A Blockchain-Based Multi-Mobile Code-Driven Trust Mechanism for Detecting Internal Attacks in Internet of Things

Tariq, Noshina; Asim, Muhammad; Khan, Farrukh Aslam; Baker, Thar; Khalid, Umair; Derhab, Abdelouahid

doi:10.3390/s21010023

Cited by 41 publications

(37 citation statements)

References 70 publications

(96 reference statements)

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“…In [14] suggested an energy-effective decentralized mechanism of trust with the use of the blockchain-dependent solution for multi-mobile code on behalf of sensing the interior attacks in the SN (sensor node) enabled IoT. The outcome validates improved concert of presented technique over traditional ones with 43.94% and 2.67% a reduced amount of overhead message in the Greyhole and blackhole attack circumstances correspondingly.…”

Section: Related Workmentioning

confidence: 64%

Trust-based Key Management Conglomerate ElGamal Encryption for Data Aggregation Framework in WSN using Blockchain Technology

Babu¹,

Jayalakshmi²

2021

IJACSA

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In wireless sensor networks (WSN), data aggregation is a widely used method. Security issues like data integrity and data confidentiality became a significant concern in data aggregation when the sensor network is deployed in a hostile environment. Many researches may carry out several works to tolerate these security issues. However, there were some limitations like delay, the arrival rate of packets, and so on. Hence, to overcome the existing problems, this approach offers a blockchain-dependent data aggregation scheme in WSN. The main intention of the proposed work is to generate a certificateless key generation so that the proposed system's secrecy rate is improved. The use of blockchain is employed for security purposes, and it enables the user to acquire the information stored internally in an effortless manner. Initially, deployment of sensor and base station (BS) is carried out, followed by node registration at which the public/private keys are generated. The computation of private hash values is carried by performing certificateless key generation. After that, the formation of blockchain is made using the PoW (Proof of Work) detection algorithm followed by the aggregation of data. In the data aggregation process, Elgammal based cryptographic approach is introduced to acquire member data, perform aggregation logic, and transfer the aggregated data. Finally, cluster-based routing is established with the use of Knapsack based cluster routing strategy. The performance investigation of the proposed system is estimated and the outcomes attained are compared with the existing techniques in terms of arrival rate, average delay, and the delay ratio of the packets. The investigation illustrates that the suggested approach is better than the traditional techniques.

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Section: Related Workmentioning

confidence: 64%

Trust-based Key Management Conglomerate ElGamal Encryption for Data Aggregation Framework in WSN using Blockchain Technology

Babu¹,

Jayalakshmi²

2021

IJACSA

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“…However, a single point of failure issue occurs, and MNs tamper the data. In [31][32][33], IoST faces the issue of internal attacks that affect the network's lifetime, scalability, and throughput. In [7], MNs broadcast false destination address, which affects the network's performance because data packets are continuously moved in the loop.…”

Section: Maliciousmentioning

confidence: 99%

Exploiting Machine Learning to Detect Malicious Nodes in Intelligent Sensor-Based Systems Using Blockchain

Sajid

Ullah

Javaid

et al. 2022

Wireless Communications and Mobile Computing

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In this paper, a blockchain-based secure routing model is proposed for the Internet of Sensor Things (IoST). The blockchain is used to register the nodes and store the data packets’ transactions. Moreover, the Proof of Authority (PoA) consensus mechanism is used in the model to avoid the extra overhead incurred due to the use of Proof of Work (PoW) consensus mechanism. Furthermore, during routing of data packets, malicious nodes can exist in the IoST network, which eavesdrop the communication. Therefore, the Genetic Algorithm-based Support Vector Machine (GA-SVM) and Genetic Algorithm-based Decision Tree (GA-DT) models are proposed for malicious node detection. After the malicious node detection, the Dijkstra algorithm is used to find the optimal routing path in the network. The simulation results show the effectiveness of the proposed model. PoA is compared with PoW in terms of the transaction cost in which PoA has consumed 30% less cost than PoW. Furthermore, without Man In The Middle (MITM) attack, GA-SVM consumes 10% less energy than with MITM attack. Moreover, without any attack, GA-SVM consumes 30% less than grayhole attack and 60% less energy than mistreatment. The results of Decision Tree (DT), Support Vector Machine (SVM), GA-DT, and GA-SVM are compared in terms of accuracy and precision. The accuracy of DT, SVM, GA-DT, and GA-SVM is 88%, 93%, 96%, and 98%, respectively. The precision of DT, SVM, GA-DT, and GA-SVM is 100%, 92%, 94%, and 96%, respectively. In addition, the Dijkstra algorithm is compared with Bellman Ford algorithm. The shortest distances calculated by Dijkstra and Bellman are 8 and 11 hops long, respectively. Also, security analysis is performed to check the smart contract’s effectiveness against attacks. Moreover, we induced three attacks: grayhole attack, mistreatment attack, and MITM attack to check the resilience of our proposed system model.

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“…Device tampering attacks also result in selective message eavesdropping attacks which acts as a base for launching other serious security attacks such as wormhole, black-hole attacks. The device tempering attacks can be avoided using various tempering proof techniques [58]- [60] proposed in the literature however require additional energy and processing costs.…”

Section: B Secure the Communication Channelmentioning

confidence: 99%

Sensor-Cloud Architecture: A Taxonomy of Security Issues in Cloud-Assisted Sensor Networks

et al. 2021

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The orchestration of cloud computing with wireless sensor network (WSN), termed as sensor-cloud has recently gained remarkable attention from both the academia and industry. It enhances the processing and storage capabilities of the resources-constrained sensor networks in various applications such as healthcare, habitat monitoring, battlefield surveillance, and disaster management etc. The diverse nature of sensor network applications imposes processing and storage limitation on the sensor networks, which can be overcome through integrating them with the cloud paradigm. Sensor-cloud offers numerous benefits such as flexibility, scalability, collaboration, automation, virtualization with enhanced processing and storage capabilities. However, these networks suffer from limited bandwidth, resources optimization, reliability, load balancing, latency , and security threats. Therefore, it is very important to secure the sensor-cloud architecture from various security attacks to preserve its integrity. The main components of the sensor-cloud architecture which can be attacked are : (i) the sensor nodes; (ii) the communication medium; and (iii) the remote cloud architecture. Although, security issues of these components are extensively studied, in the existing literature; however, a detailed analysis of various security attacks on the sensor-cloud architecture is still required. The main objective of this research is to present state-of-theart literature in the context of security issues of the sensor-cloud architecture along with their preventive measures. Moreover, several taxonomies of the security attacks from the architectural perspective of the sensor-cloud along with their innovative solutions are also provided.

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A Blockchain-Based Multi-Mobile Code-Driven Trust Mechanism for Detecting Internal Attacks in Internet of Things

Cited by 41 publications

References 70 publications

Trust-based Key Management Conglomerate ElGamal Encryption for Data Aggregation Framework in WSN using Blockchain Technology

Trust-based Key Management Conglomerate ElGamal Encryption for Data Aggregation Framework in WSN using Blockchain Technology

Exploiting Machine Learning to Detect Malicious Nodes in Intelligent Sensor-Based Systems Using Blockchain

Sensor-Cloud Architecture: A Taxonomy of Security Issues in Cloud-Assisted Sensor Networks

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