Random-walk based approach to detect clone attacks in wireless sensor networks

Zeng, Yingpei; Cao, Jiannong; Zhang, Shigeng; Guo, Shanqing; Xie, Lihua

doi:10.1109/jsac.2010.100606

Cited by 107 publications

(105 citation statements)

References 29 publications

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“…If any witness receives different location claims for a same node ID. This will result in the detection of the replicated node [23].…”

Section: Random Walk Based Protocols 4291 Random Walk (Rawl)mentioning

confidence: 99%

“…Then if any entry is found, the node will compute the digest of the claim and compare the digest with the digest in the entry. When two digest are different, the node detects a clone attack [23].…”

Section: Table Assisted Random Walk (Trawl)mentioning

confidence: 99%

“…RAWL starts several random walks randomly in the network for each node a. Then it selects the passed nodes as the witness nodes of node a [23]. In NBDS, the neighbors of a rejoining node correspond to the reporters, while the previous neighbors play the role of witnesses [28].…”

Section: Witness Node Selectionmentioning

confidence: 99%

“…In XED only constant communication cost is required for replica detection. The communication overheads of RAWL, TRAWL, protocols are higher than LSM [23]. Table 4 represents communication costs used in various distributed clone attack detection protocols.…”

Section: Communication Overheadmentioning

confidence: 99%

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Clone Attack Detection Protocols in Wireless Sensor Networks: A Survey

Anthoniraj¹,

Razak²

2014

IJCA

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Wireless Sensor Network (WSN) is a collection of autonomous sensor nodes which are low cost hardware components consists of sensor nodes with constraints on battery life, memory size and computation capabilities to monitor physical (or) environmental conditions. WSN is deployed in unattended and unsecure environments, so it is vulnerable to various types of attacks. One of the physical attacks is node replication attack (or) clone attack. An adversary can easily capture one node from the network and extract information from captured node. Then reprogram it to create a clone of a captured node. Then these clones can be deployed in all network areas, they can be considered as legitimate members of the network, so it is difficult to detect a replicated node. WSN can be either static (or) mobile, in that centralized and distributed clone attack detection methods are available. In this paper we analysis various centralized and distributed protocols in the static and mobile environments. We review these protocols and compare their performance with the help of witness selection, communication and memory overhead, detection probability of replicated nodes, resilience against adversary's node compromise. General TermsClone attack, Clone attack detection approach, Static nodes, and Mobile nodes.

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“…If any witness receives different location claims for a same node ID. This will result in the detection of the replicated node [23].…”

Section: Random Walk Based Protocols 4291 Random Walk (Rawl)mentioning

confidence: 99%

Section: Table Assisted Random Walk (Trawl)mentioning

confidence: 99%

Section: Witness Node Selectionmentioning

confidence: 99%

Section: Communication Overheadmentioning

confidence: 99%

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Clone Attack Detection Protocols in Wireless Sensor Networks: A Survey

Anthoniraj¹,

Razak²

2014

IJCA

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“…It achieves higher detection rates and lower storage overheads than the line-selected multicast scheme of [6]. Zeng et al [10] proposed a random-walk based replica node detection scheme. This scheme uses random walks as the distribution mechanism of location claims in the network.…”

Section: Related Workmentioning

confidence: 99%

Sequential Hypothesis Testing Based Approach for Replica Cluster Detection in Wireless Sensor Networks

2012

JSAN

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In wireless sensor networks, replica node attacks are very dangerous because the attacker can compromise a single node and generate as many replicas of the compromised node as he wants, and then exploit these replicas to disrupt the normal operations of sensor networks. Several schemes have been proposed to detect replica node attacks in sensor networks. Although these schemes are capable of detecting replicas that are widely spread in the network, they will likely fail to detect replica cluster attacks in which replicas form a cluster in a small region. These attacks are also harmful because the attacker can leverage a replica cluster to harmfully impact on the much of the network. To defend against replica cluster attacks, we propose an efficient and effective replica cluster detection scheme using the Sequential Hypothesis Testing. We evaluate our proposed scheme through analysis and simulation. The evaluation results demonstrate that it accomplishes robust replica cluster detection capability.

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