BinAIV: Semantic-enhanced vulnerability detection for Linux x86 binaries

Y Gu, H Shu, F Kang - Computers & Security, 2023 - Elsevier
Binary code vulnerability detection is an important research direction in the field of network
security. The extensive reuse of open-source code has led to the spread of vulnerabilities …

MalGNE: Enhancing the performance and efficiency of cfg-based malware detector by graph node embedding in low dimension space

H Peng, J Yang, D Zhao, X Xu, Y Pu… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
The rich semantic information in Control Flow Graphs (CFGs) of executable programs has
made Graph Neural Networks (GNNs) a key focus for malware detection. However, existing …

Binary Program Vulnerability Mining Based on Neural Network.

Z Li, S **ng, L Yu, H Li, F Zhou, G Yin… - Computers …, 2024 - search.ebscohost.com
Software security analysts typically only have access to the executable program and cannot
directly access the source code of the program. This poses significant challenges to security …

SimCoDe-NET: Similarity Detection in Binary Code using Deep Learning Network

S Poornima, R Mahalakshmi - International Journal of …, 2024 - ijeer.forexjournal.co.in
Binary code similarity detection is a fundamental task in the field of computer binary security.
However, code similarity is crucial today because of the prevalence of issues like plagiarism …

CrossDeep: A Hybrid Approach For Cross Version Binary Code Similarity Detection

M Nandish, J Kumar, HG Mohan - 2024 Fourth International …, 2024 - ieeexplore.ieee.org
Binary code similarity detection (BCSD) is utilized in various critical areas such as malware
detection, vulnerability search, software version control, reverse engineering, digital …