Distributed Detection of Node Capture Attacks in Wireless Sensor Networks

Ho, Jun-Won

doi:10.5772/13084

Cited by 24 publications

(20 citation statements)

References 47 publications

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“…The LSM scheme reduces the communication overhead of the RM scheme by having every claim-relaying node participate in the replica detection and revocation process. RED still has the same communication overhead as the LSM scheme [24]. …”

Section: Communication Overheadmentioning

confidence: 90%

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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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Section: Communication Overheadmentioning

confidence: 90%

“…The protocol then measures the absence time period of a sensor node and compares it to a predefined threshold. If it is more than threshold value, the sensor node considered as a captured node [24].…”

Section: Detection Of Node Capture Attack (Dnca)mentioning

confidence: 99%

Clone Attack Detection Protocols in Wireless Sensor Networks: A Survey

Anthoniraj¹,

Razak²

2014

IJCA

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“…Some works examine the possibility of detecting the compromising of nodes as soon as an opponent physically withdraws them from the network. In the method that is developed in [16], each node keeps a watch on the presence of its neighbours. The Sequential Probability Radio Test (SPRT) is used to determine a dynamic time threshold.…”

Section: Ddos and Wsnsmentioning

confidence: 99%

Predicting the Effects of DDoS Attacks on a Network of Critical Infrastructures

Hurst

Shone

Monnet

2015

2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable,

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Abstract-Over the last decade, the level of critical infrastructure technology has been steadily transforming in order to keep pace with the growing demand for the services offered. The implementation of the smart grid, which relies on a complex and intelligent level of interconnectivity, is one example of how vital amenity provision is being refined. However, with this change, the risk of threats from the digital domain must be calculated. Superior interconnectivity between infrastructures means that the future cascading impacts of successful cyberattacks are unknown. One such threat being faced in the digital domain is the Distributed Denial of Service (DDoS) attack. A DDoS has the goal of incapacitating a server, network or service, by barraging a target with external data traffic in the form of communication requests. DDoS have the potential to cause a critical infrastructure outage, and the subsequent impact on a network of such infrastructures is yet unknown. In this paper, an approach for assessing the future impacts of a cyber-attack in a network of critical infrastructures is presented; with a focus on DDoS attacks. A simulation of a critical infrastructure network provides data to represent both normal run-time and an attack scenario. Using this dataset, a technique for assessing the future impact of disruptions on integrated critical infrastructure network, is demonstrated.

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“…This is achieved using third scheme (Random Pair wise Keys Scheme). With these schemes improved resilience against node capture attacks as well as node replication can be obtained The scheme presented by [8] quickly observes compromised node through Sequential Probability Ratio Test (SPRT). The absence of captured node is found out through pre-defined threshold limit.…”

Section: Survey Of Various Detection and Key Predistribution Schemes mentioning

confidence: 99%

An Exhaustive Survey on Physical Node Capture Attack in WSN

Butani¹,

Shukla²,

Silakari³

2014

IJCA

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Node capture attack is one of the most dreadful security attack exist in wireless sensor networks. An adversary steals cryptographic key information from a captured node to compromise entire network. So, Security of wireless sensor network is an important issue for maintaining confidentiality and integrity of wireless links. Now-a-days, researchers are paying attention towards developing security schemes against Node capture attack. Our survey provides deep insights of existing modeling techniques of node capture attack in wireless sensor network. It also analyzes various detection and key predistribution schemes for inventing a new scheme to improve resilience against node capture attack..

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Distributed Detection of Node Capture Attacks in Wireless Sensor Networks

Cited by 24 publications

References 47 publications

Clone Attack Detection Protocols in Wireless Sensor Networks: A Survey

Clone Attack Detection Protocols in Wireless Sensor Networks: A Survey

Predicting the Effects of DDoS Attacks on a Network of Critical Infrastructures

An Exhaustive Survey on Physical Node Capture Attack in WSN

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