Distance Based Method for Outlier Detection of Body Sensor Networks
Distance Based Method for Outlier Detection of Body Sensor Networks
复制标题
基于距离的人体传感器网络异常检测方法
DOI:
10.4108/eai.19-1-2016.151000
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发表时间:
2016-01
期刊:
影响因子:
--
通讯作者:
Cheng Zhao
中科院分区:
文献类型:
--
作者:
Haibin Zhang;Jiajia Liu;Cheng Zhao
We propose a distance based method for the outlier detection of body sensor networks. Firstly, we use a Kernel Density Estimation (KDE) to calculate the probability of the distance to k nearest neighbors for diagnosed data. If the probability is less than a threshold, and the distance of this data to its left and right neighbors is greater than a pre-defined value, the diagnosed data is decided as an outlier. Further, we formalize a sliding window based method to improve the outlier detection performance. Finally, to estimate the KDE by training sensor readings with errors, we introduce a Hidden Markov Model (HMM) based method to estimate the most probable ground truth values which have the maximum probability to produce the training data. Simulation results show that the proposed method possesses a good detection accuracy with a low false alarm rate. Received on 19 September 2015; accepted on 24 November 2015; published on 19 January 2016
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DOI:
10.1007/s11431-013-5451-7
发表时间:
2014-03
期刊:
Science in China - Series E: Technological Sciences
影响因子:
--
作者:
Chen YiMin;Zi YanYang;Cao HongRui;He ZhengJia;Sun HaiLiang
通讯作者:
Sun HaiLiang
DOI:
10.1109/icct.2013.6820415
发表时间:
2013-11
期刊:
2013 15th IEEE International Conference on Communication Technology
影响因子:
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Kun Niu;Fang Zhao;Xiuquan Qiao
DOI:
10.1109/iccs.2006.301508
发表时间:
2006
期刊:
2006 10th IEEE Singapore International Conference on Communication Systems
影响因子:
--
作者:
Sutharshan Rajasegarar;C. Leckie;M. Palaniswami;J. Bezdek
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DOI:
10.1109/5326.897073
发表时间:
2000-11-01
期刊:
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS
影响因子:
--
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Ying, J;Kirubarajan, T;Patterson-Hine, A
通讯作者:
Patterson-Hine, A
影响因子:
3.7
作者:
Krishnamachari, B;Iyengar, S
通讯作者:
Iyengar, S