Description

本日紹介した論文の一覧

• Privacy and Accuracy-Aware AI/ML Model Deduplication
  http://arxiv.org/abs/2503.02862v1

• Quantitative Resilience Modeling for Autonomous Cyber Defense
  http://arxiv.org/abs/2503.02780v1

• ESSPI: ECDSA/Schnorr Signed Program Input for BitVMX
  http://arxiv.org/abs/2503.02772v1

• Optimisation of cyber insurance coverage with selection of cost
  effective security controls
  http://arxiv.org/abs/2503.02706v1

• RedChronos: A Large Language Model-Based Log Analysis System for Insider
  Threat Detection in Enterprises
  http://arxiv.org/abs/2503.02702v1

• Unclonable Encryption with Continuous Variables
  http://arxiv.org/abs/2503.02648v1

• LLM-Safety Evaluations Lack Robustness
  http://arxiv.org/abs/2503.02574v1

• TFHE-SBC: Software Designs for Fully Homomorphic Encryption over the
  Torus on Single Board Computers
  http://arxiv.org/abs/2503.02559v1

• Attack Tree Distance: a practical examination of tree difference
  measurement within cyber security
  http://arxiv.org/abs/2503.02499v1

• Privacy Preservation Techniques (PPTs) in IoT Systems: A Scoping Review
  and Future Directions
  http://arxiv.org/abs/2503.02455v1

• Through the Static: Demystifying Malware Visualization via
  Explainability
  http://arxiv.org/abs/2503.02441v1

• PANTHER: Pluginizable Testing Environment for Network Protocols
  http://arxiv.org/abs/2503.02413v1

• Trace of the Times: Rootkit Detection through Temporal Anomalies in
  Kernel Activity
  http://arxiv.org/abs/2503.02402v1

• A Kolmogorov-Arnold Network for Explainable Detection of Cyberattacks on
  EV Chargers
  http://arxiv.org/abs/2503.02281v1

• Client-Aided Secure Two-Party Computation of Dynamic Controllers
  http://arxiv.org/abs/2503.02176v1

• DDAD: A Two-pronged Adversarial Defense Based on Distributional
  Discrepancy
  http://arxiv.org/abs/2503.02169v1

• Malware Classification from Memory Dumps Using Machine Learning,
  Transformers, and Large Language Models
  http://arxiv.org/abs/2503.02144v1

• Network Traffic Classification Using Machine Learning, Transformer, and
  Large Language Models
  http://arxiv.org/abs/2503.02141v1

なお、ポッドキャスト内で紹介する内容は、各論文の概要を日本語で解説したもので、論文概要の著作権は論文著者に帰属します。