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Published in 2023 IEEE Conference on Communications and Network Security (CNS), 2023
In this study, we uncovered the inherent vulnerabilities in deep learning based steganogaphic systems, and proposed simple shuffling based solution to mitigate that.
Published in arxiv, 2024
We quantified the updatedness of dependencies and updatedness of vulnerable dependencies in the context of open source dependencies in this project. The idea is very common in Reliability domain (e.g., Mean-Time-To-Update, Mean-Time-To-Repair, Mean-Time-To-Remediate). We did a large-scale study of our proposed update metrics in NPM, PyPI, and Cargo packages.
Published in arxiv, 2024
We made a list of Security Sensitive APIs in Java using JDK documentation, past CVE fixes, and CWE examples. We then measured the prevalence of these Security-Sensitive API usage in our chosen 45 Java packages and in their dependencies. We finally conducted a developer survey to validate whether security-sensitive API information can be helpful in selecting dependencies.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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