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International Journal on Recent and Innovation Trends in Computing and Communication
ISSN: 2321-8169 Volume: 11 Issue: 10
Article Received: 22 August 2023 Revised: 05 October 2023 Accepted: 25 October 2023
___________________________________________________________________________________________________________________
1670
IJRITCC | October 2023, Available @ http://www.ijritcc.org
Enhancing Network Security Through Blockchain
Technology: Challenges And Opportunities
Salwa Shakir Mahmood, Mustafa Ali Hasan, and Ayad Hasan Adhab
Ministry of Education, 10065 Al Tarbawi Collection, Baghdad, 10001, Iraq. Directorate of Education Iraq, Horror KUT, IRAQ
salwa1982m@gmail.com, m1979ah@gmail.com, ayadwasit1978@gmail.com
Abstract: The rapid proliferation of digital technologies has ushered in an era where network security is of paramount importance. Traditional
security mechanisms have proven insufficient in protecting sensitive data and critical infrastructure from an ever-evolving landscape of cyber
threats. Blockchain technology, originally designed to underpin cryptocurrencies like Bitcoin, has emerged as a promising solution for enhancing
network security. Blockchain's core principles of decentralization, immutability, and transparency offer a unique approach to addressing
vulnerabilities and mitigating risks in the digital realm. This paper examines how blockchain can enhance data integrity, authentication, and
authorization processes, thereby fortifying the security posture of networks and systems.
The paper discusses real-world applications and case studies where blockchain has been successfully implemented to bolster network security,
such as supply chain management, identity verification, and secure communication protocols. These examples highlight the tangible benefits and
opportunities that blockchain presents for organizations seeking to safeguard their digital assets and operations. In conclusion, this abstract
underscore the pivotal role that blockchain technology can play in enhancing network security. By addressing challenges head-on and capitalizing
on the opportunities it offers, organizations can build resilient, transparent, and secure digital ecosystems that protect against an ever-increasing
array of cyber threats. The exploration of blockchain's potential in this context is critical for shaping the future of network security in our
interconnected world.
Keywords: Network Security, Blockchain Technology, Challenges, Opportunities, Cybersecurity
1. INTRODUCTION
The IoT is a paradigm that links devices with the help of the
Internet network.[1] IoT is used for various intents, such as
self-driving cars, healthcare, smart home, banking, wearable
sensors, E-business, and surveillance systems. [2] All these
devices transmit data from anywhere and anytime. During
DT, the collected data faces several kinds of security
challenges because the IoT is a small resource-constrained
device that cannot be able to install a system or software to
be highly secure. The memory usage limitation and the usage
of centralized servers in IoT data collection suffer from
various behaviour of intrusions. Due to the decentralized
behaviour of Blockchain, it acts as a potential candidate to
protect the secrecy and privacy of the IoT in a Peer-to-Peer
(P2P) manner.[3]
Decentralization, P2P networking architecture, secrecy,
tamper- evidence, and auditability are some of the features of
Blockchain that can be useful for data sharing, transactions,
and supply-chain management. [4] Because data saved on the
Blockchain is highly trustworthy and easily accessible
through duplication, it has piqued the interest of entire
business corporations. [5] Blockchain outperforms
counterpart approaches based on centralized digital ledgers
by acting as a decentralized ledger that verifies and stores
transaction records. [6]
The data documents in the Blockchain are stored as blocks,
and the logical relationship between them is constructed as
chains. If anyone performs modifications, that has been
reported to the entire network using the consensus approach
of Blockchain. The Blockchain does not require any
intermediary entity to transmit data, leading to decentralized
management. [7] This research creates a cloud data storage
system based on Blockchain that employs an efficient
authentication and encryption model.
2. LITERATURE REVIEW
Swan (2015) In his book titled "Blockchain: Blueprint for a
New Economy," the author presents a comprehensive and in-
depth analysis of the blockchain technology. This book
delves into the core concepts and underlying mechanics of
blockchain technology, with a specific emphasis on the
technology's potential to shake up traditional economic
institutions. The work done by Swan is an important and
necessary resource for gaining an understanding of the
conceptual foundations that drive the blockchain
technology.[8]
Crosby et al. (2016) The purpose of the book named
"Blockchain Technology: Beyond Bitcoin" is to provide a
foundational understanding of blockchain technology. The
research dives into the more technical elements of blockchain
technology and highlights its potential to be used in situations
International Journal on Recent and Innovation Trends in Computing and Communication
ISSN: 2321-8169 Volume: 11 Issue: 10
Article Received: 22 August 2023 Revised: 05 October 2023 Accepted: 25 October 2023
___________________________________________________________________________________________________________________
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IJRITCC | October 2023, Available @ http://www.ijritcc.org
other than those traditionally associated with
cryptocurrencies. This article lays the groundwork for
comprehending the larger repercussions of blockchain
technology beyond its first use by providing a platform for
doing so.[9]
Iansiti and Lakhani (2017) The book "The Truth About
Blockchain" gives readers an understanding of the significant
and game-changing potential that blockchain technology has.
The authors conduct an exhaustive study of a wide variety of
applications across a variety of industries, with a special
focus on the revolutionary influence that this technology has
had on business processes and ecosystems. This article,
which was published in the Harvard Business Review,
provides useful information on the implications that
blockchain technology might have in the real world.[10]
Mengelkamp et al. (2018) The purpose of this research is to
evaluate the potential applications of blockchain technology
within the framework of a "Blockchain-Based Smart Grid."
The evaluation of sustainable local energy markets is the
major focus of their research. A special emphasis is placed on
the use of blockchain technology to improve the effectiveness
of energy trading and consumption. This study, which
focuses on practical applications, highlights the potential of
blockchain technology in efficiently solving environmental
challenges in real-world settings. The research was carried
out by the University of Washington.[11]
Sharma et al. (2017) The author introduces "Block-VN," an
architectural framework that makes use of decentralized
blockchain technology and is designed for vehicle networks
in smart cities. The findings of the study carried out by the
authors highlight the relevance of blockchain technology in
enhancing the connection and efficacy of the Internet of
Things (IoT) and the infrastructure of smart cities. This
research reveals that blockchain technology has the potential
to improve both the safety and the performance of networks
that are connected to the Internet of Things (IoT).[12]
Zheng et al. (2018) In the paper you're working on with the
working title "Blockchain Challenges and Opportunities,"
please provide a comprehensive analysis of the themes
outlined above. The study that was carried out by the writers
incorporates the ideas of scalability, privacy, and consensus
procedures, and as a result, it provides a holistic viewpoint on
the present condition of the blockchain ecosystem. The
technology known as blockchain faces a number of
challenges and concerns over its safety.[13]
Trautman and Ormerod (2016) focuses on the obligations
and legal ramifications that corporate directors and officers
have to fulfil in order to protect the cybersecurity of their
organisations. The paper discusses the standards of care
required from business executives using the Yahoo data leak
as a case study. It looks at how the breach prompted legal
investigation and emphasizes the need for improved
cybersecurity governance.[14]
Yeoh (2017) explores the problems with regulation brought
on the blockchain technology. The study examines the
distinctive features of blockchain and how they provide
regulatory difficulties for bureaucracies and financial
institutions. It addresses concerns about privacy, security, and
the acceptance of blockchain transactions in law.[15]
3. PROPOSED METHODOLOGIES
This study proposes a novel mechanism to perform
authentication and encryption in IoT using software-defined
networks (SDN) and Blockchain. Initially, the IoT user is
registered to the trusted authority (TA) and receives the key
for data access using HSOA. The user is then authenticated
by a TA using a user id, password and an optimal key. After
successful authentication, the user encrypts their data and
uploads it to the cloud. An elliptic curve integrated encryption
scheme (ECIES) is used for encryption. The proposed
approach performs encryption on the IoT data using ECIES.
In the case of confidential data, the data is encrypted double
times. Otherwise, it is encrypted only once. The user's
encrypted data is stored in the cloud via the switches of SDN.
The SDN uses a Blockchain mechanism to keep the user's
encrypted data. In a Blockchain, a block is created for each
data the user uploads.
Each block on the Blockchain includes an index of
transactions, the hashing value (SHA-256) of user data, the
hashing value of the previous block, and a time stamp. If any
alterations to these data blocks of Blockchain have been
made, they are tracked via the smart contract (SC). In the end,
the user can get the evidence of data modification performed
on their uploaded file with the help of an investigator as a
logical graph of evidence (LGoE). The architecture of the
proposed research framework is given in Figure1.
Figure1: The architecture of the proposed research
framework
International Journal on Recent and Innovation Trends in Computing and Communication
ISSN: 2321-8169 Volume: 11 Issue: 10
Article Received: 22 August 2023 Revised: 05 October 2023 Accepted: 25 October 2023
___________________________________________________________________________________________________________________
1672
IJRITCC | October 2023, Available @ http://www.ijritcc.org
3.1. User Registration and Authentication
The first stage of the proposed model is the registration phase.
In this phase, the IoT users are registered with the legal or TA
in the cloud by providing their details such as name, age, date
of birth, and mobile number. Once the users are registered
with the TA, the TA generates a unique username, password
and an optimal key using HSOA for authentication purposes
and gives it to the user. The TA also stores these
authentication credentials (ACs) in its cloud database to
verify the user. During login, the users are asked to provide
the username, password, and a random key, and the trusted
authority checks the user-entered information with the
information stored already in the cloud. If both of these
credentials are matched, the TA allows the user as an
authenticated one. Otherwise, it declined the user's
permission for data access in the cloud. The key generation
process using HSOA is described in the below section.
3.1.1. Key generation using HSOA
The TA verifies the IoT users using a username, password,
and an optimal key. The proposed system's optimal key for
authentication purposes is generated using the HSOA. HSOA
is a heuristic-based optimization model motivated by the
music improvisation process and can solve various
optimization problems. The HSOA consists of five phases:
initialization of algorithms parameters, initialization of
harmony memory (HM), development of New Harmony
using HM information, updating of HM, and continuation of
steps 3 and 4 until the stopping criteria are met. The
pseudocode of the HSOA for optimal key generation is given.
3.2. Data Encryption and Storage
Once after successful authentication, the authenticated user
can upload or download their data in the cloud. To provide
security to the user data, here the ECIES is used by the
proposed system. The proposed method classifies the user’s
data into sensitive and non-sensitive. Based on this sensitivity
level, the ECIES encrypts the data. If the data is sensitive, it
is encrypted double times using the ECIES. Otherwise, it is
encrypted only once using the proposed ECIES model.
ECIES is a public key cryptographic approach based on
elliptic curve theory. The ECIES have a smaller key length to
do encryption and offer higher security than other
cryptographic algorithms. Elliptic curves used in the ECIES
are the group of points which satisfy a particular
mathematical equation. They are symmetrical. The encrypted
data provided by the ECIES is stored in the cloud with the
help of SDN switches. The algorithmic steps of ECIES to
perform encryption on the user data are given.
3.3. Blockchain for Evidence Collection
After successful encrypted data storage in the cloud, the
proposed system uses an SDN controller to provide security
to the cloud-stored data. The SDN controller uses the
Blockchain mechanism to secure the user-encrypted data in
the cloud. The Blockchain mechanism creates a list of blocks
for the cloud-stored data. Each block in the Blockchain
mechanism consists of the index of transactions, the hashing
value of the data, the hashing value of the preceding block
International Journal on Recent and Innovation Trends in Computing and Communication
ISSN: 2321-8169 Volume: 11 Issue: 10
Article Received: 22 August 2023 Revised: 05 October 2023 Accepted: 25 October 2023
___________________________________________________________________________________________________________________
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IJRITCC | October 2023, Available @ http://www.ijritcc.org
and the timestamp. In the Blockchain mechanism, the hash
value for each input data is generated utilizing the SHA-256
technique. The purpose of using the Blockchain mechanism
in the proposed system is to monitor the activities performed
on the cloud-stored data to provide security to the user data.
The Blockchain mechanism uses smart contracts to track the
data access that is performed on the user data in the cloud.
Smart contracts (SCs) are equivalent to real-world contracts.
SCs are fully digital, with everything being wholly
distributed.
In actuality, a SC is a computer programme, which is stored
within a Blockchain. The SCs in the Blockchain are
distributed as well as immutable. Immutability indicates that
once a contract is generated, nothing in the block can be
changed again. It eliminates legal uncertainties in data access
with transactions concluding a contract is processed on the
Blockchain. So, any access or modifications to the cloud-
stored data will be noted and reflected in the Blockchain
module. The reflected details in the Blockchain contains, who
accessed the original data, what type of modification has been
done on the data, where the data has been modified and other
such information. The detailed explanation of SDN,
Blockchain in SDN and the hashing operation performed in
Blockchain using SHA-256 is given in upcoming sections.
3.3.1. SDN controller
SDN is a networking zone that controls the network control
plane (which handles numerous devices) as well as the data
plane (forwarding plane). SDN contains various
technologies, incorporating functioning segregation,
automation, and virtualization of network via
programmability. By separating the control and data planes,
the control plane defines how the packets flow via the
network's nodes. On the other hand, the data plane transfers
packets from one location to another as controlled by the
control plane. The data packets that reach the network switch
in any networking background with SDN execution will
observe the rules assembled into the switch's proprietary
firmware. The centralized switch transmits these rules to the
switch. Figure 2 shows some of the particular characteristics
of SDN.
Figure 2: characteristics of SDN
The management and setting up of IoT devices are
profoundly impacted by SDN. When a data packet lacks a
defined route, switches in an SDN environment may submit
a request for a route to a controller. This is known as dynamic
routing, and it happens when switches, rather than the
controller, issue route requests to routers and routing
protocols. Open protocols such as OpenFlow make network
control possible in SDN architectures. Instead of using closed
and proprietary firmware to setup, operate, save, and optimize
network resources, businesses may instead access network
switches and routers at the network's edges using globally
aware software control.
3.3.2. SDN controller with Blockchain
SDN controllers provide many benefits, but they also present
certain security risks. It is simple for hackers to steal sensitive
information from a network if they can get access to the SDN
controller. Any information sent between the SDN switch and
controller is vulnerable to a man in the middle attack.
Therefore, in the proposed method, the Blockchain module
protects IoT and SDN controllers against a variety of network
assaults. Faster transactions, improved security, automated
account reconciliation, fewer instances of hacking, more
transparency in transactions, and varying degrees of data
accessibility are only some of the benefits of using the
Blockchain method in IoT data transfer. Taking these benefits
of the Blockchain technology into account, the suggested
concept encrypts the user's data using ECIES upon
authentication. The data is then sent to a Blockchain in the
cloud, where it is protected by SDN routers. The LGoE report
is generated by the investigator from the Blockchain using
SDN switches to verify any changes to the data. The
suggested paradigm provides a more secure environment for
user data in the IoT.
3.3.3. SHA-256 hashing
The Secure Hash method 2 (SHA-2) family includes many
widely used cryptographic hash functions, including the
SHA-256 method. It accepts data of any size and returns it
formatted as 256-bit bytes. In the encryption process, the
input data is changed into a secure format, which can only be
decoded if the receiver has the key. It's possible that the
encrypted data will be indefinitely larger than the original. In
contrast, data of any size may be hashed into a uniform one.
512-bit information is shrunk to a 256-bit string size in SHA-
256 hashing. A hash function produces a more secure hash
result, and modifying the original hash data is difficult. SHA-
256 hashing entails the following procedures:
• Step 1: Transform the data into binary (0’s and 1’s).
• Step 2: Separate the binary information into 512-bit
chunks. If the block size is less than 512, add
"padding" bits to make it 512 or larger.
International Journal on Recent and Innovation Trends in Computing and Communication
ISSN: 2321-8169 Volume: 11 Issue: 10
Article Received: 22 August 2023 Revised: 05 October 2023 Accepted: 25 October 2023
___________________________________________________________________________________________________________________
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IJRITCC | October 2023, Available @ http://www.ijritcc.org
If the block size is more than 512, it must be divided into 512-
bit chunks.
Add padding from the preceding data block if the final block
is shorter than 512 bits.
• Step 3: Separate the data into smaller chunks, each
of which should be 32 bits in size.
• Step 4: Compress the data using a 64-round process
in which the hash values are cycled according to a
certain pattern and new information is added each
time.
• Step 5: Produce fresh hash values for the supplied
data based on the result of step 4.
• Step 6: Create the latest iteration's SHA-256 hash
value (hash digest). Figure 3 depicts the operation of
SHA-256 hashing.
Figure 3: The working of SHA-256 hashing
3.4. Mining of Evidence Information
The cloud-based platform investigator is searching the
Blockchain for relevant data. The investigator needs the TA's
approval before he or she may mine the Blockchain for
evidentiary information. When an investigator is given
permission to access a system, they will utilised SDN
controllers to mine the Blockchain for data and then create
the LGoE to track down the history of modifications made to
the user's data. Therefore, the suggested system offers greater
security to the user data by doing all of the above in cloud
data storage and keeps track of all types of misbehavior that
occur in the cloud. Figure 4 is a flowchart of the suggested
approach of securing the data of IoT end-users.
Figure 4: Data Flow Diagram
3.5. Performance Evaluation
The effectiveness of the proposed model's encryption and
storage techniques for IoT data saved in the cloud is assessed
in this section. Using the suggested approach, a cloud-based
SDN may be built with support for 100 mobile nodes, open
flow switches, Blockchain controllers, TA, and probes. After
an IoT user has been verified, their submitted data is
encrypted using the ECIES algorithm before being saved to
the cloud. The cloud then use the Blockchain method to
safeguard the data it stores.
Each user's encrypted cloud data was given a unique hash
value by the Blockchain, which then stored the data in a series
of blocks. The smart contracts component is also used, which
detects and records any changes made to the archived
information. At last, the investigator, aided by TA and SDN,
performs the function of evidence mining. With TA's OK, it
queries the Blockchain for a history of all SDN switch
operations conducted on data stored in the cloud (LGoE).
Thus, the suggested system safeguards the cloud-stored data
of IoT users and, by using the Blockchain method, detects any
anomalous patterns in that data. the cryptographic hash of our
proposed cloud-based data storage system, as created by the
Blockchain. An investigator's LGoE report for vetting users'
encrypted data for wrongdoing.
International Journal on Recent and Innovation Trends in Computing and Communication
ISSN: 2321-8169 Volume: 11 Issue: 10
Article Received: 22 August 2023 Revised: 05 October 2023 Accepted: 25 October 2023
___________________________________________________________________________________________________________________
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IJRITCC | October 2023, Available @ http://www.ijritcc.org
3.5.1. Performance Evaluation of ECIES
Encryption time (ETI), decryption time (DTI), computational
time (CTI), and key generation time (KTI) are compared
between the proposed ECIES system and current encryption
models for evaluation. Advance Encryption Standard (AES),
Rivest-Shamir-Adleman (RSA), and Blowfish Algorithm
(BFA) are the current models used for comparison. Table 3.1
displays the ETI achieved by both the proposed and the
current models for 100Mb, 200Mb, 300Mb, 400Mb, and
500Mb user data files. The encryption time overhead (ETI) is
the amount of time needed by an algorithm to convert
plaintext into encrypted text. The proposed ECIES model
requires an ETI of 3212ms to encrypt a 100Mb file, whereas
the current AES, RSA, and BFA need 3543ms, 4562ms, and
6542ms, respectively.
Table 1: Assessment of Encryption Time
Encryption time (MS)
Techniques/File Sizes
(MB)
100
200
300
400
500
Proposed ECIES
3212
5213
6897
8871
10921
AES
3543
5423
7514
9162
11776
RSA
4562
6542
8762
10982
12453
BFA
6542
8712
10652
12286
14999
Table 2: Assessment of Decryption Time
Decryption time (MS)
Techniques/File Sizes
(MB)
100
200
300
400
500
Proposed ECIES
3219
5211
6911
8882
10916
AES
3548
5412
7533
9154
11782
RSA
4561
6545
8767
10978
12453
BFA
6546
8717
10651
12289
14994
Similarly, while comparing the ETI of the encryption
algorithms for various file sizes, the proposed ECIES
encrypts the user's data in the least amount of time. Table 2
displays the models' DTIs. The DTI measures how long it
takes an algorithm to decrypt certain data. Existing methods
require more time to decrypt user data, whereas the suggested
model achieves the DTI of 3219ms for 100Mb user data. Both
the ETI and DTI of the models grow in tandem with the
amount of the input files. While various methods can encrypt
and decode user data, the suggested model can do it in much
less time. Here, by using double encryption for private user
information, the suggested approach achieves a marginal
improvement in ETI and DTI over AES. In terms of
encryption and decryption, however, it achieves a lesser value
than alternatives. Figures 5 and 6 provide graphical
representations of the ETI and DTI, respectively.
Figure 5: ETI Assessment
Figure 6: DTI Assessment
International Journal on Recent and Innovation Trends in Computing and Communication
ISSN: 2321-8169 Volume: 11 Issue: 10
Article Received: 22 August 2023 Revised: 05 October 2023 Accepted: 25 October 2023
___________________________________________________________________________________________________________________
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IJRITCC | October 2023, Available @ http://www.ijritcc.org
Figure 7 then shows a comparison of the encryption models
using KTI. In this context, milliseconds (ms) refer to the KTI
of an encryption model, which is the time required to produce
keys for a cryptographic operation. Key generation for
encryption and decryption in the proposed model takes
2123ms, whereas in the current AES, RSA, and BFA models,
same operations take 2863ms, 3124ms, and 3876ms,
respectively.
Figure 7: KTI Assessment
Since the proposed model is lightweight and uses a smaller
key length for its cryptographic function, the KGT, ETI, and
DTI of the proposed encryption mechanism are all reduced in
comparison to existing algorithms for a key generation, as
shown by the results. The next step is the evaluation-based
CTI, seen in Figure 8. In this context, the CTI refers to the
amount of time required to complete the whole cryptographic
procedure. Changing the amount of user data (file sizes) from
100Mb to 500Mb is used to calculate the CTI. In comparison
to the current methods, such as AES, RSA, and BFA, the
suggested ECIES gets a CTI of 4321ms for the 100Mb data.
Similarly, the ECIES has a lower CTI than AES, RSA, and
BFA across the board for all file sizes tested. The analytical
findings show that the proposed ECIES provides superior
encryption outcomes for user data stored in the cloud.
Figure 8: Evaluation of CTI
3.5.2. Performance Evaluation of Blockchain
based Security Mechanism
In this part, we examine the differences between the results
obtained using the current PIN-based and password-based
security techniques and those obtained using the proposed
security model (authentication using HSO, ECIES, and
Blockchain). Data security level (SL) is used to evaluate the
methods side-by-side. By shifting the file sizes between 100
and 500Mb, we can see how the models' SL changes. Table 3
summarizes the findings. To determine SL, we divide the
number of unaltered bytes by the total number of bytes
transferred.
Table 3: Performance Analysis regarding Security Level
Data security level (%)
File Sizes
Proposed
Password based
PIN based
(Mb)/Techniques
model
authentication
authentication
100
93
70
72
200
91
73
74
300
92
71
73
400
94
72
75
500
93
71
72
Table 3 shows that our suggested model achieves a better SL
than the state-of-the-art models. Because the password and
PIN are so simple to crack, the present methods only provide
inferior protection for the user's data. The suggested
methodology generates keys using the HSO and encrypts user
data using the secure ECIES mechanism.
The SL of cloud-stored data has risen as a result of the
increased use of security measures. In addition, the research
use Blockchain technology to keep tabs on any suspicious
activity involving users' data stored in the cloud. With the aid
of an investigator, Blockchain's SCs generate LGoE detailing
every activity linked to data changes and accesses. Therefore,
the suggested model offers better protection than the current
methods. Figure 9 is a graphical representation of data found
in Table 3.
International Journal on Recent and Innovation Trends in Computing and Communication
ISSN: 2321-8169 Volume: 11 Issue: 10
Article Received: 22 August 2023 Revised: 05 October 2023 Accepted: 25 October 2023
___________________________________________________________________________________________________________________
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IJRITCC | October 2023, Available @ http://www.ijritcc.org
Figure 9: Evaluation of Security
3.6. Summary
Using HSOA-based optimum authentication and ECIES data
encryption, this research creates a Blockchain-based data
storage solution for IoT cloud users. In order to get access to
the cloud storage system, the users must first authenticate
with the TA. Cloud IoT user data is encrypted using ECIES
after authentication, with the amount of encryption
determined by the data's sensitivity. In order to prevent
hackers from gaining access to users' data kept in the cloud,
the Blockchain is then used to implement the encrypted data
saved in the cloud. Using SDN, the detective is able to
monitor all of the data modifications made to the Blockchain.
Experiments are conducted to evaluate the success of the
proposed secure data storage paradigm on a variety of
performance metrics. When comparing ETI, DTI, CTI, and
KTI, the suggested ECIES performs optimally. When
compared to traditional authentication methods like
passwords and PINs, the suggested Blockchain-based data
storage technique offers a far greater degree of protection for
cloud users' sensitive information. Since the provided
solution offers improved data security for cloud IoT users, it
follows that the study's findings support its adoption.
REFERENCES
1. Cachin, C. (2016). Architecture of the Hyperledger blockchain
fabric. In Workshop on distributed cryptocurrencies and
consensus ledgers 2016 (pp. 1-4).
2. Crosby, M., et al. (2016). Blockchain technology: Beyond
bitcoin. Applied Innovation, 2(6-10), 71.
3. Gao, Y., & Nobuhara, H. (2017). A proof of stake sharding
protocol for scalable blockchains. Proceedings of the Asia-
Pacific Advanced Network, 44, 13-16.
4. Iansiti, M., & Lakhani, K. R. (2017). The truth about
blockchain. Harvard Business Review, 95(1), 118-127.
5. Kayes, A., Rahayu, W., Dillon, T., Chang, E., & Han, J. (2017).
Context-aware access control with imprecise context
characterization through a combined fuzzy logic and ontology-
based approach. In OTM Confederated International
Conferences “On the Move to Meaningful Internet Systems”
(pp. 132-153). Springer.
6. Kolias, C., Kambourakis, G., Stavrou, A., & Voas, J. (2017).
DDoS in the IoT: Mirai and other botnets. Computer, 50(7), 80-
84.
7. Kshetri, N. (2017). Can blockchain strengthen the Internet of
Things? IT Professional, 19(4), 68-72.
8. Li, W., et al. (2017). Securing proof-of-stake blockchain
protocols. Data Privacy Management, Cryptocurrencies, and
Blockchain Technology, 8(1), 297-315.
9. Mengelkamp, E., et al. (2018). A blockchain-based smart grid:
Towards sustainable local energy markets. Computer Science-
Research and Development, 33(1), 207-214.
10. Sharma, P. K., Moon, S. Y., & Park, J. H. (2017). Block-VN:
A distributed blockchain-based vehicular network architecture
in a smart city. Journal of Information Processing Systems,
13(1), 184-195.
11. Swan, M. (2015). Blockchain: Blueprint for a new economy.
O'Reilly Media, Inc.
12. Taylor, P. J., Dargahi, T., Dehghantanha, A., Parizi, R. M., &
Choo, K. K. (2019). A systematic literature review of
blockchain cybersecurity. Digital Communications and
Networks, 12(5), 1-14.
13. Trautman, L. J., & Ormerod, P. C. (2016). Corporate Directors'
and Officers' Cybersecurity Standard of Care: The Yahoo Data
Breach. American University Law Review, 66(1), 1231.
14. Yeoh, P. (2017). Regulatory issues in blockchain technology.
Journal of Financial Regulation and Compliance, 25(2), 196-
208.
15. Zheng, Z., et al. (2018). Blockchain challenges and
opportunities: A survey. International Journal of Web and Grid
Services, 14(4), 352-375.
