A survey of binary code similarity
IU Haq, J Caballero - Acm computing surveys (csur), 2021 - dl.acm.org
Binary code similarityapproaches compare two or more pieces of binary code to identify their
similarities and differences. The ability to compare binary code enables many real-world …
similarities and differences. The ability to compare binary code enables many real-world …
Automatic vulnerability detection in embedded devices and firmware: Survey and layered taxonomies
In the era of the internet of things (IoT), software-enabled inter-connected devices are of
paramount importance. The embedded systems are very frequently used in both security …
paramount importance. The embedded systems are very frequently used in both security …
Devign: Effective vulnerability identification by learning comprehensive program semantics via graph neural networks
Vulnerability identification is crucial to protect the software systems from attacks for cyber
security. It is especially important to localize the vulnerable functions among the source code …
security. It is especially important to localize the vulnerable functions among the source code …
How machine learning is solving the binary function similarity problem
A Marcelli, M Graziano, X Ugarte-Pedrero… - 31st USENIX Security …, 2022 - usenix.org
The ability to accurately compute the similarity between two pieces of binary code plays an
important role in a wide range of different problems. Several research communities such as …
important role in a wide range of different problems. Several research communities such as …
Asm2vec: Boosting static representation robustness for binary clone search against code obfuscation and compiler optimization
Reverse engineering is a manually intensive but necessary technique for understanding the
inner workings of new malware, finding vulnerabilities in existing systems, and detecting …
inner workings of new malware, finding vulnerabilities in existing systems, and detecting …
Symlm: Predicting function names in stripped binaries via context-sensitive execution-aware code embeddings
Predicting function names in stripped binaries is an extremely useful but challenging task, as
it requires summarizing the execution behavior and semantics of the function in human …
it requires summarizing the execution behavior and semantics of the function in human …
Superion: Grammar-aware greybox fuzzing
In recent years, coverage-based greybox fuzzing has proven itself to be one of the most
effective techniques for finding security bugs in practice. Particularly, American Fuzzy Lop …
effective techniques for finding security bugs in practice. Particularly, American Fuzzy Lop …
Deepbindiff: Learning program-wide code representations for binary diffing
Binary diffing analysis quantitatively measures the differences between two given binaries
and produces fine-grained basic block matching. It has been widely used to enable different …
and produces fine-grained basic block matching. It has been widely used to enable different …
Neural machine translation inspired binary code similarity comparison beyond function pairs
Binary code analysis allows analyzing binary code without having access to the
corresponding source code. A binary, after disassembly, is expressed in an assembly …
corresponding source code. A binary, after disassembly, is expressed in an assembly …
Jtrans: Jump-aware transformer for binary code similarity detection
Binary code similarity detection (BCSD) has important applications in various fields such as
vulnerabilities detection, software component analysis, and reverse engineering. Recent …
vulnerabilities detection, software component analysis, and reverse engineering. Recent …