Capacity trust assessment for multi-hop routing in wireless sensor networks

E3S Web of Conferences, Jan 2023

This paper proposed a newIntrusion Detection mechanism based on Multiple Trust Attributes in Wireless Sensor Networks (WSNs). Mainly this work concentrated to assess the trust in ems of capacities of the sensor nodes. The capacity of a node is formulated based on two trusts namely Fault Tolerance Trust and Stability Trust. Every SN checks the trustworthiness of its neighbour SNs based on the Capacity Trust and confirms their trustworthiness. If any node is discovered as malicious, such type of node is called as intrusion or outlier and isolated from network.Extensive Simulations are conducted over the proposed intrusion detection mechanism and the performance is evaluated through Malicious Detection Rate, and False Positive Rate.

Capacity trust assessment for multi-hop routing in wireless sensor networks

E3S Web of Conferences 391, 01181 (2023) ICMED-ICMPC 2023 https://doi.org/10.1051/e3sconf/202339101181 Capacity trust assessment for multi-hop routing in wireless sensor networks Sowmya Gali 1*, Madhusudhana Reddy Y 2, Alekya Himabindu B1, Nagamani V1, Jayamangala S1, Munawwar S1, Mallikarjuna Rao Y1, A. Hussien Abbas3 1 ECE Department, Santhiram Engineering College, Nandyal, Andhra Pradesh, INDIA 2 ECE Department, RGM College of Engineering and Technology, Nandyal, Andhra Pradesh, INDIA 3 Computer Technical Engineering Department, College of Technical Engineering, The Islamic University, Najaf, Iraq Abstract: This paper proposed a newIntrusion Detection mechanism based on Multiple Trust Attributes in Wireless Sensor Networks (WSNs). Mainly this work concentrated to assess the trust in ems of capacities of the sensor nodes. The capacity of a node is formulated based on two trusts namely Fault Tolerance Trust and Stability Trust. Every SN checks the trustworthiness of its neighbour SNs based on the Capacity Trust and confirms their trustworthiness. If any node is discovered as malicious, such type of node is called as intrusion or outlier and isolated from network.Extensive Simulations are conducted over the proposed intrusion detection mechanism and the performance is evaluated through Malicious Detection Rate, and False Positive Rate. Keywords: Intrusion Detection, Capacity Trust, Stability Trust, Malicious Detection Rate. 1 Introduction WSNs are increasingly witnessing novel applications in diverse fields [1], [2]. Many of these are futurist in nature, although a large proportion of these are currently in use. Even though there is a huge prospect for WSNs in real time applications, many challenges like inter-operability, resource constraints, scalability, mobility, privacy and security are raised during the connection of sensor nodes. Many different type of architectures are developed for WSNs [3] to provide the solutions for these challenges. Major challenges are solved by changing the architectures except security and privacy. So, this security posing great hurdle to WSN architectures. As a result, there are numerous possible security and privacy issues, from the internet to the real world, and there is a chance that people could be harmed. For example, a compromised sensor node may lead to attack on the other nodes or on the entire network.A compromised node may potentially enable the leaking and misuse of personal information, depending on the attack method. Ύ  Corresponding author:  © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/). E3S Web of Conferences 391, 01181 (2023) ICMED-ICMPC 2023 https://doi.org/10.1051/e3sconf/202339101181 A communication breakdown may have an impact on the outside world and put people's physical safety at danger. Since the WSN is a more prone to several security threats, there is a necessity of an efficient routing design such that the Sensor Nodes in WSN will get protected. Once any of the node is compromised in network, it consequences to several problems such as information loss, control over the connected devices, hacking etc. A serious communication between two sensor nodes can be hacked easily if it is going on through free communication channel because of so many adversaries. A more serious concern in the WSN is that the attacked nodes starts misbehaving and can drop the packets or can manipulate the packets. Due to the nature of openness of transmission and deployment, the WSN suffer from several serious attacks like sink-hole, black-hole, wormhole, replay, Distributed Denial of Service (DDOS), Sybil selective forwarding, DoS, data tampering, hijack attacks. Thus there is a necessary to design an effective security framework to make the IoT more secure and resilient to all these attacks.Since the WSN is an infrastructure less network, for data transmission to base station, the sensor nodes look for the service of remaining nodes for an information transfer and effective communication [4]. Due to this co-operative nature, the WSN has become vulnerable to several types of security threats. 1.1 Problem Identified: In the WSN, the interconnected sensor nodes are heterogeneous in nature and every node has its own aspects by which they can be compromised more easily. Design of a trust based security framework just by considering few aspects makes the WSN network less resilient to different attacks. For example, if the trust design is addressed towards the tampering attacks, then the network can be compromised through remaining attacks like DoS attack, sinkhole attacks etc. To achieve more resilience towards different types of attacks in WSNs, this work proposes a new intrusion detection mechanism based multiple attributes. Under this objective, multiple trust metrics are combined together to help the node in the selection of a more trustworthy next hop node. Trust evaluation based on capacity of node, called as Capacity Trust (CT). Under the capacity trust, we have considered two more trust metrics; they are fault tolerance trust and stability trust. Rest of the paper is organized as follows; section II explores the details of literature survey. Section III explores the details of proposed methodology. Section IV explores the results and section V concludes the paper. 2 Related work S.M. Sajjad et al., [6] focused only on the detection of Selective forwarding attack, Jamming attack and Hello Flood attack. Towards such detection, the authors considered two metrics; they are Received Signal Strength (RSS) and Packet Forwarding Rate (PFR) and every node measures the trustworthiness based on these two factors. Based on the obtained trust, the nodes are declared as trustworthy, malicious or risky. The PFR metric is much effective but not RSS, because for maximum number of attacks, the data rate will vary but not RSS. However, without the consideration of interactions, the trust evaluation is inefficient. 2 E3S Web of Conferences 391, 01181 (2023) ICMED-ICMPC 2023 https://doi.org/10.1051/e3sconf/202339101181 A “Trust Based Adaptive Acknowledgment (TRAACK)” is proposed by G. Rajeshkumar and K. R. Valluvan [7] in which the trust of a node is evaluated based on Kalman filter and Successful packet deliveries. Based on the entire trust of a route, an acknowledgment is initiated for the selection of packets such that the control overhead will get reduced. However, the only successful packet deliveries are not sufficient for intrusion detection. Non-successful packet deliveries have more significance in the detection of several attacks, because for DoS attack there exists more number of successful packet deliveries. F. Shang et al. [5] proposed Cumulative Summation based Hybrid Intrusion Detection model for the detection of sink hole attack and Dos Attacks in WSN. This approach (...truncated)


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Gali Sowmya, Y. Madhusudhana Reddy, B. Alekya Himabindu, V. Nagamani, S. Jayamangala, S. Munawwar, Y. Mallikarjuna Rao, Abbas A. Hussien. Capacity trust assessment for multi-hop routing in wireless sensor networks, E3S Web of Conferences, 2023, pp. 01181, Issue 391, DOI: 10.1051/e3sconf/202339101181