Description

本日紹介した論文の一覧

• Mitigating Bias in Machine Learning Models for Phishing Webpage
  Detection
  http://arxiv.org/abs/2401.08363v1

• Personalized Federated Learning of Probabilistic Models: A PAC-Bayesian
  Approach
  http://arxiv.org/abs/2401.08351v1

• dabih -- encrypted data storage and sharing platform
  http://arxiv.org/abs/2401.08333v1

• Probabilistically Robust Watermarking of Neural Networks
  http://arxiv.org/abs/2401.08261v1

• Differentially Private Estimation of CATE in Adaptive Experiment
  http://arxiv.org/abs/2401.08224v1

• Towards Efficient and Certified Recovery from Poisoning Attacks in
  Federated Learning
  http://arxiv.org/abs/2401.08216v1

• On Cryptographic Mechanisms for the Selective Disclosure of Verifiable
  Credentials
  http://arxiv.org/abs/2401.08196v1

• Differentially Private Sliced Inverse Regression: Minimax Optimality and
  Algorithm
  http://arxiv.org/abs/2401.08150v1

• IoTWarden: A Deep Reinforcement Learning Based Real-time Defense System
  to Mitigate Trigger-action IoT Attacks
  http://arxiv.org/abs/2401.08141v1

• Machine Learning-Based Malicious Vehicle Detection for Security Threats
  and Attacks in Vehicle Ad-hoc Network (VANET) Communications
  http://arxiv.org/abs/2401.08135v1

• Game Rewards Vulnerabilities: Software Vulnerability Detection with
  Zero-Sum Game and Prototype Learning
  http://arxiv.org/abs/2401.08131v1

• Framework and Classification of Indicator of Compromise for
  physics-based attacks
  http://arxiv.org/abs/2401.08127v1

• Calpric: Inclusive and Fine-grain Labeling of Privacy Policies with
  Crowdsourcing and Active Learning
  http://arxiv.org/abs/2401.08038v1

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。