Trojan Attacks on Wireless Signal Classification with Adversarial Machine Learning

23 October 2019

Papers citing "Trojan Attacks on Wireless Signal Classification with Adversarial Machine Learning"

12 / 12 papers shown

Title
BadRes: Reveal the Backdoors through Residual Connection Min He Tianyu Chen Haoyi Zhou Shanghang Zhang Jianxin Li 24 0 0 15 Sep 2022
Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples Giovanni Apruzzese Rodion Vladimirov A.T. Tastemirova Pavel Laskov AAML 38 15 0 04 Jul 2022
Adversarial Attacks against Deep Learning Based Power Control in Wireless Communications Brian Kim Yi Shi Y. Sagduyu T. Erpek S. Ulukus AAML 25 27 0 16 Sep 2021
Membership Inference Attack and Defense for Wireless Signal Classifiers with Deep Learning Yi Shi Y. Sagduyu 19 16 0 22 Jul 2021
Adversarial Machine Learning for Flooding Attacks on 5G Radio Access Network Slicing Yi Shi Y. Sagduyu AAML AI4CE 41 30 0 21 Jan 2021
Developing Future Human-Centered Smart Cities: Critical Analysis of Smart City Security, Interpretability, and Ethical Challenges Kashif Ahmad Majdi Maabreh M. Ghaly Khalil Khan Junaid Qadir Ala I. Al-Fuqaha 27 142 0 14 Dec 2020
Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review Yansong Gao Bao Gia Doan Zhi-Li Zhang Siqi Ma Jiliang Zhang Anmin Fu Surya Nepal Hyoungshick Kim AAML 36 220 0 21 Jul 2020
Backdoor Learning: A Survey Yiming Li Yong Jiang Zhifeng Li Shutao Xia AAML 45 590 0 17 Jul 2020
How to Make 5G Communications "Invisible": Adversarial Machine Learning for Wireless Privacy Brian Kim Y. Sagduyu Kemal Davaslioglu T. Erpek S. Ulukus AAML 17 29 0 15 May 2020
Channel-Aware Adversarial Attacks Against Deep Learning-Based Wireless Signal Classifiers Brian Kim Y. Sagduyu Kemal Davaslioglu T. Erpek S. Ulukus AAML 23 111 0 11 May 2020
Over-the-Air Adversarial Attacks on Deep Learning Based Modulation Classifier over Wireless Channels Brian Kim Y. Sagduyu Kemal Davaslioglu T. Erpek S. Ulukus AAML 48 68 0 05 Feb 2020
When Wireless Security Meets Machine Learning: Motivation, Challenges, and Research Directions Y. Sagduyu Yi Shi T. Erpek William C. Headley Bryse Flowers G. Stantchev Zhuo Lu AAML 20 39 0 24 Jan 2020