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 …

Automatic vulnerability detection in embedded devices and firmware: Survey and layered taxonomies

A Qasem, P Shirani, M Debbabi, L Wang… - ACM Computing …, 2021 - dl.acm.org
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 …

Devign: Effective vulnerability identification by learning comprehensive program semantics via graph neural networks

Y Zhou, S Liu, J Siow, X Du… - Advances in neural …, 2019 - proceedings.neurips.cc
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 …

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 …

Asm2vec: Boosting static representation robustness for binary clone search against code obfuscation and compiler optimization

SHH Ding, BCM Fung… - 2019 ieee symposium on …, 2019 - ieeexplore.ieee.org
Reverse engineering is a manually intensive but necessary technique for understanding the
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

X Jin, K Pei, JY Won, Z Lin - Proceedings of the 2022 ACM SIGSAC …, 2022 - dl.acm.org
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 …

Superion: Grammar-aware greybox fuzzing

J Wang, B Chen, L Wei, Y Liu - 2019 IEEE/ACM 41st …, 2019 - ieeexplore.ieee.org
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 …

Deepbindiff: Learning program-wide code representations for binary diffing

Y Duan, X Li, J Wang, H Yin - 2020 - ink.library.smu.edu.sg
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 …

Neural machine translation inspired binary code similarity comparison beyond function pairs

F Zuo, X Li, P Young, L Luo, Q Zeng… - arXiv preprint arXiv …, 2018 - arxiv.org
Binary code analysis allows analyzing binary code without having access to the
corresponding source code. A binary, after disassembly, is expressed in an assembly …

Jtrans: Jump-aware transformer for binary code similarity detection

H Wang, W Qu, G Katz, W Zhu, Z Gao, H Qiu… - Proceedings of the 31st …, 2022 - dl.acm.org
Binary code similarity detection (BCSD) has important applications in various fields such as
vulnerabilities detection, software component analysis, and reverse engineering. Recent …