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January 1, 2026International Journal of Information and Computer Security

Adversarial threat evaluation of machine learning-based phishing detectors: a cybersecurity-focused black-box perspective

Eiman Tamah Al Shammari

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Key Points

The study aims to evaluate the effectiveness of machine learning-based phishing detectors against adversarial threats.
Identified types of adversarial attacks targeting phishing detectors.
Conducted evaluations of various machine learning algorithms under simulated attack scenarios.
Analyzed detection accuracy and response to specific adversarial manipulations.
Found significant vulnerabilities in existing phishing detection systems.
Demonstrated that certain attack methods considerably reduced detection rates.
Identified potential strategies to enhance resilience against adversarial threats.

Implication

Evaluative analysis uncovers vulnerabilities in machine learning phishing detectors, suggesting improvements for cybersecurity.

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Cite This Study

Eiman Tamah Al Shammari (2026) studied this question.

synapsesocial.com/papers/69c772d98bbfbc51511e33e8 https://doi.org/10.1504/ijics.2026.10077273

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