Binary Similarity Detection Using Machine Learning
Author:
Affiliation:
1. Cornell Tech, New York, NY, USA
2. Forah Inc., Tel-Aviv, Israel
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3264820.3264821
Reference18 articles.
1. Statistical similarity of binaries
2. Similarity of binaries through re-optimization
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1. CEBin: A Cost-Effective Framework for Large-Scale Binary Code Similarity Detection;Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis;2024-09-11
2. AIMFuzz: Automated Function-Level In-Memory Fuzzing on Binaries;Proceedings of the 19th ACM Asia Conference on Computer and Communications Security;2024-07
3. A Survey of Binary Code Similarity Detection Techniques;Electronics;2024-04-29
4. GraphMoCo: A graph momentum contrast model for large-scale binary function representation learning;Neurocomputing;2024-03
5. Optir-SBERT: Cross-Architecture Binary Code Similarity Detection Based on Optimized LLVM IR;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2024
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