After decades of deploying cyber-security systems, it has become a well-known fact that the existing cyber-security architecture has numerous inherent limitations that make the maintenance of the current network security devices unscalable and provide the adversary with asymmetric advantages. These limitations include: (1) difficulty in obtaining the global network picture due to lack of mutual interactions among heterogeneous network devices, (2) poor device self-awareness in current architectures, (3) error-prone and time consuming manual configuration which is not effective in real-time attack mitigation, (4) inability to diagnose misconfiguration and conflict resolution due to multi-party management of security infrastructure. In this paper, as an initial step to deal with these issues, we present a novel bio-inspired auto-resilient security architecture. The main contribution of this paper includes: (1) investigation of laws governing the dynamics of correct feedback control in Biological Regulatory Networks (BRNs), (2) studying their applicability for synthesizing correct models for bio-inspired communication networks, i.e. Firewall Regulatory Networks (FRNs), (3) verification of the formal models of real network scenarios, to prove the correctness of the proposed approach through model checking techniques.
CITATION STYLE
Rauf, U., Mohsin, M., & Mazurczyk, W. (2019). Cyber regulatory networks: Towards a bio-inspired auto-resilient framework for cyber-defense. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 289, pp. 156–174). Springer Verlag. https://doi.org/10.1007/978-3-030-24202-2_12
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