Replication attack detection with monitor nodes in clustered wireless sensor networks

Guo, Cheng; Guo, Songtao; Yang, Yuanyuan; Wang, Fei

doi:10.1109/pccc.2015.7410341

Cited by 11 publications

(5 citation statements)

References 23 publications

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“…High and successful detection probability is the most significant performance metric for any clone detection protocol. However, most of the proposed clone detection protocols suffer from low detection probability with high cost in terms of communication and memory [29], [33], [36], [38], [41], [56], [58]. This study concludes that ''Detection Probability'', with a frequency of 20.59%, can be regarded as the third-significant challenge in the clone node detection mechanism.…”

Section: ) Detection Probabilitymentioning

confidence: 89%

A Systematic Review on Clone Node Detection in Static Wireless Sensor Networks

et al. 2020

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The recent state of the art innovations in technology enables the development of low-cost sensor nodes with processing and communication capabilities. The unique characteristics of these low-cost sensor nodes such as limited resources in terms of processing, memory, battery, and lack of tamper resistance hardware make them susceptible to clone node or node replication attack. The deployment of WSNs in the remote and harsh environment helps the adversary to capture the legitimate node and extract the stored credential information such as ID which can be easily reprogrammed and replicated. Thus, the adversary would be able to control the whole network internally and carry out the same functions as that of the legitimate nodes. This is the main motivation of researchers to design enhanced detection protocols for clone attacks. Hence, in this paper, we have presented a systematic literature review of existing clone node detection schemes. We have also provided the theoretical and analytical survey of the existing centralized and distributed schemes for the detection of clone nodes in static WSNs with their drawbacks and challenges. INDEX TERMS Wireless sensor networks (WSNs), clone attack, clone attack detection schemes, systematic literature review (SLR).

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Section: ) Detection Probabilitymentioning

confidence: 89%

A Systematic Review on Clone Node Detection in Static Wireless Sensor Networks

et al. 2020

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“…Khedim et al [25] proposed a protocol that aims to mitigate the independence of the GPS and beacon node. MCD refers to a hybrid protocol that uses patrol robots and honeypots for detecting replicated nodes in a static sensor network, but this method needs more deployment cost as the hardware included is highly expensive.…”

Section: Related Workmentioning

confidence: 99%

Deployment with Location Knowledge by Multi Area Approach for Detecting Replica Nodes in Wireless Sensor Network

2024

Teh. vjesn.

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The Wireless Sensor Network (WSN) is important for the safety of network security. Numerous scholars have documented fundamentally fundamental attacks of various kinds in the WSN up to now. Replica nodes are identified using a range of replica node identification techniques. Although the replica is certain as a witness node, these approaches have poor detection precision and incur overhead control. This paper looks at the Multi Area Method (MAA) Replica Identification with Deployment with Location Knowledge (DLK) used. Initially, the nodes are clustered together and routed via the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. Several forms of node duplication identification protocols have now been proposed. Moreover, a single failure point located in clustered protocols, dispersed replications, is never identified by local protocols. Geographical positions are identified by the distributed protocols needed for the nodes. Deployment information utilising the position cluster detection method is suggested to avoid a node replica strike. Based on the deployment performance, the suggested model is compared to Area Based Cluster move towards (ABCD) and Fingerprint-based detection techniques. The proposed methodology offers excellent performance compared with other standard methods. Moreover, the energy consumption for RN detection was only 34 kWh.The proposed work provides optimal results for existing attacking strategies in cases of high detection higher detection percentage with a minimized Delay and increased communication overhead.

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“…Attackers can also impersonate network nodes by counterfeiting, and conceal legitimate users to execute unauthorized operations. The active attacks include jamming attack [15], denial of service attack, black hole attack [16], tampering attack, wormhole attack [17], selective forwarding, identity replication/cloning attack [18], Sybil attack [19], etc. The passive attack is difficult to detect for the simple reason that the attacker only monitors the transmitted data without modifying the message.…”

Section: Security Threat In Clustered Wireless Sensor Networkmentioning

confidence: 99%