4 papers
Impact of Data Snooping on Deep Learning Models for Locating Vulnerabilities in Lifted Code
Gary A. McCully, John D. Hastings, Shengjie Xu
This study examines the impact of data snooping on neural networks used to detect vulnerabilities in lifted code, and builds on previous research that used word2vec and unidirectio…
Comparing Unidirectional, Bidirectional, and Word2vec Models for Discovering Vulnerabilities in Compiled Lifted Code
Gary A. McCully, John D. Hastings, Shengjie Xu +1
Ransomware and other forms of malware cause significant financial and operational damage to organizations by exploiting long-standing and often difficult-to-detect software vulnera…
Bi-Directional Transformers vs. word2vec: Discovering Vulnerabilities in Lifted Compiled Code
Gary A. McCully, John D. Hastings, Shengjie Xu +1
Detecting vulnerabilities within compiled binaries is challenging due to lost high-level code structures and other factors such as architectural dependencies, compilers, and optimi…
Confronting the Reproducibility Crisis: A Case Study of Challenges in Cybersecurity AI
Richard H. Moulton, Gary A. McCully, John D. Hastings
In the rapidly evolving field of cybersecurity, ensuring the reproducibility of AI-driven research is critical to maintaining the reliability and integrity of security systems. Thi…