Taxonomy and Simulation of Bio-Analogous Multi-Stage Cyberattacks
Received: 29 November 2025 | Revised: 18 February 2026, 7 March 2026, and 21 March 2026 | Accepted: 23 March 2026 | Online: 15 April 2026
Corresponding author: Malek Mahmoud Barhoush
Abstract
Today, bio-inspired approaches in cybersecurity represent an active research area in the literature, as these approaches offer adaptability, learning, and robustness to face modern, evolving cyber threats. Traditional Intrusion Detection Systems (IDSs) are increasingly proficient at identifying isolated malicious events, yet they remain vulnerable to coordinated, multi-stage deception that mimics biological social structures. The primary gap in current literature is a lack of formal frameworks that map complex predator-prey dynamics, such as distraction-based deception and fission–fusion coordination, to modern network attack vectors. To address this, we propose a novel taxonomy and realistic discrete-event simulation framework for bio-analogous cyberattacks based on two natural archetypes: the Crow, representing sophisticated deception and decoy-based exfiltration, and the Wild Dog, representing decentralized coordination and sequential hunting. Leveraging the OMNeT++/INET framework and an enterprise-inspired network topology, we emulate how biological perseverance and role-division can be mapped to advanced multi-vector intrusions.
Keywords:
bio-analogous, Crows, Wild Dogs, Intrusion Detection Systems (IDSs), multi-stage attacksDownloads
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Copyright (c) 2026 Shaher Suleman Slehat, Esraa Abu Elsoud, Layla Albdour, Esra'a Alhenawi, Malek Mahmoud Barhoush
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