4 citations · 18 across the 22 of their papers we have counts for
6 papers · 1 filter
ProSec: Fortifying Code LLMs with Proactive Security Alignment
Xiangzhe Xu, Zian Su, Jinyao Guo +3
While recent code-specific large language models (LLMs) have greatly enhanced their code generation capabilities, the safety of these models remains under-explored, posing potentia…
ROCAS: Root Cause Analysis of Autonomous Driving Accidents via Cyber-Physical Co-mutation
Shiwei Feng, Yapeng Ye, Qingkai Shi +5
As Autonomous driving systems (ADS) have transformed our daily life, safety of ADS is of growing significance. While various testing approaches have emerged to enhance the ADS reli…
Source Code Foundation Models are Transferable Binary Analysis Knowledge Bases
Zian Su, Xiangzhe Xu, Ziyang Huang +2
Human-Oriented Binary Reverse Engineering (HOBRE) lies at the intersection of binary and source code, aiming to lift binary code to human-readable content relevant to source code,…
LOTUS: Evasive and Resilient Backdoor Attacks through Sub-Partitioning
Siyuan Cheng, Guanhong Tao, Yingqi Liu +7
Backdoor attack poses a significant security threat to Deep Learning applications. Existing attacks are often not evasive to established backdoor detection techniques. This suscept…
CodeArt: Better Code Models by Attention Regularization When Symbols Are Lacking
Zian Su, Xiangzhe Xu, Ziyang Huang +4
Transformer based code models have impressive performance in many software engineering tasks. However, their effectiveness degrades when symbols are missing or not informative. The…
LLMDFA: Analyzing Dataflow in Code with Large Language Models
Chengpeng Wang, Wuqi Zhang, Zian Su +3
Dataflow analysis is a fundamental code analysis technique that identifies dependencies between program values. Traditional approaches typically necessitate successful compilation…