Misleading Authorship Attribution of Source Code using Adversarial Learning

29 May 2019

Papers citing "Misleading Authorship Attribution of Source Code using Adversarial Learning"

18 / 18 papers shown

Title
Understanding and Characterizing Obfuscated Funds Transfers in Ethereum Smart Contracts Zhang Sheng Tan Kia Quang Shen Wang Shengchen Duan Kai Li Yue Duan 17 0 0 16 May 2025
On Technique Identification and Threat-Actor Attribution using LLMs and Embedding Models Kyla Guru Robert J. Moss Mykel J. Kochenderfer 7 0 0 15 May 2025
AuthAttLyzer-V2: Unveiling Code Authorship Attribution using Enhanced Ensemble Learning Models & Generating Benchmark Dataset Bhaskar Joshi Sepideh HajiHossein Khani Arash HabibiLashkari 34 0 0 28 Jun 2024
An LLM-Assisted Easy-to-Trigger Backdoor Attack on Code Completion Models: Injecting Disguised Vulnerabilities against Strong Detection Shenao Yan Shen Wang Yue Duan Hanbin Hong Kiho Lee Doowon Kim Yuan Hong AAML SILM 43 17 0 10 Jun 2024
Deep Learning for Code Intelligence: Survey, Benchmark and Toolkit Yao Wan Yang He Zhangqian Bi Jianguo Zhang Hongyu Zhang Yulei Sui Guandong Xu Hai Jin Philip S. Yu 47 21 0 30 Dec 2023
Untargeted Code Authorship Evasion with Seq2Seq Transformation Soohyeon Choi Rhongho Jang Daehun Nyang David A. Mohaisen 26 0 0 26 Nov 2023
No more Reviewer #2: Subverting Automatic Paper-Reviewer Assignment using Adversarial Learning Thorsten Eisenhofer Erwin Quiring Jonas Moller Doreen Riepel Thorsten Holz Konrad Rieck AAML 28 6 0 25 Mar 2023
"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice Giovanni Apruzzese Hyrum S. Anderson Savino Dambra D. Freeman Fabio Pierazzi Kevin A. Roundy AAML 33 75 0 29 Dec 2022
Do You Think You Can Hold Me? The Real Challenge of Problem-Space Evasion Attacks Harel Berger A. Dvir Chen Hajaj Rony Ronen AAML 29 3 0 09 May 2022
RoPGen: Towards Robust Code Authorship Attribution via Automatic Coding Style Transformation Zhen Li Guenevere Chen Chen Chen Chen Yayi Zou Shouhuai Xu AAML AI4TS 24 44 0 12 Feb 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 44 74 0 23 Dec 2021
Bridging Pre-trained Models and Downstream Tasks for Source Code Understanding Deze Wang Zhouyang Jia Shanshan Li Yue Yu Yun Xiong Wei Dong Xiangke Liao 38 80 0 04 Dec 2021
Generating Adversarial Computer Programs using Optimized Obfuscations Shashank Srikant Sijia Liu Tamara Mitrovska Shiyu Chang Quanfu Fan Gaoyuan Zhang Una-May O’Reilly AAML 30 43 0 18 Mar 2021
Identifying Authorship Style in Malicious Binaries: Techniques, Challenges & Datasets J. Gray D. Sgandurra Lorenzo Cavallaro 21 8 0 15 Jan 2021
When Machine Unlearning Jeopardizes Privacy Min Chen Zhikun Zhang Tianhao Wang Michael Backes Mathias Humbert Yang Zhang MIACV 36 218 0 05 May 2020
Backdooring and Poisoning Neural Networks with Image-Scaling Attacks Erwin Quiring Konrad Rieck AAML 54 70 0 19 Mar 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 67 0 19 Dec 2019
Generating Natural Language Adversarial Examples M. Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani B. Srivastava Kai-Wei Chang AAML 258 916 0 21 Apr 2018