Abstract
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.
Highlights
The wireless sensor networks (WSNs) play a vital role in the Internet of Sensor Things (IoST)
The proposed model uses Genetic Algorithm-based Support Vector Machine (GA-Support Vector Machine (SVM)) for classification, and it has 98% accuracy, which is higher than Decision Tree (DT), SVM, and Genetic Algorithm-based Decision Tree (GA-DT) because SVM’s accuracy is greater than DT’s accuracy
Registration is performed for the unauthenticated nodes, which can prove harmful for the network
Summary
The wireless sensor networks (WSNs) play a vital role in the Internet of Sensor Things (IoST). IoST is an emerging domain, which supports different applications like industrial Internet of Things (IoT), smart cities, air pollution detection, and underwater monitoring. These networks face well-known issues due to deployment in harsh and unattended environments like attackers can attack the network by compromising the sensor nodes, which have very sensitive information like identification (ID) and location [3, 4]. The credentials are used in different cryptographic functions like encryption and decryption for Wireless Communications and Mobile Computing generating cipher text. These credentials are misused by physically accessing the nodes. As the systems are controlled by a centralized authority, it is easy to be manipulated, which can lead to trust issues
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
