The Efficacy of Epidemic Algorithms on Detecting Node Replicas in Wireless Sensor Networks

Abstract

A node replication attack against a wireless sensor network involves surreptitious efforts by an adversary to insert duplicate sensor nodes into the network while avoiding detection. Due to the lack of tamper-resistant hardware and the low cost of sensor nodes, launching replication attacks takes little effort to carry out. Naturally, detecting these replica nodes is a very important task and has been studied extensively. In this paper, we propose a novel distributed, randomized sensor duplicate detection algorithm called Discard to detect node replicas in group-deployed wireless sensor networks. Our protocol is an epidemic, self-organizing duplicate detection scheme, which exhibits emergent properties. Epidemic schemes have found diverse applications in distributed computing: load balancing, topology management, audio and video streaming, computing aggregate functions, failure detection, network and resource monitoring, to name a few. To the best of our knowledge, our algorithm is the first attempt at exploring the potential of this paradigm to detect replicas in a wireless sensor network. Through analysis and simulation, we show that our scheme achieves robust replica detection with substantially lower communication, computational and storage requirements than prior schemes in the literature.

A Clone Detection Algorithm with Low Resource Expenditure for Wireless Sensor Networks

“…Clone attacks have attracted the attention of researchers, and there has been much effort on clone detection up to now [5][6][7][8][9][10][11][12][13][14][15][16][17][18]. According to different features, we could classify them into different categories: centralized [12][13][14][15] or distributed [5][6][7][8][9][10][11][16][17][18], witness-based [5,[8][9][10][11][16][17][18] or not, position dependent [5, 8-11, 17, 18] or not, and the scheme is for randomly deployed [5][6][7][8][9][10][11][12][13][14][15][16] or group-deployed networks…”

“…However, the shortcomings are also explicit: the BS easily suffers from a single point of failure and the nodes around the BS consume much more energy than others due to forwarding packets. In order to solve these problems, distributed schemes are proposed [5][6][7][8][9][10][11][16][17][18], which assign the detection tasks to different areas and nodes, yet the resource consumptions of nodes are increasing sharply. Most of the works are conducted to balance the detection probability and the resource expenditure.…”

Detection of Node Capture under Asynchronous Sleep Mode Based on Recurrent Neural Network

“…In practical applications, sensor nodes are usually deployed in a harsh open environment, often lacking necessary physical protection. Moreover, the networks are generally not equipped with physical tamper-proof devices due to cost constraints [5] . Therefore, the open nature of their environment and wireless communication expose the nodes to various security threats.…”

“…Most techniques proposed in the literature are intended for detection in the second and third stages. Such techniques include, for example, node redeployment location detection [9] , node clone detection [5,10] , selective forwarding attack detection [11] , black hole attack detection [12] , witch attack detection [13] , Denial of Service attack detection, and malicious data injection detection [14] . Node capture should be detected as soon as possible to reduce the damage caused by the captured nodes to the network.…”