“学萃讲坛”第699期--More semantics more robustness: improving Android malware classifiers
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报告题目：More semantics more robustness: improving Android malware classifiers
报告人：Dr. Wei Chen
报告时间：2017年11月4日 上午9:30
报告地点：21#楼426多媒体教室
主办单位：科学技术研究院
承办单位：计算机科学与技术学院
报告内容：Machine learning based malware classifiers often perform badly on detecting new malware, that is, their robustness is poor. This research takes Android apps as vehicle, investigates popular syntax-based features, some semantics-based features, and compares performance of classifiers combining popular machine learning methods and these features. We reveal one important reason affecting the robustness of malware classifiers: they do not capture general behavioural patterns of identified malware. One conclusion is: by using semantics-based features which are often hard to compute, i.e., sequences of API calls, the robustness of malware classifiers can be improved dramatically.
报告人简介：Dr. Wei Chen, a Research Associate in School of Informatics at University of Edinburgh UK since 2013. He graduated from Nanjing University of Science and Technology China, obtained MSc and PhD respectively from Tsinghua University China and University of Nottingham UK. Wei used to work in Institute of Informatics at Ludwig-Maximillian University Munich Germany, Shenzhen Huawei Technology Ltd., and Shanghai Alcatel-Bell Ltd. His main research interest includes: formal methods, software verification, theorem proving, type theory, and computer security. Wei’s current research direction is: applying formal methods and machine learning methods in communication and mobile security.
