3 papers
cs.CR2026
Does Teaming-Up LLMs Improve Secure Code Generation? A Comprehensive Evaluation with Multi-LLMSecCodeEval
Bushra Sabir, Shigang Liu, Seung Ick Jang +6
Automatically generating source code from natural language using large language models (LLMs) is becoming common, yet security vulnerabilities persist despite advances in fine tuni…
cs.CR2024
From Solitary Directives to Interactive Encouragement! LLM Secure Code Generation by Natural Language Prompting
Shigang Liu, Bushra Sabir, Seung Ick Jang +5
Large Language Models (LLMs) have shown remarkable potential in code generation, making them increasingly important in the field. However, the security issues of generated code hav…
cs.CR2023
OptimShare: A Unified Framework for Privacy Preserving Data Sharing -- Towards the Practical Utility of Data with Privacy
M. A. P. Chamikara, Seung Ick Jang, Ian Oppermann +9
Tabular data sharing serves as a common method for data exchange. However, sharing sensitive information without adequate privacy protection can compromise individual privacy. Thus…