【学术报告】Robust Deep Learning Against Deception

编辑:刘雨 来源:计算机科学与技术学院 时间:2019年10月09日 访问次数:10  源地址

主讲人:Ling Liu教授

时间:20191015日(周二)上午 1000~1100





We are entering an exciting era where human intelligence is being enhanced by big data fueled artificial intelligence (AI) and machine learning (ML). However, recent work shows that deep learning as a service may be vulnerable to adversarial inputs to the privately trained deep neural network (DNN) models even with only a black-box access to the prediction API. Such adversarial inputs inject small amount of perturbations to the input data to fool machine learning models to misbehave, turning a deep neural network against itself. As new defense methods are proposed, more sophisticated attack algorithms are surfaced. With more mission critical systems incorporating machine learning and AI as an essential component in our social, cyber, and physical systems, understanding and ensuring the verifiable robustness of deep learning becomes a pressing challenge. This talk provides a comprehensive analysis and characterization of the state of art attacks and defenses and highlight our recent research approaches towards guaranteeing robustness of deep learning as a service.


Ling Liu教授

Prof. Dr. Ling Liu is a Professor in the School of Computer Science at Georgia Institute of Technology. She directs the research programs in Distributed Data Intensive Systems Lab (DiSL), examining various aspects of large-scale data intensive systems. Prof. Liu is an internationally recognized expert in the areas of Big Data Systems and Analytics, Distributed Systems, Database and Storage Systems, Internet Computing, Privacy, Security and Trust. Prof. Liu has published over 300 international journal and conference articles, and is a recipient of the best paper award from a number of top venues, including ICDCS, WWW, Pat Goldberg Memorial Best Paper Award, IEEE CLOUD, IEEE ICWS, ACM/IEEE CCGrid 2015, IEEE Edge. Prof. Liu is an elected IEEE Fellow and a recipient of IEEE Computer Society Technical Achievement Award. Prof. Liu has served as the editor in chief of IEEE Transactions on Services Computing from 2013-2016, the program chairs of numerous IEEE and ACM conferences in the fields of big data, cloud computing, data engineering, distributed computing, very large databases, including the co-PC chair of The Web 2019 (WWW 2019). Currently, Prof. Liu is serving as the Editor in Chief of ACM Transactions on Internet Technology (TOIT). Prof. Liu’s research is primarily sponsored by NSF, IBM and Intel.