4 citations · 8 across the 11 of their papers we have counts for
13 papers
HYDRA: Quantifying Botnet Resource Thresholds for Efficient Link-Flooding Attacks on LEO Satellite Networks
Roee Idan, Rami Puzis, Asaf Shabtai +1
Low Earth orbit (LEO) satellite constellations, such as Starlink and Kuiper, are rapidly emerging as a critical backbone for low-latency global connectivity. As these systems expan…
Learning What to Fail On: Failure-Mode Contextual Bandits for Adversarial Data Curation
Roie Kazoom, Ofir Cohen, Rami Puzis +2
We introduce a failure-aware adversarial retrieval-augmented framework for improving robustness in natural language understanding. Rather than selecting synthetic examples with a f…
(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations
Neta Kirmayer, David Tayouri, Andrés Murillo +3
Security operations centers rely on anomaly detection systems to flag suspicious events. Feature-level explanations for anomaly detectors offer limited value for operational invest…
COHORT: Collaborative Orchestration for Hardening via Offensive Replay on Emulated Topologies
Chen Frydman, Aviram Zilberman, Rubin Krief +6
Mitigating an observed adversary in an enterprise network typically takes weeks of expert work: an analyst derives a mitigation tailored to that adversary, validates it without bre…
ConGISATA: A Framework for Continuous Gamified Information Security Awareness Training and Assessment
Ofir Cohen, Ron Bitton, Asaf Shabtai +1
The incidence of cybersecurity attacks utilizing social engineering techniques has increased. Such attacks exploit the fact that in every secure system, there is at least one indiv…
FreakOut-LLM: The Effect of Emotional Stimuli on Safety Alignment
Daniel Kuznetsov, Ofir Cohen, Karin Shistik +2
Safety-aligned LLMs go through refusal training to reject harmful requests, but whether these mechanisms remain effective under emotionally charged stimuli is unexplored. We introd…
SCyTAG: Scalable Cyber-Twin for Threat-Assessment Based on Attack Graphs
David Tayouri, Elad Duani, Abed Showgan +8
Understanding the risks associated with an enterprise environment is the first step toward improving its security. Organizations employ various methods to assess and prioritize the…
VAULT: Vigilant Adversarial Updates via LLM-Driven Retrieval-Augmented Generation for NLI
Roie Kazoom, Ofir Cohen, Rami Puzis +2
We introduce VAULT, a fully automated adversarial RAG pipeline that systematically uncovers and remedies weaknesses in NLI models through three stages: retrieval, adversarial gener…
ATAG: AI-Agent Application Threat Assessment with Attack Graphs
Parth Atulbhai Gandhi, Akansha Shukla, David Tayouri +4
Evaluating the security of multi-agent systems (MASs) powered by large language models (LLMs) is challenging, primarily because of the systems' complex internal dynamics and the ev…
FAA Framework: A Large Language Model-Based Approach for Credit Card Fraud Investigations
Shaun Shuster, Eyal Zloof, Asaf Shabtai +1
Credit card fraud mitigation plays a significant role in modern society. While fraud detection systems are essential, they often struggle to keep pace with the constantly evolving…
LISAA: A Framework for Large Language Model Information Security Awareness Assessment
Ofir Cohen, Gil Ari Agmon, Asaf Shabtai +1
The popularity of large language models (LLMs) continues to grow, and LLM-based assistants have become ubiquitous. Information security awareness (ISA) is an important yet underexp…
GeNet: A Multimodal LLM-Based Co-Pilot for Network Topology and Configuration
Beni Ifland, Elad Duani, Rubin Krief +9
Communication network engineering in enterprise environments is traditionally a complex, time-consuming, and error-prone manual process. Most research on network engineering automa…
Enhancing Energy Sector Resilience: Integrating Security by Design Principles
Dov Shirtz, Inna Koberman, Aviad Elyashar +2
Security by design, Sbd is a concept for developing and maintaining systems that are, to the greatest extent possible, free from security vulnerabilities and impervious to security…