Formal Modeling of Security Dynamics in Sensor Networks Using Fuzzy Inference Systems

Alexander Alexandrov
Institute of Robotics – Bulgarian Academy of Sciences, Acad. Georgi Bonchev Str., Bl. 2, Sofia, 1113, Bulgaria
akalexandrov@ir.bas.bg
DOI: 10.46793/BISEC25.076A

 

ABSTRACT: The rapid expansion of distributed sensing infrastructures has introduced complex challenges in maintaining the integrity, confidentiality, and availability of sensor data. Traditional cryptographic or rule-based approaches to securing sensor networks often fail to capture the dynamic uncertainty and partial information inherent in such systems. This paper presents a formal model of security dynamics in sensor networks using a Fuzzy Inference System (FIS). The proposed model quantifies and evaluates network security levels through fuzzy variables representing node trustworthiness, data integrity, intrusion likelihood, and energy state. A mathematical framework for fuzzy membership functions and inference rules is established, leading to a formal representation of the system’s global security state as a dynamic equilibrium. Analytical evaluation demonstrates that fuzzy-based reasoning provides adaptive, interpretable, and computationally efficient security estimation. The proposed model advances theoretical foundations for self-managing, context-aware sensor networks.

KEYWORDS: Fuzzy inference systems, wireless sensor networks, WSN, information security, formal modeling, dynamic analysis.

REFERENCES:

  1. Jain, Khushboo. (2025). Exploring Cryptographic Key Management Schemes for Enhanced Security in WSNs. Journal of Information Assurance and Secu rity. 20. 18-37. 10.2478/ias-2025-0002.
  2. Sarkar, Sayani & Shafaei, Sima & Jones, Trishtanya & Totaro, Michael. (2025). Secure Communication in Drone Networks: A Comprehensive Survey of Lightweight Encryption and Key Management Techniques. Drones. 9.10.3390/drones9080583.
  3. Țălu, Mircea. (2025). DNA-Based Cryptography for Internet of Things Security: Concepts, Methods, Applications, and Emerging Trends. Buletin Ilmiah Sarjana Teknik Elektro. 68-94. 10.12928/biste.v7i2.12942.
  4. Pandey, Rashmikiran & Pandey, Mrinal & Nazarov, Alexey. (2023). Modelling the Dynamics of Information Warfare: An Attacker-Defender Scenario Using Lotka-Volterra Equations. 10.21203/rs.3.rs-3148628/v1.
  5. Joseph, Michael. (2010). Modeling attacker-defender interactions in information networks. 10.2172/1008137.
  6. Butun, Ismail & Morgera, Salvatore & Sankar, Ravi. (2013). A Survey of Intrusion Detection Systems in Wireless Sensor Networks. IEEE Communications Surveys & Tutorials. PP. 266 – 282. 10.1109/SURV.2013.050113.00191.
  7. F. Shiming, Z. Ping and S. Xuehong, “A fuzzy trust management mechanism with dynamic behavior monitoring for wireless sensor networks,” in China Communications, vol. 21, no. 5, pp. 177-189, May 2024, doi: 10.23919/JCC.fa.2022-0616.202405. keywords: {Wireless sensor networks;Monitoring;Cloud computing;Security;Wireless communication;Distributed databases;Communication system security;behavior monitoring;cloud;fuzzy;trust;wireless sensor networks}

IZVOR: Proceedings of the 16th International Conference on Business Information Security BISEC’2025