Comparing Unidirectional, Bidirectional, and Word2vec Models for Discovering Vulnerabilities in Compiled Lifted Code

Ransomware and other forms of malware cause significant financial and operational damage to organizations by exploiting long-standing and often difficult-to-detect software vulnerabilities. To detect vulnerabilities such as buffer overflows in compiled code, this research investigates the applicatio...

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Vydané v:	Proceedings (International Symposium on Digital Forensic and Security. Online) s. 1 - 6
Hlavní autori:	McCully, Gary A., Hastings, John D., Xu, Shengjie, Fortier, Adam
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 24.04.2025
Predmet:	Accuracy Bidirectional control Binary Security Buffer Over-flows Codes Encoding GPT-2 Long short term memory Machine Learning Neural networks Organizations Recurrent neural networks Training Transformers Unidirectional Encoders
ISSN:	2768-1831
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