Evolutionary computation as an artificial attacker: generating evasion attacks for detector vulnerability testing

Hilmi Gunes Kayacik, Nur Zincir-Heywood, Malcolm Heywood

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Intrusion detection systems protect our infrastructures by monitoring for signs of intrusions. However, intrusion detection systems are themselves susceptible to vulnerabilities, which the attackers take advantage of to evade detection. In particular, we focus on evasion attacks in which the attacker aims to generate a stealthy attack that eliminates or minimizes the likelihood of detection.
    Original languageEnglish
    Pages (from-to)243-266
    Number of pages24
    JournalEvolutionary Intelligence
    Volume4
    Issue number4
    DOIs
    Publication statusPublished - Dec 2011

    Keywords

    • intrusion detection
    • artificial arms race
    • evolutionary computation
    • computer security
    • Anomaly detection
    • evasion attacks

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