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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 …
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
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 …
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 …
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 …
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
Binary code similarity detection (BCSD) is utilized in various critical areas such as malware
detection, vulnerability search, software version control, reverse engineering, digital …
detection, vulnerability search, software version control, reverse engineering, digital …