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Softw. Eng. Methodol."],"published-print":{"date-parts":[[2025,11,30]]},"abstract":"\n Binary similarity involves determining whether two binary programs exhibit similar functionality with applications in vulnerability detection, malware analysis, and copyright detection. However, variations in compiler settings, target architectures, and deliberate code obfuscations significantly complicate the similarity measurement by effectively altering the syntax, semantics, and structure of the underlying binary. To address these challenges, we propose\n VexIR2Vec<\/jats:sc>\n , a robust, architecture-neutral approach based on VEX-IR to solve binary similarity tasks.\n VexIR2Vec<\/jats:sc>\n consists of three key components: a peephole extractor, a normalization engine (\n VexINE<\/jats:sc>\n ), and an embedding model (\n VexNet<\/jats:sc>\n ). The process to build program embeddings starts with the extraction of sequences of basic blocks, or\n peepholes<\/jats:italic>\n , from control-flow graphs via random walks, capturing structural information. These generated peepholes are then\n normalized<\/jats:italic>\n using\n VexINE<\/jats:sc>\n , which applies compiler-inspired transformations to reduce architectural and compiler-induced variations. Embeddings of peepholes are generated using representation learning techniques, avoiding Out-of-Vocabulary (OOV) issues. These embeddings are then fine-tuned with\n VexNet<\/jats:sc>\n , a feed-forward Siamese network that maps functions into a high-dimensional space for diffing and searching tasks in an application-independent manner.\n <\/jats:p>\n \n We evaluate\n VexIR2Vec<\/jats:sc>\n against five baselines\u2014BinDiff, DeepBinDiff, SAFE, BinFinder, and histograms of opcodes\u2014on a dataset comprising 2.7\n M<\/jats:italic>\n functions and 15.5\n K<\/jats:italic>\n binaries from 7 projects compiled across 12 compilers targeting x86 and ARM architectures. The experiments span four adversarial settings\u2014cross-optimization, cross-compilation, cross-architecture, and obfuscations\u2014that are typically exploited by malware and vulnerabilities. In diffing experiments,\n VexIR2Vec<\/jats:sc>\n outperforms the nearest baseline in these four scenarios by\n \n \\(40\\%\\)<\/jats:tex-math>\n <\/jats:inline-formula>\n ,\n \n \\(18\\%\\)<\/jats:tex-math>\n <\/jats:inline-formula>\n ,\n \n \\(21\\%\\)<\/jats:tex-math>\n <\/jats:inline-formula>\n , and\n \n \\(60\\%\\)<\/jats:tex-math>\n <\/jats:inline-formula>\n , respectively. In the searching experiment,\n VexIR2Vec<\/jats:sc>\n achieves a mean average precision of 0.76, the nearest baseline, by\n \n \\(46\\%\\)<\/jats:tex-math>\n <\/jats:inline-formula>\n . Our framework is highly scalable and is built as a lightweight, multi-threaded, parallel library using only open source tools.\n VexIR2Vec<\/jats:sc>\n is\n \n \\(\\approx 3.1\\)<\/jats:tex-math>\n <\/jats:inline-formula>\n \u2013\n \n \\(3.5\\times\\)<\/jats:tex-math>\n <\/jats:inline-formula>\n faster than the closest baselines and orders-of-magnitude faster than other tools.\n <\/jats:p>","DOI":"10.1145\/3721481","type":"journal-article","created":{"date-parts":[[2025,3,5]],"date-time":"2025-03-05T10:12:46Z","timestamp":1741169566000},"page":"1-54","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["VexIR2Vec<\/scp>\n : An Architecture-Neutral Embedding Framework for Binary Similarity"],"prefix":"10.1145","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1393-7321","authenticated-orcid":false,"given":"S.","family":"VenkataKeerthy","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad, Hyderabad, India"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5772-2469","authenticated-orcid":false,"given":"Soumya","family":"Banerjee","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad, Hyderabad, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4115-0588","authenticated-orcid":false,"given":"Sayan","family":"Dey","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad, Hyderabad, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1180-4197","authenticated-orcid":false,"given":"Yashas","family":"Andaluri","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad, Hyderabad, India"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3059-5025","authenticated-orcid":false,"given":"Raghul","family":"P. 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