Control Flow Obfuscation using Neural Network to Fight Concolic Testing

• Main Authors: Ma, Haoyu, Ma, Xinjie, Liu, Weijie, Huang, Zhipeng, GAO, Debin, Jia, Chunfu
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2014
• Subjects: Software obfuscation; malware analysis; reverse engineering; concolic testing; neural network; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/2260; https://ink.library.smu.edu.sg/context/sis_research/article/3260/viewcontent/GaoDControlFlowObfuscationsecurecomm14.pdf
• Institution: Singapore Management University

Concolic testing is widely regarded as the state-of-the-art technique in dynamic discovering and analyzing trigger-based behavior in software programs. It uses symbolic execution and an automatic theorem prover to generate new concrete test cases to maximize code coverage for scenarios like software...