7 citations · 9 across the 3 of their papers we have counts for
4 papers
On the Effectiveness of Instruction-Tuning Local LLMs for Identifying Software Vulnerabilities
Sangryu Park, Gihyuk Ko, Homook Cho
Large Language Models (LLMs) show significant promise in automating software vulnerability analysis, a critical task given the impact of security failure of modern software systems…
Unsupervised Detection of Adversarial Examples with Model Explanations
Gihyuk Ko, Gyumin Lim
Deep Neural Networks (DNNs) have shown remarkable performance in a diverse range of machine learning applications. However, it is widely known that DNNs are vulnerable to simple ad…
Proxy Non-Discrimination in Data-Driven Systems
Anupam Datta, Matt Fredrikson, Gihyuk Ko +2
Machine learnt systems inherit biases against protected classes, historically disparaged groups, from training data. Usually, these biases are not explicit, they rely on subtle cor…
Use Privacy in Data-Driven Systems: Theory and Experiments with Machine Learnt Programs
Anupam Datta, Matthew Fredrikson, Gihyuk Ko +2
This paper presents an approach to formalizing and enforcing a class of use privacy properties in data-driven systems. In contrast to prior work, we focus on use restrictions on pr…