NoiseCAM: Explainable AI for the Boundary Between Noise and Adversarial Attacks-Reference-Cited by-同舟云学术

NoiseCAM: Explainable AI for the Boundary Between Noise and Adversarial Attacks

Author:

Tan Wenkai¹,Renkhoff Justus²,Velasquez Alvaro³,Wang Ziyu⁴,Li Lusi⁴,Wang Jian⁵,Niu Shuteng⁶,Yang Fan¹,Liu Yongxin¹,Song Houbing²

Affiliation:

1. Embry-Riddle Aeronautical University,FL,USA,32114

2. University of Maryland,MD,USA,21250

3. University of Colorado Boulder,CO,USA,80309

4. Old Dominion University,VA,USA,23529

5. University of Tennessee at Martin,TN,USA,38237

6. Bowling Green State University,OH,USA,43403

Funder

National Science Foundation

Publisher

IEEE

Link

Reference40 articles.

3. Convergence of adversarial training in overparametrized neural networks;gao;Advances in neural information processing systems,2019

4. Tensorfuzz: De-bugging neural networks with coverage-guided fuzzing;odena;International Conference on Machine Learning,2019

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

2. Explainable AI for Comparative Analysis of Intrusion Detection Models;2024 IEEE International Mediterranean Conference on Communications and Networking (MeditCom);2024-07-08

3. Explainable Artificial Intelligence for Antenna Sensor Modeling;2024 IEEE International Mediterranean Conference on Communications and Networking (MeditCom);2024-07-08

4. X-GRL: An Empirical Assessment of Explainable GNN-DRL in B5G/6G Networks;2023 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN);2023-11-07