An interpretable vulnerability-aware ML-based approach is presented to solve the problem of smart home IoT intrusion detection through the integration of vulnerability classes of IoT, attack classes, network flow attributes, and ML features into one interpretation model.
Huda Aldawghan, Mounir Frikha· International Journal of Adv...· 0 citations
This study proposes a machine learning (ML)-based framework intended for integration within penetration testing environments, designed for real-time deployment, enabling integration into penetration testing workflows for proactive security assessment.
Ashwag Alotaibi, Mounir Frikha· International Journal of Adv...· 0 citations
A behavior-sensitive access control solution is presented, which integrates lightweight supervised Machine Learning on the IoT gateway to provide dynamic authorization and uses a Supervised Random Forest model to process real-time statistical feature summaries in terms of mean, standard deviation, and sparsity of the I...
Yaseen Alduwayl, Abdullah T. Al-Essa, Mounir Frikha· International Journal of Adv...· 0 citations
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