AIセキュリティポータルbot

Adaptive Attractors: A Defense Strategy against ML Adversarial Collusion Attacks

Authors: Jiyi Zhang, Han Fang, Ee-Chien Chang | Published: 2023-06-02
攻撃の評価
敵対的攻撃
透かし評価

FedCIP: Federated Client Intellectual Property Protection with Traitor Tracking

Authors: Junchuan Liang, Rong Wang | Published: 2023-06-02
プライバシー保護技術
知的財産保護
透かし評価

DeepfakeArt Challenge: A Benchmark Dataset for Generative AI Art Forgery and Data Poisoning Detection

Authors: Hossein Aboutalebi, Dayou Mao, Rongqi Fan, Carol Xu, Chris He, Alexander Wong | Published: 2023-06-02 | Updated: 2024-05-23
データセット生成
知的財産保護
透かし評価

Impact of using a privacy model on smart buildings data for CO2 prediction

Authors: Marlon P. da Silva, Henry C. Nunes, Charles V. Neu, Luana T. Thomas, Avelino F. Zorzo, Charles Morisset | Published: 2023-06-01
CO2識別モデル
データプライバシー評価
プライバシー保護技術

Adversarial Robustness in Unsupervised Machine Learning: A Systematic Review

Authors: Mathias Lundteigen Mohus, Jinyue Li | Published: 2023-06-01
プライバシー保護手法
ポイズニング
敵対的攻撃手法

Byzantine-Robust Clustered Federated Learning

Authors: Zhixu Tao, Kun Yang, Sanjeev R. Kulkarni | Published: 2023-06-01
ビザンチン合意メカニズム
収束特性
損失項

Constructing Semantics-Aware Adversarial Examples with a Probabilistic Perspective

Authors: Andi Zhang, Mingtian Zhang, Damon Wischik | Published: 2023-06-01 | Updated: 2024-11-24
ポイズニング
拡散モデル
敵対的攻撃手法

Adversarial-Aware Deep Learning System based on a Secondary Classical Machine Learning Verification Approach

Authors: Mohammed Alkhowaiter, Hisham Kholidy, Mnassar Alyami, Abdulmajeed Alghamdi, Cliff Zou | Published: 2023-06-01
敵対的サンプル
敵対的攻撃
透かし評価

Case Study-Based Approach of Quantum Machine Learning in Cybersecurity: Quantum Support Vector Machine for Malware Classification and Protection

Authors: Mst Shapna Akter, Hossain Shahriar, Sheikh Iqbal Ahamed, Kishor Datta Gupta, Muhammad Rahman, Atef Mohamed, Mohammad Rahman, Akond Rahman, Fan Wu | Published: 2023-06-01
マルウェア分類
リソース不足の課題
学習タスクの効率的な解決

Feature Engineering-Based Detection of Buffer Overflow Vulnerability in Source Code Using Neural Networks

Authors: Mst Shapna Akter, Hossain Shahriar, Juan Rodriguez Cardenas, Sheikh Iqbal Ahamed, Alfredo Cuzzocrea | Published: 2023-06-01
深層学習手法
脅威モデリング
脆弱性分析