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One Step Forward: Towards a Blockchain
Based Trust Model for WSNs
Abdul Mateen1, Jawad Tanveer2, Ashrafullah1, Nasir Ali Khan1,
Mubariz Rehman1, and Nadeem Javaid1(B
)
1COMSATS University Islamabad, Islamabad, Pakistan
ammateen49@gmail.com, ashrafullahmarwat12@gmail.com,
nasirkhan.online@gmail.com, mubarizrahman@gmail.com,
nadeemjavaidqau@gmail.com
2Sejong University, Seoul, South Korea
comsats8@gmail.com
Abstract. Nowadays, Wireless Sensor Networks (WSNs) are facing var-
ious challenges. Cost efficiency, low energy consumption, reliable data
communication between nodes and security are the major challenges in
the field of WSNs. On the other hand, blockchain is also a very hot
domain in this era. Blockchain has a remedy for some challenges, which
are faced by the WSNs, e.g., secure data transactions and trustworthi-
ness, etc. By keeping in mind the security issues, we induce blockchain
into the WSNs. In short, we have proposed a trust model to avoid the
malicious attacks and keep the transact data using the blockchain prop-
erty of immutability. Moreover, an enhanced version of Proof of Stack
(PoS), i.e., the Proof of Authority (PoA) consensus mechanism is being
used to add a new node in the network. Additionally, the smart contract
is also written to check the working status of nodes. Simulations are
performed in order to record the transaction cost and execution cost.
Keywords: Blockchain ·Trust model ·Security ·ProofofAuthority
1 Introduction
Blockchain attracts great courtesy of researchers as they have faith in that,
this technology will bring remarkable changes and opportunities to industries.
Blockchain is a very powerful technology for resolving trusted communications
in a decentralized fashion. This technology was introduced back in 2008 and
circulated by the cryptography mailing group. The main strength of blockchain
is in decentralization, which allows direct (peer to peer) transactions. This app-
roach is also used in distributed systems where trust is not needed for nodes
to do transactions. Blockchain adopts many means such as: time stamping, dis-
tributed consensus, data encryption and economic incentives. It is used to solve
the problems having inefficiency, high cost and insecure data storage. In contem-
porary years, the research on blockchain technology is excited to grow quickly
with the rapid acclaim and development of blockchain.
c
Springer Nature Switzerland AG 2020
L. Barolli et al. (Eds.): 3PGCIC 2019, LNNS 96, pp. 57–69, 2020.
https://doi.org/10.1007/978-3-030-33509-0_6
58 A. Mateen et al.
Wireless Sensor Network (WSN) comprises of different type of small sens-
ing devices. These small devices are being used to monitor physical conditions.
Applications of WSNs are smart cities, military purpose, medicine and most com-
monly monitor an environment [1]. Sensing nodes are deployed in the desired area
with desired fashion (may be random or static) for the purpose of monitoring,
detecting and collecting information. It has some challenges, e.g., throughput,
routing, connectivity, void holes, small memory and most importantly security
issues.
The threats which are faced by the WSNs majorly come from two sources.
Firstly, the external attacks on the network and secondly, internal nodes of
the network become malicious [2]. Therefore, it is an essential security enigma
for WSNs to have the capability to recognize and exclude internal malicious
nodes. So, how to solve this security issue for sensor nodes becomes a major
challenge. The malicious node problem in WSNs can be avoided by using one
of the following two categories; (1) either propose a secure model or (2) WSN
protocol. In this paper, we adopt the first one and propose a trust model for
WSNs by using the concepts of blockchain.
In [8], Lin et al. proposed a blockchain based solution for Long Range
Wide Area Networks (LoRaWAN). Authors integrate blockchain and LoRaWAN
by considering the crowd sensing and sharing economy. They developed a
LoRaWAN server to solve the problems of trust on private network operators
and lack of network coverage. In this study, a mechanism is proposed to verify
the existence of data at a specific time on a network. Authors in [14]propose
a blockchain based location privacy protection incentive mechanism. Confusion
Mechanism Algorithm (CMA) is introduced to protect the user’s information by
encrypting the received information from the sensors. Blockchain is also there
to further secure the user’s information and issue incentives based on the fre-
quency of participation. Results show that the proposed mechanism increased
the user’s participation largely from 20% in traditional to 80% in the proposed
mode. However, the results obtained may be one-sided as a limited data (100
pieces of data) was collected.
In this paper, we proposed a blockchain based trust model for WSNs. This
model is used to avoid the malicious attacks and performs secure data transfer
from one ordinary sensor node to the sink node. The main contributions of this
paper are as follows:
•Trust model is proposed for avoiding the malicious attacks.
•A smart contract is composed and simulations are performed using the fol-
lowing tools: Remix IDE, Ganache, MetaMask and MATLAB R2018a.
•A comparative analysis table for transaction and execution costs is presented.
Remaining of this paper is proceeded as follows: Sect. 2covers state of the
art work. In Sect. 3, system model of this work is presented. Section4shows the
results of simulations. At the end, Sect.5concludes this work.
One Step Forward: Towards a Blockchain Based Trust Model for WSNs 59
2 Literature Review and Problem Statement
Authors in [3–5] proposed a blockchain oriented secure service provisioning mech-
anism for the lightweight Internet of Things (IoT) devices. Authors applied smart
contracts to check the validity of acquired services. High throughput and low
latency using consortium-blockchain with Proof of Authority (PoA) is achieved.
Analysis of packaging time, throughput and latency by comparing PoA with
Proof of Work (PoW) is also done in this work. Moreover, the results show that
the proposed scheme guards lightweight devices from untrusted edge service
providers and insecure services.
In [6], it is expected by the researchers that conventional blockchain tech-
nology cannot be effortlessly applied to mobile devices. It is due to the reason
that PoW prerequisites large computational ability and storage volume during
the mining process. For this, authors proposed Mobile Edge Computing (MEC)
enabled wireless blockchain framework in [7]. In which they used stochastic geom-
etry theory and Alternating Direction-Method of Multipliers (ADMM) based
algorithm. The proposed algorithm is also compared with the existing central-
ized solution. Simulation results demonstrate that the proposed algorithm is
efficient.
Blockchain based incentive mechanism was proposed in [9] for data storage
by the nodes of a WSN. The authors used Provable Data Possession (PDP)
technique instead of PoW to obtain better results. They also applied preserving
hash function to compare the existing data of nodes with the new one. The only
problem with PDP is that it can identify the damaged data on nodes, but is
unable to recover it.
The authors in [10] proposed a data transmission scheme based on the multi-
link concurrent communication tree model. It is to handle the failure nodes
in blockchain. Results show that proposed scheme works effectively for 15% of
failed nodes. However, if this number reaches the 30%, communication time and
delay will increase. In [11], problem of user access control for network optimiza-
tion in a data-intensive application was identified. Proposed solution considers
authenticity of Channel State Information (CSI) using blockchain consensus and
deep learning. Analysis shows that the proposed scheme increases the spectral
efficiency.
Branch based blockchain technology for Intelligent Vehicles (IVs) was pro-
posedin[12]. Branching is done at Locally Dynamic Blockchain (LDB). It is
to handle the large amount of data generated by IVs. While blockchain is used
to keep track of the data generated by IVs and to verify it. Additionally, the
concept of Intelligent Vehicle Trust Point (IVTP) is also introduced to build
the trust. Problem with branching is that duplicate state changes increase with
increasing load.
Orchestration is the automated configuration, coordination and management
of computer systems and softwares. A Blockchain-based Distributed Applications
(DApps) framework for multi domain service orchestration was proposed in [13].
The authors used blockchain, smart contract and DApps to solve the automation
and distributed harmony issues in networking. Results show that it is essential for
60 A. Mateen et al.
the Multi-domain Orchestrators (MdO) blockchain network to be secure. Also,
transaction confirmation time should be well defined for better performance.
At the same, representing smart contract and interpreting it in the proposed
framework is still an open topic to be covered.
In [16], blockchain is integrated with Internet of Vehicles (IoVs) to provide
large and secure data storage. The authors designed multi-blockchain architec-
ture consists of five blockchains according to the different data blocks to be
stored. Results show that this integration provides large and secure data storage.
They achieved high throughput with increasing data, but delay also increases. In
[17], the authors proposed a vehicular network architecture based on blockchain
for smart city. The authors used the blockchain with smart contract. However,
the service providers are not rewarded so they will not provide services effectively.
Some other authors also involve blockchain in their research works [19–27]for
multiple purposes.
2.1 Problem Statement
In conventional routing protocols, central authority is required for facilitating
the authentication and identification of every device. The research work in [18]
implements the blockchain in networks for avoiding malicious attacks. Two types
of attacks are considered in this paper: greyhole attacks and blackhole attacks.
However, the performance of the network was gradually decreased and some
unnecessary computations was involved due to the Proof of Work (PoW) consen-
sus algorithm. In current work, a trust model is proposed to avoid the malicious
attacks and provide the security to the sensor networks using the concepts of
blockchain. Moreover, PoW is replaced with PoA to avoid unnecessary compu-
tations, which were involved earlier due to the PoW.
3 Proposed System Model
In this section, the blockchain based system model for malicious node avoidance
in WSNs is presented. The key components for this system model are classified
as follow:
3.1 Ordinary Sensor Nodes
These sensor nodes only monitor the environment and collect the real-time data
and upload this data to the associated sink node.
3.2 Sink Nodes
These nodes perform three major responsibilities; first, data collection from ordi-
nary sensor node; second, new node addition using PoA consensus mechanism
and last, smart contract execution which is published by the main server. Sink
nodes differentiate data on the base of id and location of the ordinary node.
One Step Forward: Towards a Blockchain Based Trust Model for WSNs 61
Fig. 1. Blockchain based system model
Each sink node has its own database consists of hashes to keep the record of
transactions. Every sink node has the ability to communicate with ordinary sen-
sor node, other sink nodes and the main server. Sink node uses the private keys
for accessing the data from the main server.
3.3 Main Server
The main server is also known as endpoint or base station. The major tasks
for base station are to publish the smart contracts, issuance of activity and
processing of sensed data. The main server records each and every transaction
along with sink id and location in its immutable database. This database can
only be accessed by the main server itself or pre-authorized sink nodes.
It can be observed from the Fig. 1that the ordinary nodes are connected with
sink nodes. Every sink node will get the data from ordinary sensor nodes. Sink
nodes can send their data to other sinks as well as to the main server. Where,
a smart contract is implemented on sink nodes and issued by the main server.
Sink nodes can authenticate and blacklist any ordinary sensor node at any time
on the detection of malicious activity. Each sink has a communication record of
its own as well other nodes in its distributed ledger.
In this system model, the validity of data is checked at sink nodes. Noticeable
thing is that access on the main server is only granted to the sink nodes. The
main server checks the working status of sink nodes and ordinary nodes. It can
also remove any node if (1) it is dead or (2) involved in any suspicious activity.
62 A. Mateen et al.
3.3.1 Hash Function
For each transaction, a hash is generated which is called transaction hash. A hash
is just a function which takes the input value and generates the output value.
This output is a deterministic value against the input value. This is mathemat-
ically written as follows:
f(a)=b, (1)
where, ais any input and bis associated output against the a; e.g., hash
value for “hi” in keccak-256 is “7624778dedc75f8b322b9fa1632a610d40b85e106
c7d9bf0e743a9ce291b9c6f”. Hash values are generally ‘irreversible’ which means
that input cannot be figured out by knowing the output except hit and trial
method.
4 Simulation Results
In this section, we discuss the simulation results which are obtained using dif-
ferent tools and the reasons for these results. In Sect. 4.1, simulation tools are
explained. Moreover, results and their reasoning are discussed in Sect.4.2.
4.1 Simulation Tools
In order to take the simulation results, we have used multiple tools. Four tools are
reviewed for developing and testing the smart contract. First, we write a smart
contract on Remix IDE. Second, Ganache is used to show the clear deployment
visualization of the smart contract. Third, to connect the Etherium node with
browser, MetaMask which is the extension of Chrome browser, is used. Fourth,
execution cost and transaction cost of different transactions are obtained from
Remix IDE and later plotted with MATLAB.
Transaction Cost Execution Cost
0
1
2
3
4
5
6
Cost (gas)
106
Fig. 2. Network deployment cost
One Step Forward: Towards a Blockchain Based Trust Model for WSNs 63
Table 1. Network deployment cost
Parameter Val u e
Status 0x1 Transaction mined and execution succeed
Transaction hash 0x98933, ..., 75f15
Contract address 0x08970, ..., 659fb
From 0xca35b, ..., a733c
To Clustering.(constructor)
Gas 300000000 gas
Transaction cost 5674465 gas
Execution cost 4272505 gas
Hash 0x98933, ..., 75f15
Input 0x608...40029
Decoded input {}
Decoded output -
Logs []
Valu e 0wei
Current states of Sink nodes Current states of Sink nodes on main server
0
0.5
1
1.5
2
2.5
3
Cost (gas)
104
Transaction Cost
Execution Cost
Fig. 3. State checking cost of sink nodes
Sink Node 1 Sink Node 2 Sink Node 3 Sink Node 4 Sink Node 5
0
0.5
1
1.5
2
2.5
3
3.5
Cost (gas)
104Transaction Cost Execution Cost
Fig. 4. Individual state checking cost of sink nodes
64 A. Mateen et al.
Sink Node 1 Sink Node 2 Sink Node 3 Sink Node 4 Sink Node 5
0
1
2
3
4
5
Cost (gas)
104Transaction Cost Execution Cost
Fig. 5. Transaction cost of sink nodes
4.1.1 Remix IDE
Integrated Development Environment (IDE) is an open source tool which allows
you to debug, test and compile smart contract from browser. It helps program-
mers for designing the software and other different tasks relating to software
development.
Table 2. Current active/de-active state of nodes
Parameter Val u e
Transaction hash 0xfbaef, ..., 840f96
From 0xca35b7, ..., fa733c
To Clustering.StateOfSNs() 0xbbf28, ..., 732db
Transaction cost 27886 gas (Cost only applies when called by a contract)
Execution cost 6614 gas (Cost only applies when called by a contract)
Hash 0xfbaef, ..., 840f96
Input 0x38e, ..., fccad
Decoded input {}
Decoded output {“0”: “string: Current state of Sink Node 1 is: 1”
“1”: “string: Current state of Sink Node 2 is: 1”
“2”: “string: Current state of Sink Node 3 is: 0”
“3”: “string: Current state of Sink Node 4 is: 0”
“4”: “string: Current state of Sink Node 5 is: 1”
“5”: “string: State of selected Ordinary Node is: 1”}
Logs []
One Step Forward: Towards a Blockchain Based Trust Model for WSNs 65
Table 3. Comparison of different costs
Function Transaction cost (gas) Execution cost (gas)
Network deployment cost 5674465 4272505
Per transaction cost
Sink Node 1 46325 23837
Sink Node 2 46019 23595
Sink Node 3 46237 23749
Sink Node 4 46193 23705
Sink Node 5 46457 23969
Current state (Active/De-active)
of sink nodes
27886 6614
Current state (Active/De-active)
of sink nodes according to main
server
27911 6639
Individual state checking cost
Sink Node 1 30427 9155
Sink Node 2 30493 9221
Sink Node 3 31964 10692
Sink Node 4 32118 10846
Sink Node 5 30515 9243
4.1.2 Ganache
Ganache provides a clear visualization of the smart contract deploying trans-
actions. Ganache grants you access to 10 accounts and each having 100 Ethers
for testing purpose. When a transaction or a smart contract is deployed on the
blockchain, Ganache immediately confirms this transaction or smart contract. In
the result of any transaction or smart contract deployment, the transaction log
is increased and Ether is deducted. Each transaction has details of fund trans-
fer, contract creation and contract call, etc. along with the sender’s address and
transaction hash.
4.1.3 MetaMask
MetaMask is a Google Chrome extension which connects the Etherium node
and browser. It allows us to send and receive Ethers from Ganache. For this, the
connection of Ganache wallet with MetaMask is possible by using a private key.
MetaMask is also connected with Remix IDE. When Remix IDE and MetaMask
are connected, Ether will be deducted on each transaction.
4.1.4 MATLAB R2018a
MATLAB R2018a is a comfortable tool for researchers to work within. It is
a multi-dimensional mathematical computing environment used to solve linear
66 A. Mateen et al.
programming problems within seconds. However, we have used this tool for get-
ting plots by passing the values which were obtained by the Remix IDE.
4.2 Simulations Reasoning
In this section, the simulation tools, results and reasoning of these results will be
discussed. Nevertheless, we provide an overview of some important terms which
require for understanding the term gas price and about its calculation.
4.2.1 Execution Cost
Execution cost is a cost which requires the gas as a fuel on the execution of the
functions (code lines). It also requires storage allocation for different variables
as a result of the execution of operations. On the other hand, the transaction
cost requires for sending the data on the blockchain.
4.2.2 Estimating Transaction Cost
The total Ether cost of a transaction is based on the following two factors:
•Gas used: it can be defined as total gas consumed by the transaction.
•Gas price: it is a price of per unit gas specified in the transaction.
This transaction cost is calculated by the following formula:
Costtotal =Ugas ×Pgas.(2)
Where, Ugas and Pgas represent the gas used in transaction and price specified
for that transaction, respectively.
4.2.3 Why Ether Is Not Used Instead of Gas?
Actually, it is made to decouple the cost of any operation from the market price
of Ether. As we know that the cryptocurrency prices are volatile and Ether also
has no exception. The gas limit for each action is constant and this is the reason
why we use gas instead of Ether.
Simulations for the calculation of execution and transaction costs are per-
formed in Remix IDE. During simulations, it is observed that the transaction
cost is always high with the comparison of execution cost. We perform a cost
analysis for a smart contract using the aforementioned costs in term of gas
consumption. Figure 2shows the transaction and execution costs required for
network deployment. We can see from the Fig. 2that the operation for network
deployment is the most expensive. It can also be seen from the Table 1that the
transaction cost for network deployment is 5674465 gas which is higher than the
execution cost (4272505 gas).
Figure 3depicts the state checking cost of sink nodes. State checking cost
means that the cost which is used for ensuring the active or de-active status of
sink nodes. To check whether the sink nodes are active or not, their status has
One Step Forward: Towards a Blockchain Based Trust Model for WSNs 67
been checked by other sink nodes and then by the main server. This active or de-
active states must be the same in both places. If the status is same then the node
is working perfectly; otherwise, the node is malicious and need to be removed
from the network. This state checking cost is presented in Fig.3. Similarly, Fig. 4
shows the transaction and execution costs for each sink node’s state. Moreover,
status for each node is presented in Fig. 4and this status is cross-verified by
the main server. Nevertheless, notable thing is that the active status of nodes is
represented by “1” and vice versa by “0”.
Transaction and execution costs per transaction are shown in Fig. 5.Wecan
easily observe the difference between both of aforementioned costs. Transaction
cost is always high and execution cost is low. We have already discussed the
reasons for the higher transaction cost than the execution cost.
4.2.4 Comparison Between Transaction and Execution Costs
We execute different functions and calculate the transaction and execution costs
in terms of gas. After that, these costs are plotted using MATLAB. Moreover,
the aforementioned costs for different functions are provided in Tables1and 2,
respectively. Nevertheless, we have also provided with comprehensive comparison
of different costs in Table 3.
5 Conclusion
WSN has the ability to monitor, collect and send data from one place to another
in unorthodox conditions. However, this network has lots off security risks. In this
paper, we come up with the solution for their security concerns by exploiting the
blockchain concepts. So in this paper, we propose a blockchain based trust model
for WSN to communicate with other nodes without having any security risks.
Moreover, simulations are performed to compare the transaction and execution
costs. In future, we will implement blockchain in any state of the art routing
protocol and compare the performance with the original one.
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