Smaclad: Secure Mobile Agent Based Cross Layer Attack Detection and Mitigation in Wireless Network

Nithya, S.; Gomathy, C.

doi:10.1007/s11036-018-1201-1

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…As a third example, to detect and mitigate the cross-layer attacks that utilize manipulating and jamming process, there is a new method which is based on Bayesian learning model to meet the security requirements of the applications of WSNs and has an acceptable performance. 86 Some other works proposed different MA-based key management methods to meet the military applications in the WSNs. 87 Tables 1 and 2 illustrate the comparison of the performance parameters about the multiagent-based simulated approaches in the WSNs.…”

Section: Simulated Approachesmentioning

confidence: 99%

A review on the applications of multiagent systems in wireless sensor networks

Derakhshan

Yousefi

2019

International Journal of Distributed Sensor Networks

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Nowadays, the efficiency of multiagent systems in wireless sensor networks prompts the researchers to use these emerging mobile software packets in different simulated approaches or real-world applications. Heterogeneous and distributed wireless sensor networks could be integrated with the multiagent systems to map the real-world challenges into the artificial intelligence world. The multiagent systems have been applied from simulated approaches like object detection/ tracking, healthcare, control/assistant, and security systems to real-world applications, including medical/human-care systems and unmanned aerial vehicles. Furthermore, the integration of wireless sensor networks with multiagent systems have emerged novel application, which is known as mobile robots. However, the extensive use of mobile agents in wireless sensor networks has posed different challenges for researchers, including security, resource, and timing limitation. In this work, we review recent simulated approaches and real-world applications of multiagent systems in wireless sensor networks, in which a set of common factors about the things that have been studied are extracted and compared to analyze the performance of mobile agent-based systems in the wireless sensor networks, as well. This analysis provides new research directions about multiagent systems in wireless sensor networks for interested researchers. Finally, a novel framework for dealing with the challenges of multiagent-based applications in the wireless sensor networks which have been mentioned is suggested.

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Section: Simulated Approachesmentioning

confidence: 99%

A review on the applications of multiagent systems in wireless sensor networks

Derakhshan

Yousefi

2019

International Journal of Distributed Sensor Networks

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“…A Bayesian detection scheme for physical layer attacks is proposed by Nithya et al [ 28 ]. Their method determines the probability of a physical and MAC layer attack considering the packet delivery and receiving rate, the channel contention activity, and the packet delivery delay.…”

Section: Introductionmentioning

confidence: 99%

A Low-Cost Jamming Detection Approach Using Performance Metrics in Cluster-Based Wireless Sensor Networks

Del-Valle-Soto

Mex-Perera

Nolazco-Flores

et al. 2021

Sensors

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Wireless Sensor Networks constitute an important part of the Internet of Things, and in a similar way to other wireless technologies, seek competitiveness concerning savings in energy consumption and information availability. These devices (sensors) are typically battery operated and distributed throughout a scenario of particular interest. However, they are prone to interference attacks which we know as jamming. The detection of anomalous behavior in the network is a subject of study where the routing protocol and the nodes increase power consumption, which is detrimental to the network’s performance. In this work, a simple jamming detection algorithm is proposed based on an exhaustive study of performance metrics related to the routing protocol and a significant impact on node energy. With this approach, the proposed algorithm detects areas of affected nodes with minimal energy expenditure. Detection is evaluated for four known cluster-based protocols: PEGASIS, TEEN, LEACH, and HPAR. The experiments analyze the protocols’ performance through the metrics chosen for a jamming detection algorithm. Finally, we conducted real experimentation with the best performing wireless protocols currently used, such as Zigbee and LoRa.

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Enhancing Fault Tolerance in Wireless Mesh Networks through Adaptive and Resilient Routing Protocols

Caleb,

Thangaraj

2023

2023 International Conference on Data Science, Agents &Amp; Artificial Intelligence (ICDSAAI)

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Smaclad: Secure Mobile Agent Based Cross Layer Attack Detection and Mitigation in Wireless Network

Cited by 4 publications

References 13 publications

A review on the applications of multiagent systems in wireless sensor networks

A review on the applications of multiagent systems in wireless sensor networks

A Low-Cost Jamming Detection Approach Using Performance Metrics in Cluster-Based Wireless Sensor Networks

Enhancing Fault Tolerance in Wireless Mesh Networks through Adaptive and Resilient Routing Protocols

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