally, Link-Guard offers protection against malicious
or unsolicited links found in web pages and instant messages,
making it a versatile solution. Although the authors have
implemented this approach by considering URL and domain
identity criteria, there is scope for further refinement and the
inclusion of additional criteria in future work. Radha [8]
focuses on raising awareness about phishing issues and
explores the utilization of various anti-phishing tools such as
ANTI-PHISHING Devices, Security Instruments - Netcraft,
ESET SECURITY, and others. Phishers employ tactics like
sending seemingly legitimate emails from government
agencies and financial institutions in order to obtain personal
information or unknowingly install malware on users'
computers. Presently, there are several types of phishing
attacks, including deceptive phishing, crime ware-based
phishing, and DNS-based phishing (content injection
phishing). To address these issues, an anti-phishing browser
plug-in is discussed. This plug-in monitors sensitive
information and generates a warning when a user attempts to
enter such data on a website that has previously been
associated with another reputable website. This proves
effective in cases where users unintentionally enter their
banking login details on a phishing site. However, it should
be noted that the anti-phishing tool may also flag legitimate
reuse of credentials as suspicious, presenting a potential
drawback. Bashir et.al [9] in their work have addressed the
following question: “how can an Antiphishing solution be
developed that can automatically detect phishing websites
based on their visual appearance, patterns, and common
characteristics, without relying on frequent updates or
maintaining a database of previous phishing sites?”. Relying
solely on data mining classification algorithms for this
purpose has been found to have a high error rate. Fadare et.al
[10] have found a battle against phishing attacks, which will
possibly increase the trust between customers and banks
relation and even helps to gain new customers. Banks have
realized the key role of KM in advancing an edge in the
competitive field of managing risks, eliminating fraud and
making sure of compliance. The purpose of KM is to
accomplish knowledge more skillfully and proficiently. The
integration of KM into internet banking actions facilitates in
the provision of more accurate understanding of KM as an
enabler of information strategy specifically for the internet
banking platform. Hence, KM can be used as a way to help
internet banking users defend themselves against attacks. An
exploratory assessment of Phishing, Smishing and Vishing
attacks against mobile devices is done by Ezer Osei Yeboah-
Boateng et.al [11]. The implications of end-user behavior
towards mitigating the risks posed by using mobile devices
for online services and facilities. The purpose of this research
was to identify the many dangers that affect mobile devices,
as well as how end users react to and perceive such threats.
Users were also discovered to be unaware of the frequent
phishing attempts made against their mobile devices or to be
unaware of them. Finally, the taxonomy of ‘alluring” and
“decoying” words used in phishing attacks could be a
benchmark to end-users to guard against becoming cyber-
victims. It comprises investigating various types of mobile
device attacks. The samples were purposively selected
amongst friends, family, office colleagues, and some students
on a university campus. The operating systems for the
selected sample mobile devices were restricted to the most
common ones, which are Microsoft Windows, Android and
iOS. The current issue of preventing cyberattacks in the
banking industry, specifically within the realm of e-banking.
Fadare et.al [12] propose a scientific demonstration
illustrating a method to combat e-banking fraud. The
proposed model is based on the classic Lotka-Volterra model
with the Holling-Tanner dynamic models. Through
simulation experiments using the constructed model, it was
observed that the occurrence of a saddle case and a line of
stable fixed points is highly unlikely in real-life scenarios.
This is due to the implication that after each successful fraud
attempt, at least one new attack must emerge, but in practice,
it is more common for multiple attacks to occur. The most
probable scenarios are a stable node and a stable degenerate
node. Brad Wardman et.al [13] explains that phishers
continuously modify the source code of their phishing web
pages to mimic changes in legitimate websites and avoid
being detected by anti-phishing measures. This study utilizes
file-matching algorithms to determine if a new file or set of
files can be classified as a phishing web page. The focus of
this research is on achieving efficient runtime performance.
Various file matching and string alignment techniques were
tested, including Main Index File MD5 matching, Deep MD5
Matching, phishDiff, context-triggered piecewise hashing
using ssdeep, and a novel algorithm called Syntactical
Fingerprinting. We studied that PhishDiff and ssdeep-based
methodologies require additional information to find
comparable candidate files, as running them without this
information would be time-consuming and impractical. The
research experiments in the paper showcased the
effectiveness of several string-matching algorithms in
quickly and accurately identifying phishing websites based
on their content. According to the author, techniques
mentioned in the paper was tried in various set of phishing
website and the outcome of detection was 90% maintaining
manageable false positive rates. Rachna Dhamija et.al [14]
explore the topic of authenticating websites in the context of
phishing attacks. Phishing presents a significant challenge in
terms of usability and security, as both system designers and
attackers leverage user interfaces to influence users. To
address this issue, a novel approach called Dynamic Security
Skins is proposed. This approach allows a remote web server
to demonstrate its authenticity in a manner that is easily
verifiable by users and difficult for attackers to imitate. The
Mozilla platform was selected for its openness and flexibility,
and the standard Mozilla browser interface, along with our
extension, was developed using Mozilla's XML-based User
Interface Language (XUL), which is a markup language for
defining user interface components.

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and Sciences Publication (BEIESP)
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DOI: 10.35940/ijitee.H9680.0712823
Journal Website: www.ijitee.org
In this section, authors provide an overview of their solution
and subsequently delve into detailed explanations of each
component. Engin Kirda et.al [15] introduce a new browser
extension called AntiPhish, which aims to safeguard users
from phishing attacks that occur on spoofed websites. The
development of AntiPhish was influenced by the existence of
automated form-filling applications. Popular browsers like
Mozilla and Internet Explorer offer built-in features that
allow users to store and automatically fill form contents if
desired, requiring a master password for access. The
prototype of AntiPhish was implemented as a Mozilla
browser extension or plug-in, utilizing the Mozilla XML
User-Interface Language (XUL) and Javascript. The
AntiPhish implementation for Mozilla is lightweight,
consisting of approximately 900 lines of Javascript code and
200 lines of XUL user interface code. While the best
approach to prevent phishing is to educate users about not
clicking on random links and entering sensitive information
such as passwords, it is unrealistic to expect that all users will
fully grasp the phishing threat and navigate the web
accordingly. There will always be users who fall victim to
visiting phishing websites. A new method to address the issue
of uncertainty in evaluating e-banking phishing websites and
puts forward an intelligent, robust, and efficient model for
detecting such websites. The model utilizes fuzzy logic in
conjunction with data mining algorithms to analyze the
characteristics of e-banking phishing websites and classify
different types of phishing attacks Maher Aburrous et.al [16].
It also establishes six attack criteria for e-banking phishing
websites through a layered structure. An approach for
identifying phishing URLs using the Gated Recurrent Unit
(GRU), a fast and accurate method for classifying phishing
attempts by Mousa Tayseer Jafar et.al [17]. Phishing websites
have become a growing concern in the online world. Phishing
involves fraudulent attempts to deceive individuals by
impersonating legitimate institutions and tricking them into
revealing sensitive information like passwords and bank
account numbers. The proposed approach involves analyzing
website URLs by extracting features using a lexical method.
The GRU classifier is then trained on a dataset containing
both malicious and benign URLs. The experiments conducted
in this research utilize the powerful GRU model to detect
suspicious websites based on features extracted from the
URLs. The focus paper is on leveraging the gate mechanism
to enhance the speed of the model in identifying phishing
URLs. E. Konda Reddy et.al [18] said that phishing is a
modern type of scheme in which attackers create a replica of
an existing webpage to deceive users into providing personal,
financial, or password information, thinking they are
interacting with their trusted service provider's website. Link
Guard algorithm, which is employed to identify phishing
emails sent by phishers and protect end users' information.
The system implements the Link Guard algorithm as shown
in figure 2, a host-based algorithm that effectively detects and
prevents both known and unknown phishing attacks. Being
characteristic-based, Link Guard can identify and prevent not
only known phishing attacks but also unknown ones. The
project utilizes Java technologies and Oracle for its
implementation.
Figure 2: Link guard algorithm Architecture
Forensic case analysis of the e-banking website prepared for
phishing attacks was made by author. On a real attack
example, the attacker's tactics and attack strategy were
examined. Since the phishing attack can use different designs
according to the fiction chosen, the detection and analysis
approach may differ depending on the case, although it is
similar to the other attack examples. By clicking on malicious
links within email attachments or on fake websites, victims
can be targeted, and their computers can be compromised by
attackers who execute infected files from emails or malicious
links on web pages. The attack strategy and the methods used
by the attacker were examined on a real attack example by
Ilker Kara [19]. To enhance future research, the author
suggests planning investigations with diverse sample datasets
for the detection and analysis of e-banking websites
susceptible to phishing attacks. Sayan Karmakar et.al [20]
insights into the significant threat of identity theft, which is
prevalent in the online realm. Identity theft occurs when an
attacker assumes someone's identity to unlawfully acquire
their personal information, such as social security numbers,
bank details, or credit card numbers, for malicious purposes,
including financial theft and various other crimes. Tony
UcedaVelez [21] focuses on tackling one of the major
challenges currently faced by the financial industry: Phishing.
The author emphasizes the need for security professionals
and banks to keep up with new developments. In conclusion,
the author suggests that the user interface of email services
should be carefully designed to provide effective alerts when
users encounter suspicious emails.
III. RESULTS AND DISCUSSION
The literature survey helped us to understand certain
important factors such as Phishers exploit the sense of
urgency by utilizing terms like "important" to trigger an
emotional response from users and entice them to click on
"View message." One of the primary challenges of phishing
is that attackers continuously seek innovative and emerging
methods to deceive users into believing they are interacting
with legitimate emails or websites. Phishers have become
increasingly adept at creating websites that closely resemble
targeted locations, incorporating graphics and logos in
phishing emails to enhance authenticity.

International Journal of Innovative Technology and Exploring Engineering (IJITEE)
ISSN: 2278-3075 (Online), Volume-12 Issue-8, July 2023
50
Published By:
Blue Eyes Intelligence Engineering
and Sciences Publication (BEIESP)
© Copyright: All rights reserved.
Retrieval Number: 100.1/ijitee.H96800712823
DOI: 10.35940/ijitee.H9680.0712823
Journal Website: www.ijitee.org
Phishing is commonly associated with deceptive emails that
imitate credit card companies, banks, or popular e-commerce
platforms like eBay and Amazon, aiming to deceive victims
into disclosing sensitive information. The overall process of
phishing mechanism as per the existing literature analysis
involves:
1. Planning – Phishers select businesses to target and
devise strategies to gather email addresses of their
customers.
2. After selecting the spoofed business and victims,
phishers distribute messages and employ various
methods to collect data, often utilizing web pages and
email addresses.
3. Attack – Phishers send spam messages that appear to
originate from legitimate sources.
4. Collection – Phishers gather the information provided
by victims in pop-up windows or web pages.
5. Once phishers gather the necessary information, they
employ it for illegal purchases or other fraudulent
activities.
The analysis further helps to focus on financial sector as
rather than viewing banking security measures as a one-time
implementation, that should be seen as an ongoing process of
development and adaptation. As phishing attacks become
more sophisticated, it is essential to continuously reassess
security measures to ensure they can effectively counter these
new threats. Some effective defense mechanisms against
phishing attacks include:
1. Anti-virus scanning serves the purpose of identifying
harmful attachments, embedded HTML, or concealed
binary code within a bank's network.
2. Anti-Spam Filtering: Uses rule-based inspection of
emails to prevent successful delivery of spam.
3. Content Filtering: Inspects the content of
communication channels such as instant messaging
(IM), HTTP, FTP, etc.
4. Proxy Services: Assist in managing different forms of
internet communication within a banking network.
By combining technical security measures with effective
communication to consumers, the risk associated with social
engineering attacks can be significantly minimized.
IV. CONCLUSION
Complete eradication of phishing is unlikely. Phishing refers
to the deceptive practice of posing as a trustworthy source in
electronic communication to obtain sensitive information like
usernames, passwords, and credit card details, often with
malicious intent. Nowadays, this issue has grown
significantly in seriousness, prompting the exploration of
various techniques to address it. Through the study of
multiple papers, awareness has been raised regarding the
problems associated with phishing and the utilization of
different algorithms, tools, and other solutions to combat it.
Firstly, education plays a crucial role in preventing successful
spear phishing attacks by creating awareness. Secondly,
implementing robust email security measures is essential.
Advanced email filtering systems can detect and block
malicious emails, thus reducing the likelihood of spear
phishing attacks reaching the intended targets. Additionally,
email authentication protocols such as DMARC (Domain-
based Message Authentication, Reporting, and
Conformance) can help verify the authenticity of incoming
emails, making it harder for attackers to impersonate trusted
entities. Furthermore, multi-factor authentication (MFA)
should be widely adopted to add an extra layer of security. By
requesting users to provide multiple forms of verification,
such as a password, biometric data, or a one-time code, the
risk of unauthorized access through spear phishing can be
significantly reduced. By implementing these solutions,
individuals and organizations can better protect themselves
from falling victim to this highly targeted form of cyber-
attack.
DECLARATION
Funding/ Grants/
Financial Support
No, we did not receive.
Conflicts of Interest/
Competing Interests
No conflicts of interest to the
best of our knowledge.
Ethical Approval and
Consent to Participate
No, the article does not require
ethical approval and consent
to participate with evidence.
Availability of Data and
Material/ Data Access
Statement
Not relevant.
Authors Contributions
All authors have equal
participation in this article.
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and Sciences Publication (BEIESP)
© Copyright: All rights reserved.
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DOI: 10.35940/ijitee.H9680.0712823
Journal Website: www.ijitee.org
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AUTHORS PROFILE
Anjali Shukla, Student, M.Sc in Information
Technology, Department of IT, University of Mumbai,
India. Anjali specializes in cyber security and is also
doing internship in Maharashtra Cyber Cell, Mumbai.
She is also pursuing her training to appear for defence
examinations.
Sameer Chavan Student, M.Sc in Information
Technology, Department of IT, University of Mumbai,
India. Sameer specializes in cyber security and cloud
computing and has job experience as a developer. He
has hands one experience in using cyber security tools
and is preparing for EC council certifications. He has
deployed a small security mechanism as a prototype
for the department.
Srivaramangai R, Head, Department of IT,
University of Mumbai, India. Having 21 years of
experience in teaching and 6 years in industry. The
specialization areas are artificial intelligence, security,
image processing. Has industry experience in web
development and report code generators. Has
published more than 30 International journal papers,
20 conference papers, resource persons for various
workshops and chaired sessions.
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