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PhD Thesis Proposal - Adriana Sejfia

PhD Thesis Proposal - Adriana Sejfia

Committee Members: Nenad Medvidovic (chair), Chao Wang, William Halfond, Mukund Raghothaman, Sandeep Gupta, and Jyotirmoy Deshmukh

Title: Systematic Improvement of Deep Learning Based Vulnerability Detection

Abstract: Deep learning based techniques have gained traction in software vulnerability detection. However, the performance of these techniques in data drawn from distributions other than the ones the models have been explicitly trained on has been shown to vary a lot. In this talk, I will present our study on four limitations of the current deep learning based vulnerability detectors and the datasets they use along with solutions we propose to address these limitations

Audiences: Everyone Is Invited

Contact: Melissa Ochoa

Event Link: https://usc.zoom.us/j/97573523067?pwd=aW94cUlkM3IwZmk5L3E2a1ZTTG9SUT09

This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.

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