Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples

13 February 2018

Papers citing "Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples"

21 / 21 papers shown

Title
CaFA: Cost-aware, Feasible Attacks With Database Constraints Against Neural Tabular Classifiers Matan Ben-Tov Daniel Deutch Nave Frost Mahmood Sharif AAML 107 0 0 20 Jan 2025
Updating Windows Malware Detectors: Balancing Robustness and Regression against Adversarial EXEmples M. Kozák Luca Demetrio Dmitrijs Trizna Fabio Roli AAML 31 0 0 04 May 2024
CARE: Ensemble Adversarial Robustness Evaluation Against Adaptive Attackers for Security Applications Hangsheng Zhang Jiqiang Liu Jinsong Dong AAML 21 1 0 20 Jan 2024
Madvex: Instrumentation-based Adversarial Attacks on Machine Learning Malware Detection Yang Cai Felix Mächtle C. Daskalakis Volodymyr Bezsmertnyi T. Eisenbarth AAML 31 7 0 04 May 2023
A Survey on Malware Detection with Graph Representation Learning Tristan Bilot Nour El Madhoun Khaldoun Al Agha Anis Zouaoui AAML 13 20 0 28 Mar 2023
RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion Zhuoqun Huang Neil G. Marchant Keane Lucas Lujo Bauer O. Ohrimenko Benjamin I. P. Rubinstein AAML 29 15 0 31 Jan 2023
Adversarial Attacks against Windows PE Malware Detection: A Survey of the State-of-the-Art Xiang Ling Lingfei Wu Jiangyu Zhang Zhenqing Qu Wei Deng ... Chunming Wu S. Ji Tianyue Luo Jingzheng Wu Yanjun Wu AAML 31 73 0 23 Dec 2021
A Comparison of State-of-the-Art Techniques for Generating Adversarial Malware Binaries P. Dasgupta Zachary Osman AAML 28 2 0 22 Nov 2021
EvadeDroid: A Practical Evasion Attack on Machine Learning for Black-box Android Malware Detection Hamid Bostani Veelasha Moonsamy AAML 30 51 0 07 Oct 2021
ML-based IoT Malware Detection Under Adversarial Settings: A Systematic Evaluation Ahmed A. Abusnaina Afsah Anwar Sultan Alshamrani Abdulrahman Alabduljabbar Rhongho Jang Daehun Nyang David A. Mohaisen AAML 22 1 0 30 Aug 2021
secml-malware: Pentesting Windows Malware Classifiers with Adversarial EXEmples in Python Luca Demetrio Battista Biggio AAML 37 11 0 26 Apr 2021
A survey on practical adversarial examples for malware classifiers Daniel Park B. Yener AAML 22 14 0 06 Nov 2020
Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection Luca Demetrio Scott E. Coull Battista Biggio Giovanni Lagorio A. Armando Fabio Roli AAML 22 59 0 17 Aug 2020
Subpopulation Data Poisoning Attacks Matthew Jagielski Giorgio Severi Niklas Pousette Harger Alina Oprea AAML SILM 16 112 0 24 Jun 2020
Random CapsNet Forest Model for Imbalanced Malware Type Classification Task Aykut Çayır U. Ünal Hasan Dag 24 41 0 20 Dec 2019
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey Olakunle Ibitoye Rana Abou-Khamis Mohamed el Shehaby Ashraf Matrawy M. O. Shafiq AAML 26 68 0 06 Nov 2019
COPYCAT: Practical Adversarial Attacks on Visualization-Based Malware Detection Aminollah Khormali Ahmed A. Abusnaina Songqing Chen Daehun Nyang Aziz Mohaisen AAML 17 28 0 20 Sep 2019
Exploring Adversarial Examples in Malware Detection Octavian Suciu Scott E. Coull Jeffrey Johns AAML 18 188 0 18 Oct 2018
Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables Bojan Kolosnjaji Ambra Demontis Battista Biggio Davide Maiorca Giorgio Giacinto Claudia Eckert Fabio Roli AAML 16 316 0 12 Mar 2018
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,835 0 08 Jul 2016
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 218 7,926 0 17 Aug 2015