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20232026
most citedA Comprehensive Analysis of the Role of Artificial Intelligence and Machine Learning in Modern Digital Forensics and Incident Response

119 citations · 193 across the 11 of their papers we have counts for

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Showing 2026 · cs.CRShow all

6 papers · 2 filters

cs.CR2026

When Benign Is Unverified: Label-Signal Mismatch and Abstention-First Triage in Graph-Based Memory Forensics

Viraj Rajeshbhai Chudasama, Eduardo Palmieri, Dipo Dunsin +2

Machine-learning triage for memory forensics is usually validated on corpora whose benign class is asserted by provenance and never verified. We report a validation study of a grap…

cs.CR2026

Adaptive Dynamic Security for Operational Technology Against AI-Powered Attacks

Mohamed Chahine Ghanem

Operational technology now faces attackers whose tempo is set by AI. We present ADS-OT, an adaptive dynamic security framework modelling defensive posture as a partially observable…

cs.CR2026

PentestChain: A Cost-Aware, MCP-Orchestrated Framework for Automated Penetration Testing with Free-Tier LLMs

Rushabh Vipulkumar Patel, Dipo Dunsin, Mohammed Almaiah +1

AI-driven penetration testing has been demonstrated with premium frontier models such as GPT-4, but the per-engagement token cost makes continuous, automated testing unaffordable f…

cs.CR2026

Steganalysis of Adaptive Covert Collusion in Tool-Using Agent Populations: A Black-Box, Cross-Principal Approach

Mohamed Chahine Ghanem

Tool-using agents built on large language models (LLMs) are increasingly deployed not by a single operator but by many, side by side on shared infrastructure. This creates a popula…

cs.CR2026

Agentic and Generative AI for Open-Source Intelligence and Cyber Investigations: Taxonomy, Evaluation, Challenges, and Future Directions

Eduardo Almeida Palmieri, Mohamed Chahine Ghanem, Dipo Dunsin +3

The rapid growth of publicly available digital information has rendered manual open-source intelligence (OSINT) analysis insufficient for modern intelligence, cybersecurity, and cy…

cs.CR2026

Builder, Defender, Breaker: Measurable Independence and Bounded Autonomy When Generative Models Build, Defend and Test Software

Mohamed Chahine Ghanem

Generative models now write application code, harden and monitor it, and probe it for exploitable flaws, so that one family of models increasingly plays builder, defender and break…