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An efficient secure detection and prevention of malevolent nodes with lightweight surprise check scheme using trusted mobile agents in mobile ad-hoc networks

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Abstract

Mobile ad-hoc networks are a type of self-configuring networks in which the node moves from one location to another without any fixed infrastructure. Providing security in mobile ad-hoc networks is a challenging task due to its frequent topology change. Protecting legitimate nodes from the malevolent nodes is an important factor. To solve this problem, we propose trusted agent-based lightweight surprise check for malevolent node detection in mobile ad-hoc networks. This scheme uses three phases: lightweight surprise check manager, cluster formation and mobile agent phase. Lightweight surprise check manager detects the malevolent node based on node forward rate, node acknowledgement, secure communication and node location. In cluster phase, the clusters are formed depending upon received signal strength and the cluster heads are elected based on the residual energy and utility of neighbors. In mobile agent phase, the secret key method is used to verify the mobile agent authentication. The mobile agent is used for data communication among cluster head to destination, thus it reduces the energy utilization, network overload, average delay as well as improve the network efficiency in the network. Simulation results shows that the lightweight surprise check scheme provides improved security and quality of service compared to the existing schemes.

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Authors and Affiliations

  1. Department of ETCE, Sathyabama Institute of Science and Technology, Chennai, India

    A. Aranganathan

  2. School of Ocean Engineering and Underwater Technology, Kerala University of Fisheries and Ocean Studies, Panangad, India

    C. D. Suriyakala

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  1. A. Aranganathan
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  2. C. D. Suriyakala
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Correspondence to A. Aranganathan.

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Aranganathan, A., Suriyakala, C.D. An efficient secure detection and prevention of malevolent nodes with lightweight surprise check scheme using trusted mobile agents in mobile ad-hoc networks. J Ambient Intell Human Comput 10, 3493–3503 (2019). https://doi.org/10.1007/s12652-018-1069-8

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  • DOI: https://doi.org/10.1007/s12652-018-1069-8

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