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Quick and Accurate False Data Detection in Mobile Crowd Sensing

文献类型：期刊论文

作者Li, Xiaocan2; Xie, Kun1,2,3; Wang, Xin4; Xie, Gaogang5,6; Xie, Dongliang7; Li, Zhenyu8,9; Wen, Jigang5; Diao, Zulong3,8; Wang, Tian10
刊名IEEE-ACM TRANSACTIONS ON NETWORKING
出版日期2020-06-01
卷号28期号:3页码:1339-1352
ISSN号1063-6692
关键词Sparse matrices Sensors Matrix decomposition Monitoring Principal component analysis Robustness Wireless sensor networks Matrix separation false data detection mobile crowd sensing
DOI10.1109/TNET.2020.2982685
英文摘要The attacks, faults, and severe communication/system conditions in Mobile Crowd Sensing (MCS) make false data detection a critical 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. Depending on the type of data corruption, random or successive/mass, we design two versions of LightLRFMS. From a theoretical perspective, we validate that LightLRFMS only requires one round of SVD computation and thus has very low computation cost. We have done extensive experiments using a PM 2.5 air condition trace and a road traffic trace. Our results demonstrate that LightLRFMS can achieve very good false data detection performance with the same highest detection accuracy as DRMF but with up to 20 times faster speed thanks to its lower computation cost.
资助项目National Natural Science Foundation of China[61972144] ; National Natural Science Foundation of China[61572184] ; National Natural Science Foundation of China[61725206] ; National Natural Science Foundation of China[61976087] ; Hunan Provincial Natural Science Foundation of China[2017JJ1010] ; U.S. NSF[ECCS 78929] ; U.S. NSF[CNS 1526843] ; Open Project Funding of State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences[CARCH201809] ; CERNET Innovation Project[NGII20190118] ; Open Foundation of State key Laboratory of Networking and Switching Technology (Beijing University of Posts and Telecommunications)[SKLNST-2018-1-20] ; Peng Cheng Laboratory Project of Guangdong Province[PCL2018KP004]
WOS研究方向Computer Science ; Engineering ; Telecommunications
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000544036100028
源URL[http://119.78.100.204/handle/2XEOYT63/15063]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Xie, Kun
作者单位1.Peng Cheng Lab, Cyberspace Secur Res Ctr, Shenzhen 518000, Peoples R China
2.Hunan Univ, Coll Comp Sci & Elect Engn, Changsha 410082, Peoples R China
3.Purple Mt Lab, Nanjing 211111, Peoples R China
4.SUNY Stony Brook, Dept Elect & Comp Engn, Stony Brook, NY 11794 USA
5.Chinese Acad Sci, Comp Network Informat Ctr, Beijing 100190, Peoples R China
6.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing 100190, Peoples R China
7.Beijing Univ Posts & Telecommun, Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China
8.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
9.Taobao Com, Beijing 100102, Peoples R China
10.Huaqiao Univ, Coll Comp Sci & Technol, Quanzhou 362021, Peoples R China
推荐引用方式
GB/T 7714		 Li, Xiaocan,Xie, Kun,Wang, Xin,et al. Quick and Accurate False Data Detection in Mobile Crowd Sensing[J]. IEEE-ACM TRANSACTIONS ON NETWORKING,2020,28(3):1339-1352.
APA Li, Xiaocan.,Xie, Kun.,Wang, Xin.,Xie, Gaogang.,Xie, Dongliang.,...&Wang, Tian.(2020).Quick and Accurate False Data Detection in Mobile Crowd Sensing.IEEE-ACM TRANSACTIONS ON NETWORKING,28(3),1339-1352.
MLA Li, Xiaocan,et al."Quick and Accurate False Data Detection in Mobile Crowd Sensing".IEEE-ACM TRANSACTIONS ON NETWORKING 28.3(2020):1339-1352.

入库方式： OAI收割

来源：计算技术研究所

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