Integrating Artificial Intelligence and Cyber Law For Phishing and Fake Content Detection: A Legal Intelligence Framework
DOI:
https://doi.org/10.67440/ahj.vi.3088Keywords:
Phishing detection, fake content detection, machine learning, deep learning, natural language processing, cyber law, legal intelligence, explainable AI, adversarial robustness, cybersecurity.Abstract
Phishing and deceptive digital content combine URL obfuscation, impersonation, social engineering, and generated content. This paper reviews AI-based detection and presents a modular framework integrating URL, content, behavioral, explainability, and cyber-law intelligence. The framework connects technical threat evidence to candidate legal provisions, jurisdictional information, evidence requirements, and reporting guidance for human review. A reproducible validation protocol is specified for temporal drift, adversarial robustness, multilingual detection, computational efficiency, legal mapping, and human review. No experimental performance is claimed for the proposed integrated framework; the contribution is a structured architecture and an evaluation pathway that can be implemented and tested.
