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From the 1 of 7 linked papers with an AI index.

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7 papers

cs.CR2026

MTD-Playground: An Attacker-Aware Evaluation Framework for Network Moving Target Defense

Mohammad Farhad, Mohoshin Ara Tahera, Padam Jung Thapa +2

The paper introduces MTD-Playground, a framework that evaluates how SDN‑based path‑randomization moving target defenses affect multi‑stage attacks, showing that frequent reconfigur…

cs.SE2026

Residual Risk Assessment in Benign Code: How Far Are We? A Multi-Model Semantic and Structural Similarity Approach

Mohammad Farhad, Shuvalaxmi Dass

Software security assurance relies on effective vulnerability detection and patching, yet determining whether a patch fully eliminates risk remains an underexplored challenge. Exis…

cs.CR2026

HYDRA: A Hybrid Heuristic-Guided Deep Representation Architecture for Predicting Latent Zero-Day Vulnerabilities in Patched Functions

Mohammad Farhad, Sabbir Rahman, Shuvalaxmi Dass

Software security testing, particularly when enhanced with deep learning models, has become a powerful approach for improving software quality, enabling faster detection of known f…

cs.CR2026

BlocksecRT-DETR: Decentralized Privacy-Preserving and Token-Efficient Federated Transformer Learning for Secure Real-Time Object Detection in ITS

Mohoshin Ara Tahera, Sabbir Rahman, Shuvalaxmi Dass +2

Federated real-time object detection using transformers in Intelligent Transportation Systems (ITS) faces three major challenges: (1) missing-class non-IID data heterogeneity from…

cs.CR2026

SoK: Privacy-aware LLM in Healthcare: Threat Model, Privacy Techniques, Challenges and Recommendations

Mohoshin Ara Tahera, Karamveer Singh Sidhu, Shuvalaxmi Dass +1

Large Language Models (LLMs) are increasingly adopted in healthcare to support clinical decision-making, summarize electronic health records (EHRs), and enhance patient care. Howev…

cs.CR2026

Memory-Based Malware Detection under Limited Data Conditions: A Comparative Evaluation of TabPFN and Ensemble Models

Valentin Leroy, Shuvalaxmi Dass, Sharif Ullah

Artificial intelligence and machine learning have significantly advanced malware research by enabling automated threat detection and behavior analysis. However, the availability of…