MSSA: multi-stage semantic-aware neural network for binary code similarity detection
Binary code similarity detection (BCSD) aims to identify whether a pair of binary code snippets is similar, which is widely used for tasks such as malware analysis, patch analysis, and clone detection. Current state-of-the-art approaches are based on Transformer, which require substantial computatio...
Saved in:
Main Authors: | Bangrui Wan, Jianjun Zhou, Ying Wang, Feng Chen, Ying Qian |
---|---|
Format: | Article |
Language: | English |
Published: |
PeerJ Inc.
2025-01-01
|
Series: | PeerJ Computer Science |
Subjects: | |
Online Access: | https://peerj.com/articles/cs-2504.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Uncertainty-based quantization method for stable training of binary neural networks
by: A.V. Trusov, et al.
Published: (2024-08-01) -
Vehicle classification algorithm based on binary proximity sensors and neural networks
by: ZHANG Wei, et al.
Published: (2008-01-01) -
Brain-model neural similarity reveals abstractive summarization performance
by: Zhejun Zhang, et al.
Published: (2025-01-01) -
Robust multi-source geographic entities matching by maximizing geometric and semantic similarity
by: YuHan Yan, et al.
Published: (2024-12-01) -
Similar handwritten Chinese character recognition based on deep neural networks with big data
by: Zhao YANG, et al.
Published: (2014-09-01)