時間：2019年12月25日下午14:30-15:30

地點：88858cc永利官网綜合樓401

報告題目：Deep Learning for Practical Program Analysis

報告人：Shiqi Shen, National University of Singapore (沈詩琦，新加坡國立大學)

報告人簡介：

Shiqi Shen is a Ph.D. student in the School of Computing at National University of Singapore (NUS). Her research interests include software security, program analysis and security in machine learning. During her Ph.D., she has published many high-quality peer-reviewed research papers in well-regarded security conference proceedings (e.g., CCS, Usenix and NDSS).

報告摘要：

Program analysis is a classical problem in computer security. It analyzes the behaviors of software which are essential for multiple security applications such as hardening, bug-finding, clone detection and program repair. However, developing practical program analysis techniques that scale to real-world programs and automatically adapt to a given platform/language is challenging. To address these challenges, I investigate an alternative line of research, which utilizes the existing advance in machine learning to enhance state-of-the-art program analysis techniques. To show the effectiveness and generality of machine learning approaches, I evaluate it on two different scenarios: type recovery and symbolic execution. The evaluation results demonstrate that the machine learning approaches significantly improve the existing techniques in terms of efficiency, accuracy and adaptability.

邀請人：彭國軍教授