When Ying Zhang was a doctoral student at Virginia Tech, she spent years learning to think like an attacker—probing software ...
This artifact includes the code to reproduce our experiments on DeepDFA, LineVul, and LineVul+DeepDFA, accepted at ICSE 2024. This constitutes a large part of the research prototype, with other ...
Abstract: Software vulnerability can cause disastrous consequences for information security. Earlier detection of vulnerabilities minimizes these consequences. Manual detection of vulnerable code is ...
Abstract: With the increasing use of smart contracts, vulnerabilities have become a critical concern, making intelligent vulnerability detection increasingly essential. Deep learning offers a ...
The proliferation of dApps is increasing the attack surface for exploitable vulnerabilities in smart contracts, and thus there is a need for verifiable detection methodologies. The Random Forest ...
An understanding of community resilience and risk analysis is vital when it comes to protecting civilians and infrastructure from natural hazards, such as hurricanes or earthquakes. Artificial ...
A recently disclosed vulnerability in Google’s Gemini AI panel could have allowed hackers to hijack the feature and access sensitive data on a user’s device. Researchers at Palo Alto Networks’ Unit 42 ...
Using graph neural networks and open-source repositories to detect code vulnerabilities. This is an implementation of the model described in: "Combining Graph-based Learning with Automated Data ...
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