https://doi.or g/10.31449/inf.v47i4.3494 Informatica 47 (2023) 515–522 515
Blockchain-based Efficient and Secur e Peer -to-Peer Distributed IoT Network
for Non-T rusting Device-to-Device Communication
Rajesh Kumar Sharma and Ravi Singh Pippal
Department of Computer Science & Engineering,
RKDF University , Bhopal, India
E-mail: rajeshsharma.ercs@gmail.com, ravesingh@gmail.com
Keywords: Security , blockchain, internet of things, avalanche ef fect, device-to-device communications, peer -to-peer
communications
Received: April 5, 2021
The security and privacy issues in the Internet of Things (IoT) ar e a mandatory pr ocess and also a challeng-
ing task for r esear chers. Blockchain technology enhanced and motivated the r ecent security parameters,
and it has been validating various technical sectors since its inception. In this paper , a peer -to-peer dis-
tributed IoT network is pr esented wher e non-trusting devices can interact with other devices without a
trustworthy intermediary using the blockchain technique in automated verifiable mode. Major implemen-
tation issues for deploying blockchain in the IoT network ar e pointed out in this paper . The model pr esents
a modern blockchain technique to surpass the traditional security system for efficient and secur e IoT de-
ployment under various conditions. Finally , to validate the signification of blockchain in the IoT network,
the avalanche effect is calculated and compar ed with T riple-DES, AES, and Blowfish cryptographic al-
gorithms for non-trusting device-to-device (D2D) communications and transactions. The r esult pr esents
significant output changes in hash for the blockchain-IoT integrated model as compar ed to other crypto-
graphic algorithms. Conclusively , blockchain in the IoT network can make a r emarkable impact acr oss
various industrial and business applications.
Povzetek: Študija pr edstavlja varno bločno omr ežje za IoT , ki omogoča komunikacijo br ez zaupanja med
napravami, s primerjavo z obstoječimi kriptografskimi algoritmi.
1 Intr oduction
The most auspicious technologies in this modern era are
the Internet of Things (IoT) and the Blockchain. The per -
fect solution to incorporate decentralized security in IoT
is blockchain technology for peer -to-peer communication,
and the integration of these two technologies is certainly
required in many applications and domains [ 1 ]. There are
many possible blockchain applications for IoT cases, in-
cluding the healthcare industry , supply chain management,
public safety , personal data management, finance, educa-
tion, insurance, notary services, smart homes, and cities
[ 2 , 3 ]. Blockchain is continuously blowing up modern IoT -
based industries, and it is expected to motivate IoT onward.
The distinguishing features, such as decentralized trust and
security provided by blockchain, are crucial characteristics
of IoT infrastructure [ 4 ]. Many researchers are innovatively
working on IoT -blockchain collaboration in several ways
due to the prevalence of both technologies and inventing
extremely secure and robust systems to address the techni-
cal problems [ 5 ].
A blockchain framework stores information records in
attached blocks, which are connected using a cryptographic
algorithm [ 6 ]. Basically , it has a continuously extending
database list in distributed form to maintain record infor -
mation, where participating nodes in the blockchain vali-
date new and existing records [ 7 ]. For establishing a trusted
network between nodes, any central third-party authentica-
tion or participating node is not required in this decentral-
ized blockchain network [ 8 ]. All the completed transac-
tions and their information are always shared, distributed,
and updated to each node in the blockchain network, so all
the nodes have the exact same information record [ 9 – 1 1 ].
The most secure and transparent system than centralized
transactions can be structured by the blockchain. It can ef-
ficiently record transactions and details between two par -
ties using a distributed ledger in a permanent and verifiable
way . Ultimately , privacy , security , anonymity , and trans-
parency are the main goals of blockchain technology for all
of its users.
Information about other physical conditions in the envi-
ronment is acquired by Internet of Things (IoT) devices,
and they communicate and transmit data with each other us-
ing inbuilt software systems. IoT devices generate a huge
quantity of information and sensing data, but devices do
not inevitably trust others at the time of transactions. Criti-
cal privacy issues can be raised because connected IoT de-
vices transmit sensitive personal information and can dis-
close the preferences and behaviors of their users. When
personal, sensitive data is utilized by any centralized or -

516 Informatica 47 (2023) 515–522 R. K. Sharma et al.
ganization, the privacy of IoT users is especially at risk
due to the illegitimate usage of data. T o solve this prob-
lem, blockchain technology can be beneficial in structuring
privacy-preserving IoT systems. There are many techni-
cal benefits of blockchain, as presented in Figure 1 . The
foremost benefit is security , and other facilities such as
open architecture, timestamped, smart contacts, distributed
ledger technology , etc. are significant characteristics of
blockchain technology .
Figure 1: T echnological Benefits of Blockchain
Since the blockchain is peer -to-peer (P2P) technology ,
it is tamper -proof, contains only trustworthy information,
and is not dominated by any single centralized entity . The
blockchain technology provides secure agreement-based
peer -to-peer communications between devices in the IoT
network. It also resolves other issues such as trust, privacy ,
scalability , time-stamping, single points of failure, and re-
liability challenges of the network for IoT devices. For the
transmission of data between devices in a consistent, se-
cured, and time-stamped manner , blockchain technology
of fers a trustworthy framework for the IoT network. In this
infrastructure, IoT devices can take advantage of smart con-
tracts to enable message conversations, which create trust
agreements between devices. The characteristics of au-
tonomous activities and intelligent applications for sensing
devices can be enabled using these features. T o construct a
completely distributed, trustworthy blockchain-based dig-
ital infrastructure, IoT -based peer -to-peer transactions can
be extended to a person-to-device or person-to-person plat-
form. Currently , there are numerous blockchain-based so-
lutions and applications; it has continuously been applied
in various cases since its inception.
2 Blockchain technology
Blockchain is a distributed, trusted, shared, and public
ledger of transactions that every user can analyze but a
single user cannot control. Basically , it is a distributed
database system that preserves the endlessly developing list
of all transaction data and records in a cryptographically
locked system from any tampering or violation. Since the
Blockchain is a distributed system, the concept of a central-
ized master node is not required, and all the other connected
nodes maintain a true copy of the database. An ef ficient,
highly resistant, transparent, and secured digital interac-
tion and transaction storage system is of fered by blockchain
technology . This system has the potential to enable new in-
dustrial and business models.
In blockchain technology , all transaction data and relay
information are listed in the connected chain of blocks ini-
tiated and generated by anonymous users. It provides ad-
vantages such as speed, transparency of transactions, cost
ef ficiency , and high security . Blockchain provides data im-
mutability using cryptographic hashes, where data is stored
linearly and the new block keeps a record of the hash value
of the previous block. Each transaction is required to un-
der go validation before being appended to the blockchain
by participants in the network. The noteworthy issues con-
stituted by blockchain technology are related mainly to the
following:
– Accuracy ,
– T rust,
– Intermediaries,
– Decentralization,
– T ransparency ,
– T ransaction freedom.
– Data privacy and security ,
3 Beneficial aspect of
blockchain-based IoT
The engrossment of blockchain-based IoT research is to
gear up an ef ficient, secure, and trusted peer -to-peer dis-
tributed IoT network for communications among non-
trusting devices. Blockchain technology of fers many ben-
eficial aspects for IoT [ 12 ]:
– The blockchain-based shared ledger is immutable and
can hold records. Many characteristics of the IoT
network, such as the type of device, sensing fea-
tures, range, embedded software, malfunctions, status,
hardware changes, and current position, enhance trust
among devices and their data.
– T rust agreement between devices for any sensed and
measured value of specific characteristics in the IoT
network.
– The smart contracts allow the devices to interact au-
tonomously and independently with other commercial
systems and devices.

Blockchain-based Ef ficient and Secure Peer -to-Peer… Informatica 47 (2023) 515–522 517
– Third-party validation, verification, or trust is not re-
quired, which provides cost reduction and high trans-
action speed.
– Easy and ef ficient recovery of data and information
due to distributed ledger recording management dur -
ing system failure.
The overall important advantage is the transfer of trust in
a trustless infrastructure. This is especially applicable in
the IoT network, where many types of IoT device manu-
facturers have a dif ferent standard of accuracy , range, and
functional characteristics. In the network, if new devices
are added, smart contracts can be used to interact and com-
municate with other IoT devices for transactions, repair ser -
vices, or replacement. The other devices can assume the re-
sponsibilities in case any device malfunctions. It validates
and increases the value of data generated by IoT devices.
4 Related work
This section presents existing works, ef forts, and literature
reviews based on blockchain-integrated IoT systems to tar -
get the issues of privacy and security .
Chen et al. [ 14 ] proposed a data integrity checking
system on the Internet of Things (IoT) network using the
stochastic blockchain technique. They investigated the po-
tentiality of blockchain to protect data integrity and secu-
rity in the Internet of Things networks. The conventional
decentralized techniques face the issues of network conges-
tion and single-point failure. T o overcome these shortcom-
ings, a stochastic-based blockchain method is proposed for
verifying data integrity in the IoT network. The proposed
method minimizes the quantity of cooperating IoT devices
and relies on edge devices to produce the block, which re-
duces the computational and transmission time. The sim-
ulation outcomes present an enhanced success rate against
lar ge-area IoT networks with a low number of cooperating
devices.
Haseeb et al. [ 13 ] presented “R TS: a robust and trusted
scheme for IoT -based mobile wireless mesh networks” for
increasing network coverage with the reliability of the sys-
tem. Their proposed model for IoT -based mesh networks is
presented in Figure 2 . In this model, RSA-based cryptog-
raphy is applied to communication links between gateways
and clients of the mesh network with existing malicious de-
vices. The existing data routing method works for static
mesh devices and monitors transmission links, which can
create a deficient ef fect on the performance of the network
and increase the chance of packet drop ratio. Their pro-
posed infrastructure constitutes a mesh network of mobile
clients to perform better network exposure in data trans-
mission lines, considering factors for packet drop reduction
and a high ratio of data delivery . This model overcomes
the communication cost by using the flooding of distance
vector routing over periodic time intervals by mobile mesh
clients. Their simulation outcomes present high data relia-
bility as well as a low computational operating expense in
dif ferent topological networks.
For edge-based devices in the Internet of Things (IoT)
network, Pyoung et al. [ 15 ] proposed “LiT iChain, a
blockchain with finite-lifetime blocks”. The LiT iChain
handles the dif ficulty of traditional blockchain as it con-
tinuously grows into an information block list. The out-
dated block of information should be promptly eliminated
so that an extended blockchain list can be stored at the end
node. T o eliminate the information block consistently , a
tree-structured end-time ordering graph (EOG) was intro-
duced to arrange block lists according to their endings, and
it also maintained the chain connectivity of the blocks.
Mazzei et al. [ 16 ] designed and implemented secure in-
dustrial devices using blockchain-based interfacing tech-
niques. Their proposed system allows interaction devices
to be made available to the public as a secure blockchain
service. The proposed system can also be easily modified as
an independent blockchain-equipped tracking system. The
system acts as a connection between blockchain-based se-
curity and the industrial Internet of Things, which enable
the tokenization of industrial devices.
Lei et al. [ 17 ] proposed “Groupchain”, an original
double-chain structure-based scalable public blockchain
system for fog computing in IoT . T o address the problem
of increased transaction throughput generated by the serial-
ized leader election process, they proposed a double-chain
structured-based IoT security system using blockchain.
The experimental results of the implemented “Groupchain”
prototype present the scalability and transaction ef ficiency
of “Groupchain”.
Muthavhine et al. [ 18 ] studied concerning cryptographic
algorithms applied, especially in the security of the Internet
of Things. They collected existing cryptographic methods
applied to several IoT devices for encryption and authen-
tication, analyzed the A valanche ef fects of cryptographic
algorithms for each device, and improved their speed using
mathematical methods.
Novo [ 19 ] addressed the extensibility problem of access-
ing, arranging, and managing a lar ge number of secure IoT
devices because conventional centralized control to access
the system is unable to handle increasing loads ef fectively .
This research introduced a novel access handling control
that reduces the management problems of plenty of con-
strained devices in the Internet of Things network. The pro-
posed technique is a completely decentralized blockchain-
based method.
For autonomous cooperative intrusion detection in the
devices of lar ge Internet of Things networks, Mirsky et al.
[ 20 ] introduced a blockchain-based security solution. In the
IoT network, an agent system is configured for detection of
any software exploitation on the devices, which provides
regular control for intrusion detection. Any kind of man-
ual activity or update is not required to generate a malware
signature in this proposed framework.
Due to the deficient management of the Internet of
Things network and devices, particularly the arrangement

518 Informatica 47 (2023) 515–522 R. K. Sharma et al.
Figure 2: T rusted and Robust Model for IoT -based Mesh Network [ 13 ]
and installation method, observable exploitation in the IoT
network environment can be detected. T o provide a so-
lution to this problem, Y ohan et al. [ 21 ] proposed the
“Firmware-Over -the-Blockchain (FOTB) Framework, a se-
cure and ef ficient blockchain-based firmware update struc-
ture between manufacturers of IoT devices and network-
deployed devices. In this proposed framework, a peer -
to-peer verification technique through a blockchain-based
mechanism is applied for the security of firmware distribu-
tion activities, which also ensures the integrity of the system
in a distributed IoT network.
Li et al. [ 22 ] designed “Blockchain-based Distributed
IoT Data T ransaction (BDDT)” a novel data architecture for
the IoT network that of fers a framework for data producers
and users and provides a solution for reliability problems
and usage of data facilities of fered by the central storage of
IoT . The problems of secure data circulation and transac-
tion in IoT network, BDDT system ef ficiently resolve these
problems.
Liu et al. [ 23 ] combined blockchain technology in the
”Attributed-Based Access Control (ABAC) Model”, which
carries the benefits of blockchain-based decentralized tech-
nology for access control demands into the Internet of
Things and solves the problem of conventional access con-
trol techniques. The ABAC model provides a device au-
thentication system, implements the management policy of
ABAC, and verifies device security access using the smart
application. A Hyperledger Fabric-based opensource ac-
cess control system “Fabric-IoT” is developed and applied
in the network. The final steps involved in this model
are network deployment using blockchain, installation of
chaincodes, and invoking smart contracts.
Rathee et al. [ 24 ] proposed a blockchain technology-
based secure hybrid “Industrial Internet of Things (IIoT)”
framework. In this framework, the activities of employees
are collected and stored by blockchain-based industrial IoT
devices to maintain the security , transparency , and tracing
of all work by producing the hash of each record for IoT de-
vices. The proposed secure framework expressively mini-
mizes the loss ratio of the product and falsification prob-
lems in network devices.
Chatterjee et al. [ 25 ] developed a lightweight authen-
tication network protocol for secure key swapping, text
messaging, and supporting the hierarchically architectural
framework of the IoT network. T o protect against adver -
sarial active and passive threats, the Physically Unclonable
Function (PUF) [ 26 ] cryptography method is used. The
limitations of previous PUF-based security methods can be
eliminated using their proposed protocol, which is strong
against many threats.
W ang et al. [ 27 ] proposed a hierarchically struc-
tured storage system for storing the blockchain in a
cloud network, and it maintains newly added blocks in
the blockchain network. They presented a blockchain-
integrated Internet of Things architecture to protect and
maintain blocks and transactions produced in IoT networks.
The blockchain and cloud connection as a software inter -
face is designed to build block synchronization for storage
in the cloud.
For the security of supply chain management applica-
tions, Malik et al. [ 28 ] proposed a blockchain-based “T rust
Management Framework (T rustChain)” to solve the issues
related to the quality trust of commodities and the entity
of logging data. Basically , the “T rustChain” framework
utilizes blockchain technology to monitor all interactions.
The agent- and asset-based reputation model is also pro-
vided by this framework; it reaches ef ficiency and automa-
tion through smart contracts with the reputations provided
to the same participant for the particular product.
Biswas et al. [ 29 ] designed and implemented a novel
“lightweight block cipher named LRBC” to constrict In-
ternet of Things resources. By integrating Feistel and
substitution-permutation networks (SPN), the proposed
structure has been implemented, which takes advantage of

Blockchain-based Ef ficient and Secure Peer -to-Peer… Informatica 47 (2023) 515–522 519
both techniques. T o resist linear and dif ferential attacks,
LRBS produces a high quantity of extinct S -boxes. Gu-
ruprakash and Koppu [ 30 ] carried out an empirical inves-
tigation to showcase that the “Edwards curve digital sig-
nature algorithm (EdDSA)” can serve as a performance-
enhancing alternative to the “elliptic curve digital signa-
ture algorithm (ECDSA)” in the context of Blockchain and
IoT . T anweer Alam [ 31 ] introduced “IBchain”, an IoT and
blockchain-integrated system that can be used for secure
communications in a smart city network.
V arious state-of-the-art methods for securing the IoT
network have been provided in the literature, with their
advantages and limitations. Many researchers addressed
blockchain-based solutions in their unique and specific pro-
posed methods. However , these studies lack validation and
comparative analysis with other applicable modern crypto-
graphic algorithms. T o address this research gap, a com-
parative analysis of blockchain with modern cryptographic
techniques is provided in this research, using the A valanche
ef fect as a parameter to observe the significant changes in
the hash value.
5 IoT management in blockchain
The management of IoT devices in blockchain technique
of fers essential information to the significant structured
layer and works on the controllable components of the sys-
tems. Figure 3 illustrates the structured layer of blockchain-
based IoT management. The four major components of
Figure 3: IoT Management in Blockchain
this structured layer are represented as:
– Blockchain Unit: It manages useful information and
blockchain activities. All kinds of ledger data and in-
formation are used by this part. It contains three sub-
units:
1. Blockchain of things,
2. Microservice for blockchain,
3. Smart contracts.
The microservice index contains information about
smart contracts.
– Peer -to-peer Communication Unit: Data commu-
nication, exchange, and transfer are facilitated by
this component with the help of peer -to-peer network
technology . The management process related to the
blockchain of things is also controlled by this compo-
nent.
– Smart Contract Unit: The function and process re-
quired for smart contracts defined by the system are
provided by this component. The blockchain unit is
responsible for storing smart contract codes and infor -
mation. The smart contracts are capable of processing
the mechanism of the system.
– Payment Unit: All the payment processes and trans-
actions are supported by this unit in cooperation with
the structured function layer and other components of
the IoT device management layer . The wallet infor -
mation of the user and IoT devices is also managed by
this unit.
6 Pr oposed method
In cryptographic analysis, the avalanche ef fect is basically a
mathematical function applied to the encryption technique,
and it is evaluated as the most preferable attribute of the
encryption algorithm. The avalanche ef fect presents a con-
siderable change in the ciphertext if a few changes are made
in either the plaintext or key . This basic property is known
as the avalanche ef fect in cryptography . Generally , it mea-
sures the quantity of ef fect on the ciphertext concerning mi-
nor alterations made to the key or the plaintext.
The method is to consider fixed-length inputs to the hash
function f . Otherwise, it is problematic what probabil-
ity distribution it wants to impose on the input set{ 0, 1} ∗ which is the collection of all finite input strings. In prac-
tice, hash functions do have an upper limit on the input
string, but that’ s astronomical, in terms of testing all input
strings. The simple explanation of the A valanche Ef fect is
that “A small change in the plaintext (or key) should create
a significant change in the ciphertext”. Concerning these
characteristics, “Data encryption standard (DES)” has been
proven to be significantly strong.
So, let’ s assume the hash function has a security param-
eter ofk bits. This corresponds to the function acting like
a random function with outputs of lengthn = 2k bits.
The testing would generate numerous random values
from a uniform distribution on { 0, 1} m
, thus treating the
hash function as a random functionf :{ 0, 1} m
→{ 0, 1} n
.
Let this random set of inputs be denoted byX . Now define
a
ij
= #{ x∈ X : [f(x⊕ e
i
)]
j
̸= [f(x)]
j
} (1)
for1≤ i≤ n, 1≤ j≤ m , wheree
i
is the vector with a one
in thei
th
position and zeroes everywhere, and [u]
j
denotes
the j
th
component of vector u . a
ij
counts the number of
inputs fromX that dif fer in thej
th
output bit when thei
th
input bit is flipped.
It can now be defined as a degree of strict avalanche cri-
terion,D
SAC
(f) as
D
SAC
(f) := 1− n
∑ i=1
n
∑ j=1
∥ 2aij
#X
− 1∥ nm
(2)

520 Informatica 47 (2023) 515–522 R. K. Sharma et al.
Figure 4: A valanche Ef fect on Cryptographic Algorithms
with the expectation thatD
SAC
(f) should be approximately
1, i.e., the sum of the absolute dif ferences. A modification
in a single bit of plaintext or key generates a significant
modification in many bits at the ciphertext outcome; this
is well known as the A valanche ef fect.
A valanche Ef fect =
N
c
N
p| k
(3)
where, N
c
is the number of bit changes in ciphertext and
hash, whereasN
p| k
is the number of bit changes in plaintext
or key in the IoT -generated data. The A valanche ef fect hash
function is presented in Figure 5 .
Figure 5: A valanche Ef fect Hash Function
7 Result analysis
After a successful simulation, the test result shows the
outcome of the A valanche ef fect. Similar and uniformly
small changes were made to the input value of plaintext
or key (IoT -generated data), and the hash functions gener -
ated a hash sum as the output. For testing purposes, three
cryptographic encryption methods are considered ”T riple
Data Encryption Standard (3-DES), Advanced Encryption
Standard (AES), and Blowfish”, along with the blockchain
method. A desirable attribute of any encryption technique
is that some minor modification in either plaintext gener -
ated from IoT devices or the key must generate a consid-
erable dif ference in the ciphertext output and its associated
hash value. The simulation result is presented in Figure 4 .
The A valanche ef fect as a significant change in hash value
is presented in the T able 1 , which shows the percentage of
output changes in hash with respect to the number of input
bits changes for Blowfish, AES, 3-DES, and Blockchain.
T able 1 is basically a numeric representation of the simu-
lation result ( Figure 4 ).The quantity of changes in the per -
centage of hash output depends on the cryptographic algo-
rithms and the changes in the number of input bits. T a-
ble 1 definitely shows that the blockchain presents high
percentages of variations in hash output as compared to
other cryptographic methods, as 1–2 bits changes in input
af fect 9%–33% changes in a hash using Blowfish, 12%–
45% for AES, 55%–81% for 3-DES, and 44%–88.4% for
Blockchain. Similarly , when changing 1 1–12 bits in in-
put, the percentage of changes in hash output for Blow-
fish is 7%–36%, for AES it is 21%–55%, for 3-DES it is
12%–70%, and for Blockchain it is 21%–93% as the high-
est changes. The blockchain percentage may not vary uni-
formly with the increment in the number of inputs because
the avalanche ef fect is basically a ratio of the number of bit
changes in ciphertext or hash to the number of bit changes in
plaintext or key . The significance of the result is considered
based on the maximum percentage of variation in the hash
for the blockchain. The result shows the high avalanche ef-
fect of blockchain as compared to T riple-DES, AES, and
Blowfish. Significantly , the maximum changes in the bits
of ciphertext can be observed in the blockchain method as
compared to other cryptographic techniques. A blockchain-
based IoT network is more secure for non-trusting device-
to-device communications and transactions.
Our objective is to present a method for ef ficient and
trustworthy P2P communications and transactions in a
blockchain-based distributed IoT network for non-trusting
D2D communication without a centralized 3rd party .

Blockchain-based Ef ficient and Secure Peer -to-Peer… Informatica 47 (2023) 515–522 521
T able 1: A valanche Ef fect on Cryptographic Algorithm
No. of Input Output Changes (%)
Bits Changes Blowfish AES 3-DES Blockchain
1–2 9%–33% 12%–45% 55%–81% 44%–88.4%
3–4 12%–38% 9%–30% 40%–70% 25%–83%
5–6 5%–29% 14%–55% 35%–88% 57%–94%
7–8 15%–31% 17%–45% 25%–78% 42%–88%
9–10 4%–26% 19%–43% 45%–68% 6%–79%
1 1–12 7%–36% 21%–55% 12%–70% 21%–93%
Changes made by intruders in IoT -generated data can be
validated using the A valanche ef fect, and blockchain-based
integrity can be provided by using the proposed model.
8 Conclusion and futur e work
This research presents a significant peer -to-peer distributed
IoT network based on blockchain technology for secure
and ef ficient non-trusting device-to-device communication
and transaction. Manipulating and integrating the IoT net-
work with blockchain modeled a secure system success-
fully . The model presents a modern blockchain technique
to surpass the traditional security system for ef ficient and
secure IoT deployment under various conditions. Finally ,
to validate the signification of blockchain in the IoT net-
work of non-trusting device-to-device communication, the
avalanche ef fect is calculated and compared with T riple-
DES, AES, and Blowfish cryptographic algorithms using
IoT -generated data. The result presents significant output
changes in hash for the blockchain IoT integrated model
as compared to other cryptographic algorithms. Using the
A valanche ef fect calculation, the hash function with the en-
cryption technique of blockchain can significantly provide
strength to the IoT network, as proven by the security level
validation.
The proposed work can be applied to applications based
on intrusion detection techniques. This work can be ex-
tended by comparing blockchain with other hybrid crypto-
graphic methods. In the future, using the A valanche ef fect,
the validation assessment can be done in the fog/edge com-
puting model as well as on a cloud server . The avalanche
ef fect assessment is an engrossing process to notice the IoT -
generated data processing techniques of blockchain that can
be enhanced for validity checking in other applications such
as banking, financial, business, and industrial transactions.
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