96 citations · 141 across the 18 of their papers we have counts for
Showing 2024 · cs.CRShow all
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cs.CR2024
A Survey on Adversarial Machine Learning for Code Data: Realistic Threats, Countermeasures, and Interpretations
Yulong Yang, Haoran Fan, Chenhao Lin +4
Code Language Models (CLMs) have achieved tremendous progress in source code understanding and generation, leading to a significant increase in research interests focused on applyi…
cs.CR2024
Systematic Categorization, Construction and Evaluation of New Attacks against Multi-modal Mobile GUI Agents
Yulong Yang, Xinshan Yang, Shuaidong Li +4
The integration of Large Language Models (LLMs) and Multi-modal Large Language Models (MLLMs) into mobile GUI agents has significantly enhanced user efficiency and experience. Howe…
cs.CR2024★ 96 cited
LESSON: Multi-Label Adversarial False Data Injection Attack for Deep Learning Locational Detection
Jiwei Tian, Chao Shen, Buhong Wang +4
Deep learning methods can not only detect false data injection attacks (FDIA) but also locate attacks of FDIA. Although adversarial false data injection attacks (AFDIA) based on de…