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20192026
most citedAn Experimental Analysis of Attack Classification Using Machine Learning in IoT Networks

432 citations · 520 across the 17 of their papers we have counts for

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5 papers · 1 filter

cs.CR2026

Automated Rule Mutation for Emerging Attack Variants using Infrastructure-Aware Technique Proximity

Sepehr Ghaffarzadegan, Boubakr Nour, Makan Pourzandi +2

Detection rules are typically crafted based on specific observations of an attack. While these rules are effective for particular attack instances, their coverage diminishes when a…

cs.CR2026

Evidence-Grounded Retrieval for Investigation Hunt Lead Generation from CTI Reports

Akash Prakash, Boubakr Nour, Makan Pourzandi +2

Threat hunting increasingly depends on converting unstructured knowledge (e.g., Cyber Threat Intelligence reports) into actionable hunt leads: concise, investigable hypotheses grou…

cs.CR2026

From Threat Intelligence to Detection: Knowledge-driven Enrichment and Template-based Rule Grounding for Automated Sigma Rule Generation

Sepehr Ghaffarzadegan, Boubakr Nour, Makan Pourzandi +2

Mechanisms for dynamically converting cyber threat intelligence (CTI) into actionable detection capabilities are necessary due to the rapid evolution of Advanced Persistent Threats…

cs.CR2025

Automated Attack Testflow Extraction from Cyber Threat Report using BERT for Contextual Analysis

Faissal Ahmadou, Sepehr Ghaffarzadegan, Boubakr Nour +3

In the ever-evolving landscape of cybersecurity, the rapid identification and mitigation of Advanced Persistent Threats (APTs) is crucial. Security practitioners rely on detailed t…

cs.CR2021★ 432 cited

An Experimental Analysis of Attack Classification Using Machine Learning in IoT Networks

Andrew Churcher, Rehmat Ullah, Jawad Ahmad +6

In recent years, there has been a massive increase in the amount of Internet of Things (IoT) devices as well as the data generated by such devices. The participating devices in IoT…