2021/08/27 by İbrahim Meşecan, Mesecan, Ibrahim, Daniel J. Blackwell +7 · 1 citation
Computer Science · #Advanced Malware Detection Techniques #Cryptography and Security (cs.CR) #Digital and Cyber Forensics #FOS: Computer and information sciences #Security and Verification in Computing #Software Engineering (cs.SE)
paper · pdf · doi:10.48550/arxiv.2108.12075
openalex publication_date 2021/08/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Maintaining confidential information control in software is a persistent security problem where failure means secrets can be revealed via program behaviors. Information flow control techniques traditionally have been based on static or symbolic analyses -- limited in scalability and specialized to particular languages. When programs do leak secrets there are no approaches to automatically repair them unless the leak causes a functional test to fail. We present our vision for HyperGI, a genetic improvement framework tha detects, localizes and repairs information leakage. Key elements of HyperGI include (1) the use of two orthogonal test suites, (2) a dynamic leak detection approach which estimates and localizes potential leaks, and (3) a repair component that produces a candidate patch using genetic improvement. We demonstrate the successful use of HyperGI on several programs which have no failing functional tests. We manually examine the resulting patches and identify trade-offs and future directions for fully realizing our vision.