共 50 条
- [1] Data Poisoning Attacks against Autoencoder-based Anomaly Detection Models: a Robustness Analysis IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2022), 2022, : 5427 - 5432
- [3] Robust Graph Autoencoder-Based Detection of False Data Injection Attacks Against Data Poisoning in Smart Grids IEEE Transactions on Artificial Intelligence, 2024, 5 (03): : 1287 - 1301
- [7] Utilizing Autoencoder to Improve the Robustness of Intrusion Detection Systems against Adversarial Attacks IEEE CONFERENCE ON GLOBAL COMMUNICATIONS, GLOBECOM, 2023, : 970 - 975
- [8] Proving Robustness of KNN Against Adversarial Data Poisoning 2022 FORMAL METHODS IN COMPUTER-AIDED DESIGN, FMCAD, 2022, 3 : 7 - 16
- [9] Training Strategies for Autoencoder-based Detection of False Data Injection Attacks 2020 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES EUROPE (ISGT-EUROPE 2020): SMART GRIDS: KEY ENABLERS OF A GREEN POWER SYSTEM, 2020, : 1 - 5
- [10] Intrinsic Certified Robustness of Bagging against Data Poisoning Attacks THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2021, 35 : 7961 - 7969