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Quick and Accurate False Data Detection in Mobile Crowd Sensing

主讲人 :Xin Wang教授 地点 :新科研楼610会议室 开始时间 : 2019-07-12 14:00 结束时间 : 2019-07-10 15:00

报告摘要:

With the proliferation of smartphones, a novel sensing paradigm called Mobile Crowd Sensing (MCS) has emerged very recently. However, the attacks and faults in MCS cause a serious false data problem. Observing the intrinsic low dimensionality of general monitoring data and the sparsity of false data, false data detection can be performed based on the separation of normal data and anomalies. Although the existing separation algorithm based on Direct Robust Matrix Factorization (DRMF) is proven to be effective, requiring iteratively performing Singular Value Decomposition (SVD) for low rank matrix approximation would result in a prohibitively high accumulated computation cost when the data matrix is large. In this work, we observe the quick false data location feature from our empirical study of DRMF, based on which we propose an intelligent Light weight Low Rank and False Matrix Separation algorithm (LightLRFMS) that can reuse the previous result of the matrix decomposition to deduce the one for the current iteration step. Our algorithm can largely speed up the whole iteration process. with up to 10 times the speed of DRMF.

 

主讲人简介:

Dr. Wang is currently the director of the Wireless Networking and Systems lab of the department of Electrical and Computer Engineering of the State University of New York (SUNY) at Stony Brook. Prior to joining Stony Brook university, she was a faculty in the department of computer science and engineering of SUNY at Buffalo between 2003 and 2005, and was a Member of Technical Staff in the area of mobile and wireless networking at Bell Labs Research, Lucent Technologies, New Jersey between 2001 and 2003. While in Bell-Labs, she served as the QoS subsystem architect for the Lucent Imminent Content Switch project, cross-team consultant for Lucent Metro Ethernet Project, and technical lead in QoS management in Lucent 3G Radio Network Controller project.

Dr. Wang has been conducting and leading research work in the design of network architectures, protocols and algorithms.  Her research areas have expanded from the core Internet research, to the current focus on wireless network infrastructure design with the major goals of significantly improving the wireless network capacity, reliability, and scalability, supporting advanced wireless applications and services. Her interest areas also include mobile cloud computing and distributed computing, and networked sensing, detection, and data fusion. She current serves as an associate editor of IEEE Transactions of Mobile Computing. She also serves TPC chair or program committee members in many technical conferences, including ACM MobiCom, IEEE Infocom, IEEE ICDCS, and IEEE PerCom. Her research group has published more than 100 papers in highly reputed conferences and journals, including ACM Sigmetrics, ACM MobiCom, USENIX NSDI, IEEE ICNP, IEEE Infocom, IEEE ICDCS, IEEE Percom, IEEE TON, IEEE TMC, IEEE JSAC, IEEE TC, and IEEE TDSC.

Dr. Wang obtained her PhD from Columbia University, BS and MS from Beijing University of Post and Telecommunications, respectively. She is a recipient of NSF career award in 2005 and the ONR Chief of Naval Research (CNR) Challenge award in 2011.

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