Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables

12 March 2018

Bojan Kolosnjaji

Ambra Demontis

Battista Biggio

Davide Maiorca

Giorgio Giacinto

Claudia Eckert

Fabio Roli

AAML

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Papers citing "Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables"

31 / 31 papers shown

Title
Updating Windows Malware Detectors: Balancing Robustness and Regression against Adversarial EXEmples M. Kozák Luca Demetrio Dmitrijs Trizna Fabio Roli AAML 34 0 0 04 May 2024
Exploring the Vulnerabilities of Machine Learning and Quantum Machine Learning to Adversarial Attacks using a Malware Dataset: A Comparative Analysis Mst. Shapna Akter Hossain Shahriar Iysa Iqbal M. Hossain M. A. Karim Victor A. Clincy R. Voicu AAML 18 8 0 31 May 2023
Harnessing the Speed and Accuracy of Machine Learning to Advance Cybersecurity Khatoon Mohammed AAML 18 10 0 24 Feb 2023
PAD: Towards Principled Adversarial Malware Detection Against Evasion Attacks Deqiang Li Shicheng Cui Yun Li Jia Xu Fu Xiao Shouhuai Xu AAML 54 18 0 22 Feb 2023
Backdoor Learning for NLP: Recent Advances, Challenges, and Future Research Directions Marwan Omar SILM AAML 33 20 0 14 Feb 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 32 15 0 31 Jan 2023
Analysis of Label-Flip Poisoning Attack on Machine Learning Based Malware Detector Kshitiz Aryal Maanak Gupta Mahmoud Abdelsalam AAML 18 18 0 03 Jan 2023
Efficient Malware Analysis Using Metric Embeddings Ethan M. Rudd David B. Krisiloff Scott E. Coull Daniel Olszewski Edward Raff James Holt AAML 23 6 0 05 Dec 2022
Adversarial Robustness for Tabular Data through Cost and Utility Awareness Klim Kireev B. Kulynych Carmela Troncoso AAML 26 16 0 27 Aug 2022
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 34 73 0 23 Dec 2021
Single-Shot Black-Box Adversarial Attacks Against Malware Detectors: A Causal Language Model Approach Junjie Hu Mohammadreza Ebrahimi Hsinchun Chen AAML 18 11 0 03 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 32 51 0 07 Oct 2021
Adversarial Transfer Attacks With Unknown Data and Class Overlap Luke E. Richards A. Nguyen Ryan Capps Steven D. Forsythe Cynthia Matuszek Edward Raff AAML 33 7 0 23 Sep 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 33 14 0 06 Nov 2020
Being Single Has Benefits. Instance Poisoning to Deceive Malware Classifiers T. Shapira David Berend Ishai Rosenberg Yang Liu A. Shabtai Yuval Elovici AAML 19 4 0 30 Oct 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 24 59 0 17 Aug 2020
A Survey of Machine Learning Methods and Challenges for Windows Malware Classification Edward Raff Charles K. Nicholas AAML 27 54 0 15 Jun 2020
Functionality-preserving Black-box Optimization of Adversarial Windows Malware Luca Demetrio Battista Biggio Giovanni Lagorio Fabio Roli A. Armando AAML 23 136 0 30 Mar 2020
Explanation-Guided Backdoor Poisoning Attacks Against Malware Classifiers Giorgio Severi J. Meyer Scott E. Coull Alina Oprea AAML SILM 21 18 0 02 Mar 2020
MDEA: Malware Detection with Evolutionary Adversarial Learning Xiruo Wang Risto Miikkulainen AAML 17 15 0 09 Feb 2020
WAF-A-MoLE: Evading Web Application Firewalls through Adversarial Machine Learning Luca Demetrio Andrea Valenza Gabriele Costa Giovanni Lagorio AAML 11 27 0 07 Jan 2020
Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable Bytes Keane Lucas Mahmood Sharif Lujo Bauer Michael K. Reiter S. Shintre AAML 31 66 0 19 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 26 28 0 20 Sep 2019
Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries Luca Demetrio Battista Biggio Giovanni Lagorio Fabio Roli A. Armando AAML 19 129 0 11 Jan 2019
Evading classifiers in discrete domains with provable optimality guarantees B. Kulynych Jamie Hayes N. Samarin Carmela Troncoso AAML 13 19 0 25 Oct 2018
Exploring Adversarial Examples in Malware Detection Octavian Suciu Scott E. Coull Jeffrey Johns AAML 21 188 0 18 Oct 2018
Non-Negative Networks Against Adversarial Attacks William Fleshman Edward Raff Jared Sylvester Steven Forsyth Mark McLean AAML 27 41 0 15 Jun 2018