1 citations · 1 across the 4 of their papers we have counts for
4 papers
Train in Vain: Functionality-Preserving Poisoning to Prevent Unauthorized Use of Code Datasets
Yuan Xiao, Jiaming Wang, Yuchen Chen +8
The widespread availability of large-scale code datasets has accelerated the development of code large language models (CodeLLMs), raising concerns about unauthorized dataset usage…
Fuzzing with Quantitative and Adaptive Hot-Bytes Identification
Tai D. Nguyen, Long H. Pham, Jun Sun
Fuzzing has emerged as a powerful technique for finding security bugs in complicated real-world applications. American fuzzy lop (AFL), a leading fuzzing tool, has demonstrated its…
Two Sides of the Same Coin: Exploiting the Impact of Identifiers in Neural Code Comprehension
Shuzheng Gao, Cuiyun Gao, Chaozheng Wang +3
Previous studies have demonstrated that neural code comprehension models are vulnerable to identifier naming. By renaming as few as one identifier in the source code, the models wo…
Verifying Neural Networks Against Backdoor Attacks
Long H. Pham, Jun Sun
Neural networks have achieved state-of-the-art performance in solving many problems, including many applications in safety/security-critical systems. Researchers also discovered mu…