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Probabilistic intrusion detection based on an optimal strong K-barrier strategy in WSNs

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Abstract

Ensuring better surveillance of borders with K-barrier coverage type via homogeneous wireless sensor networks (WSNs) remains a challenging task to be solved urgently since it influences the lifetime of the network. The main contribution of this paper is the proposal of a strong K-barrier coverage strategy based on the scheduling of state change combinations (0/1) in the truth table. The change of node state (Active/Passive) truth tables depends on a mathematical probability formula according which it makes impossible the crossing of the barriers (intrusion probability tends towards zero). Furthermore, the proposed probabilistic interference increases the vulnerability against any type of possible intrusion in the WSN regardless of the speed of the intruder. The proposed protocol is named; K-Barrier Coverage via Probabilistic Interference of Truth-Table states in Homogeneous Sensor Network (KBC-PITT). We have shown in two ways that our strategy is optimal compared to the proposed k-barrier coverage strategies in the literature; (a) by demonstrating that the probability of barrier intrusion tends towards zero; and (b) by simulations to confirm the effectiveness of KBC-PITT in terms of perfect coverage, connectivity, and power consumption with high reliability and simple architecture. The simulation results highlight the benefits of using KBC-PITT strategy to solve the intrusion detection problem by maintaining coverage and connectivity with minimal power consumption throughout the network’s lifetime, reaching 100% of coverage, compared to other well-known strategies, namely WTBC, AND, HMB-SAA, PGSA, CHA, and QUEC.

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Author notes

  1. Cyril De Runz, Marwane Ayaida and Hisham Kholidy are authors contributed equally to this work.

Authors and Affiliations

  1. Computer Science Department, Ibn Khaldoun University, Tiaret, 14000, Algeria

    Adda Boualem

  2. LIFAT, University of Tours, Blois, F-41000, France

    Cyril De Runz

  3. UMR 8520 - IEMN, Polytechnique Hauts-de-France, CNRS, Univ. Lille, Valenciennes, F-59313, France

    Marwane Ayaida

  4. CReSTIC EA 3804, Université de Reims Champagne Ardenne, Reims, 51097, France

    Marwane Ayaida

  5. State University of New York Polytechnic Institue, College of Engineering, New York, USA

    Hisham Kholidy

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  1. Adda Boualem
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All authors have participated in (a) conception and design, or analysis and interpretation of the data; (b) drafting the article or revising it critically for important intellectual content; and (c) approval of the final version.

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Boualem, A., De Runz, C., Ayaida, M. et al. Probabilistic intrusion detection based on an optimal strong K-barrier strategy in WSNs. Peer-to-Peer Netw. Appl. 17, 1190–1207 (2024). https://doi.org/10.1007/s12083-024-01634-w

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