Skip to main content
SpringerLink
Log in

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

  • Published:
Peer-to-Peer Networking and Applications Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

Data availibility

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

References

  1. Barati H, Movaghar A, Barati A et al (2008) A review of coverage and routing for wireless sensor networks. Int J Electron Commun Eng 2(1):67–73

    Google Scholar 

  2. Boualem A (2021) Stratégies d’amélioration de la couverture dans les réseaux de capteurs sans fil. These de doctorat en informatique, école supérieur d’informtique, ESI, Alger, Algerien

  3. Han R, Yang W, Zhang L (2018) Achieving crossed strong barrier coverage in wireless sensor network. Sensors 18(2):534. https://doi.org/10.3390/s18020534

    Article  PubMed  PubMed Central  Google Scholar 

  4. Saraereh OA, Ali A, Al-Tarawneh L et al (2021) A robust approach for barrier-reinforcing in wireless sensor networks. J Parallel Distrib Comput 149:186–192. https://doi.org/10.1016/j.jpdc.2020.12.007

    Article  Google Scholar 

  5. Chowdary V, Deogharia D, Sowrabh S et al (2022) Forest fire detection system using barrier coverage in wireless sensor networks. Mater Today Proc 64:1322–1327. https://doi.org/10.1016/j.matpr.2022.04.202

    Article  Google Scholar 

  6. Mini, Pal A, Thakur G (2023) k-coverage probability assessment of wireless sensor networks with boolean and elfes models. Mater Today Proc. https://doi.org/10.1016/j.matpr.2023.03.049

  7. Boualem A, Taibi D, Ammar A (2023) Linear and non-linear barrier coverage in deterministic and uncertain environment in wsns: A new classification. CoRR abs/2306.12355. https://doi.org/10.48550/arXiv.2306.12355

  8. Boualem A, Fouchal H, Ayaida M et al (2022) Fibonacci tiles strategy for optimal coverage in IoT networks. Ann Telecommun 77(5–6):331–344. https://doi.org/10.1007/s12243-021-00890-8

    Article  Google Scholar 

  9. Luo Q, Liu C, Yan X et al (2022) A distributed localization method for wireless sensor networks based on anchor node optimal selection and particle filter. Sensors 22(3):1003. https://doi.org/10.3390/s22031003

    Article  PubMed  PubMed Central  Google Scholar 

  10. Papi F, Barati H (2022) HDRM: A hole detection and recovery method in wireless sensor network. Int J Commun Syst 35(8). https://doi.org/10.1002/dac.5120

  11. Boualem A, Runz CD, Ayaida M et al (2023) A fuzzy/possibility approach for area coverage in wireless sensor networks. Soft Computing 27(14):9367–9382. https://doi.org/10.1007/s00500-023-08406-3

    Article  Google Scholar 

  12. Singh A, Amutha J, Nagar J et al (2023) A deep learning approach to predict the number of k-barriers for intrusion detection over a circular region using wireless sensor networks. Expert Syst Appl 211(118):588. https://doi.org/10.1016/j.eswa.2022.118588

    Article  Google Scholar 

  13. Mulligan R, Ammari HM (2010) Coverage in wireless sensor networks: A survey. Netw Protocols Algo 2(2):27–53

    Google Scholar 

  14. Boulis A, Jha S (2005) Network management in new realms: wireless sensor networks. Int J Netw Manag 15(4):219–221. https://doi.org/10.1002/nem.569

    Article  Google Scholar 

  15. Hallafi A, Barati A, Barati H (2022) A distributed energy-efficient coverage holes detection and recovery method in wireless sensor networks using the grasshopper optimization algorithm. J Ambient Intell Humaniz Comput 14(10):13697–13711. https://doi.org/10.1007/s12652-022-04024-3

  16. Balister P, Bollobas B, Sarkar A et al (2007) Reliable density estimates for coverage and connectivity in thin strips of finite length. In: Proceedings of the 13th Annual ACM International Conference on Mobile Computing and Networking. ACM, New York, NY, USA, MobiCom ’07, pp 75–86, https://doi.org/10.1145/1287853.1287863

  17. Sharma S, Nagar J (2020) Intrusion detection in mobile sensor networks: A case study for different intrusion paths. Int J Wirel Pers Commun 115(3):2569–2589. https://doi.org/10.1007/s11277-020-07697-1

    Article  Google Scholar 

  18. Chen B, Jamieson K, Balakrishnan H et al (2002) Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks. Wirel Netw 8(5):481–494. https://doi.org/10.1023/A:1016542229220

    Article  Google Scholar 

  19. Wang Q, Wang L, Zhou R et al (2011) An Approach of K-Barrier Coverage of WSN for Mine, vol 4, Springer Berlin Heidelberg, pp 295–302. https://doi.org/10.1007/978-3-642-21762-3_38

  20. Suzuki T, Yamamoto K, Koyamashita H et al (2012) Wave-type barrier coverage for border security in wireless sensor networks. In: Computing and Convergence Technology (ICCCT), 2012 7th International Conference on. ICCCT, pp 78–83

  21. Dezfouli NN, Barati H (2018) A distributed energy-efficient approach for hole repair in wireless sensor networks. Wirel Netw 26(3):1839–1855. https://doi.org/10.1007/s11276-018-1867-0

    Article  Google Scholar 

  22. Boualem A, Ayaida M, Runz CD (2021) Semi-deterministic deployment based area coverage optimization in mobile WSN. In, (2021) IEEE Global Communications Conference (GLOBECOM). IEEE. https://doi.org/10.1109/globecom46510.2021.9685760

  23. Cheng CF, Hsu CC, Pan MS et al (2022) A cluster-based barrier construction algorithm in mobile wireless sensor networks. Phys Commun 54:1–9. https://doi.org/10.1016/j.phycom.2022.101839

    Article  Google Scholar 

  24. Federica F, Talignani LC, Silvia C et al (2019) Safety barrier functions and multi-camera tracking for human-robot shared environment. Wirel Commun Mob Comput, pp 1–57. Robotics and Autonomous Systems

  25. Chen J, Yang LT, Deng X et al (2020) Optimal receiver placement for k-barrier coverage in passive bistatic radar sensor networks. ACM Trans Internet Technol 20(3):1–23. https://doi.org/10.1145/3377402

    Article  CAS  Google Scholar 

  26. Chang J, Shen X, Bai W et al (2019) Hierarchy graph based barrier coverage strategy with a minimum number of sensors for underwater sensor networks. Sensors 19(11):1–21. https://doi.org/10.3390/s19112546

    Article  Google Scholar 

  27. Mortazavi MG, Shirvani MH, Dana A et al (2023) Sleep-wakeup scheduling algorithm for lifespan maximization of directional sensor networks: a discrete cuckoo search optimization algorithm. Complex Intell Syst. https://doi.org/10.1007/s40747-023-01078-4

  28. Khanjary M, Sabaei M, Meybodi MR (2017) Critical density in adjustable-orientation directional sensor networks using continuum percolation. Proc Comput Sci 116:548–555. https://doi.org/10.1016/j.procs.2017.10.054

    Article  Google Scholar 

  29. Jiao W, Tang R, Xu Y (2022) A coverage optimization algorithm for the wireless sensor network with random deployment by using an improved flower pollination algorithm. Forests 13:1–16. https://doi.org/10.3390/f13101690

    Article  Google Scholar 

  30. DeWitt J, Shi H (2017) Barrier coverage in energy harvesting sensor networks. Ad Hoc Netw 56(1):72–83. https://doi.org/10.1016/j.adhoc.2016.11.014

    Article  Google Scholar 

  31. Ghahroudi MS, Shahrabi A, Ghoreyshi SM et al (2023) Distributed node deployment algorithms in mobile wireless sensor networks: Survey and challenges. ACM Trans Sens Netw 19(4):1–26. https://doi.org/10.1145/3579034

    Article  Google Scholar 

  32. My BNT, Binh HTT, Le LV et al (2019) An efficient approximate algorithm for achieving \((k - \omega )\) barrier coverage in camera wireless sensor networks. In: Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications. SPIE, https://doi.org/10.1117/12.2519272

  33. Liu Z, Jiang G (2021) Sensor parameter estimation for full-view coverage of camera sensor networks based on bounded convex region deployment. IEEE Access 9:97,129–97,137. https://doi.org/10.1109/access.2021.3095063

  34. Hong Y, Luo C, Li D et al (2022) Lifetime-maximized strong barrier coverage of 3d camera sensor networks. Wirel Commun Mob Comput 2022:1–12. https://doi.org/10.1155/2022/2659901

    Article  Google Scholar 

  35. Ruisong WYH, Zhang L (2018) Achieving crossed strong barrier coverage in wireless sensor network. Sensors 18(534):1–17. https://doi.org/10.3390/s18020534

    Article  Google Scholar 

  36. Zhao L, Bai G, Shen H et al (2018) Strong barrier coverage of directional sensor networks with mobile sensors. Int J Distrib Sens Netw 14(2):1–11. https://doi.org/10.1177/1550147718761582

    Article  Google Scholar 

  37. Mostafaei H, Chowdhury MU, Obaidat MS (2018) Border surveillance with wsn systems in a distributed manner. IEEE Syst J 12(4):3703–3712

    Article  Google Scholar 

  38. Fan XG, Che ZC, Hu FD et al (2020) Deploy efficiency driven k-barrier construction scheme based on target circle in directional sensor network. J Comput Sci Technol 35(3):647–664. https://doi.org/10.1007/s11390-020-9210-5

    Article  Google Scholar 

  39. Yu Z, Chi K, Hu P et al (2019) Energy provision minimization in wireless powered communication networks with node throughput requirement. IEEE Trans Veh Technol 68(7):7057–7070. https://doi.org/10.1109/tvt.2019.2917947

    Article  Google Scholar 

  40. Bonnah E, Ju S, Cai W (2020) Coverage maximization in wireless sensor networks using minimal exposure path and particle swarm optimization. Sens Imaging 21(4)

  41. Liu Z, Zhou W (2023) Energy-efficient algorithms for path coverage in sensor networks. Sensors 23(11):5026. https://doi.org/10.3390/s23115026

    Article  PubMed  PubMed Central  Google Scholar 

  42. Boualem A, Dahmani Y, Maatoug A (2017) Energetic sleep- scheduling via probabilistic interference k-barrier coverage with truth-table technique in sensor network. In: International Conference on Mathematics and information Technology. IEEE, Adrar, Algeria, pp 255–262, https://doi.org/10.1109/MATHIT.2017.8259726

  43. Fan XG, Che ZC, Hu FD et al (2020) Deploy efficiency driven k-barrier construction scheme based on target circle in directional sensor network. J Comput Sci Technol 35(3):647–66. https://doi.org/10.1007/s11390-020-9210-5

    Article  Google Scholar 

  44. Chi K, Zhu YH, Li Y et al (2017) Minimization of transmission completion time in wireless powered communication networks. IEEE Internet Things J 4(5):1671–1683. https://doi.org/10.1109/JIOT.2017.2689777

    Article  Google Scholar 

  45. Yakıcı E, Karatas M (2021) Solving a multi-objective heterogeneous sensor network location problem with genetic algorithm. Comput Netw 192(108):041. https://doi.org/10.1016/j.comnet.2021.108041

    Article  Google Scholar 

  46. Boualem A, Dahmani Y, Runz CD et al (2019) Spiderweb strategy: application for area coverage with mobile sensor nodes in 3d wireless sensor network. Int J Sens Netw 29(2):121. https://doi.org/10.1504/ijsnet.2019.097808

    Article  Google Scholar 

  47. Sun Z, Li C, Xing X et al (2017) k-degree coverage algorithm based on optimization nodes deployment in wireless sensor networks. Int J Distrib Sens Netw 13(2):1–16. https://doi.org/10.1177/1550147717693242

    Article  Google Scholar 

  48. Shen W, Zhang C, Sh J (2019) Weak k-barrier coverage problem in underwater wireless sensor networks. Mob Netw App, pp 1–16. https://doi.org/10.1007/s11036-019-01273-z

  49. Zhang Y, Sun X, Yu Z (2017) Solving k-barrier coverage problem using modified gravitational search algorithm. Hindawi, Mathematical Problems in Engineering p 12. https://doi.org/10.1155/2017/1206129

  50. Li L, Chen H (2022) Uav enhanced target-barrier coverage algorithm for wireless sensor networks based on reinforcement learning. Sensors 2(22):1–16. https://doi.org/10.3390/s22176381

    Article  CAS  Google Scholar 

  51. Tian D (2004) Node activity scheduling schemes in large-scale wireless sensor networks. Phd thesis: Site, University of Ottawa

Download references

Funding

This research was not funded.

Author information

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

Authors
  1. Adda Boualem
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Cyril De Runz
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marwane Ayaida
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hisham Kholidy
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

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.

Corresponding author

Correspondence to Adda Boualem.

Ethics declarations

Ethical approval

This article does not contain any study with human or animals performed by any of the authors.

Consent to publish

The authors give the publisher permission to publish the work.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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. (2024). https://doi.org/10.1007/s12083-024-01634-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12083-024-01634-w

Keywords

Search

Navigation