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C. Assi

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2026

Multistatic ISAC for Improved Sensing Under Jamming Attacks: A Gradient-Based Meta-Learning Approach

Motivated by the growing vulnerability of integrated sensing and communication (ISAC) systems to jamming attacks, this work explores multistatic architectures as a promising approach to improve robustness in adversarial environments, specifically in the sensing functionality. We consider a multistatic ISAC framework in...

Aya El Bokhary, Ali Amhaz, S. Sharafeddine et al. · 0 citations
#artificial intelligence Preprint Sep 2026

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

Threat hunting increasingly depends on converting unstructured knowledge (e.g., Cyber Threat Intelligence reports) into actionable hunt leads: concise, investigable hypotheses grounded in observable artifacts and adversary techniques. Producing such leads manually is a tedious and hard-to-scale task. Existing automated...

A. Prakash, Boubakr Nour, M. Pourzandi et al. · 0 citations
#artificial intelligence Preprint Aug 2026

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

AUTOSIGMA, an automated solution for transforming unstructured CTI reports into relevant Sigma rules that enables accurate, context-aware, and relevant rule generation, outperforms alternative solutions and LLM models in rule validity, rule relevancy, MITRE ATT&CK technique coverage, and robustness to input quality.

Sepehr Ghaffarzadegan, Boubakr Nour, M. Pourzandi et al. · 0 citations

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