Adversarial Samples on Android Malware Detection Systems for IoT Systems

Adversarial Samples on Android Malware Detection Systems for IoT Systems

12 February 2019

Papers citing "Adversarial Samples on Android Malware Detection Systems for IoT Systems"

10 / 10 papers shown

Title
Privacy Preservation in Artificial Intelligence and Extended Reality (AI-XR) Metaverses: A Survey Mahdi Alkaeed Adnan Qayyum Junaid Qadir 34 16 0 19 Sep 2023
Deep transfer learning for intrusion detection in industrial control networks: A comprehensive review Hamza Kheddar Yassine Himeur A. Awad AI4CE 34 62 0 19 Apr 2023
"How Does It Detect A Malicious App?" Explaining the Predictions of AI-based Android Malware Detector Zhi Lu V. Thing AAML 24 4 0 06 Nov 2021
EvadeDroid: A Practical Evasion Attack on Machine Learning for Black-box Android Malware Detection Hamid Bostani Veelasha Moonsamy AAML 40 51 0 07 Oct 2021
Metamorphic Detection of Repackaged Malware S. Singh Gail E. Kaiser 24 8 0 27 Apr 2021
ShellCore: Automating Malicious IoT Software Detection by Using Shell Commands Representation Hisham Alasmary Afsah Anwar Ahmed A. Abusnaina Abdulrahman Alabduljabbar Mohammad Abuhamad An Wang Daehun Nyang Amro Awad David A. Mohaisen 14 11 0 26 Mar 2021
When the Guard failed the Droid: A case study of Android malware Harel Berger Chen Hajaj A. Dvir AAML 30 7 0 31 Mar 2020
MAB-Malware: A Reinforcement Learning Framework for Attacking Static Malware Classifiers Wei Song Xuezixiang Li Sadia Afroz D. Garg Dmitry Kuznetsov Heng Yin AAML 55 27 0 06 Mar 2020
Weighted-Sampling Audio Adversarial Example Attack Xiaolei Liu Xiaosong Zhang Kun Wan Qingxin Zhu Yufei Ding DiffM AAML 36 36 0 26 Jan 2019
A Black-box Attack on Neural Networks Based on Swarm Evolutionary Algorithm Xiaolei Liu Yuheng Luo Xiaosong Zhang Qingxin Zhu AAML 24 16 0 26 Jan 2019