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Huangyi Ge

Researcher at Purdue University

Publications -  16
Citations -  183

Huangyi Ge is an academic researcher from Purdue University. The author has contributed to research in topics: Selection (genetic algorithm) & Software bug. The author has an hindex of 5, co-authored 16 publications receiving 137 citations. Previous affiliations of Huangyi Ge include Memorial Sloan Kettering Cancer Center.

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Journal ArticleDOI

P3DB 3.0: From plant phosphorylation sites to protein networks

TL;DR: The new P3DB reflects a community-based design through which users can share datasets and automate data depository processes for publication purposes, and incorporates multiple network viewers for the above features, such as PPI network, kinase-substrate network, phosphatase- substrate network and domain co-occurrence network to help study phosphorylation from a systems point of view.
Proceedings ArticleDOI

SymCerts: Practical Symbolic Execution for Exposing Noncompliance in X.509 Certificate Validation Implementations

TL;DR: It is observed that symbolic execution, a technique proven to be effective in finding software implementation flaws, can also be leveraged to expose noncompliance in X.509 implementations.
Journal ArticleDOI

Influence of privacy priming and security framing on mobile app selection

TL;DR: It is shown that priming can be accomplished with a single item, which holds promise for real-world applications, and although the participants relied heavily on user ratings to guide their app selections, both the self-relevant and factual priming items induced the participants to take safety more into account.
Journal ArticleDOI

Cybersecurity for Android Applications: Permissions in Android 5 and 6

TL;DR: Although a pilot study showed that users favored the Android 6 permissions interface over Android 5’s, the present study found no clear evidence that it was more effective than Android 5.
Proceedings ArticleDOI

Koinonia: verifiable e-voting with long-term privacy

TL;DR: Koinonia is designed and implemented, a voting system that provides long-term privacy against powerful adversaries and enables anyone to verify that each ballot is well-formed and the tallying is done correctly and argues that secret-sharing based voting protocols offer a more natural and elegant privacy-preserving solution than their encryption-based counterparts.