Advancements of Data Anomaly Detection Research in Wireless Sensor Networks: A Survey and Open Issues
Published 2013 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Advancements of Data Anomaly Detection Research in Wireless Sensor Networks: A Survey and Open Issues
Authors
Keywords
-
Journal
SENSORS
Volume 13, Issue 8, Pages 10087-10122
Publisher
MDPI AG
Online
2013-08-07
DOI
10.3390/s130810087
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Scalable Hypergrid k-NN-Based Online Anomaly Detection in Wireless Sensor Networks
- (2013) Miao Xie et al. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
- Distributed online outlier detection in wireless sensor networks using ellipsoidal support vector machine
- (2012) Yang Zhang et al. Ad Hoc Networks
- An adaptive and efficient dimension reduction model for multivariate wireless sensor networks applications
- (2012) Murad A. Rassam et al. APPLIED SOFT COMPUTING
- Ensemble based sensing anomaly detection in wireless sensor networks
- (2012) Daniel-Ioan Curiac et al. EXPERT SYSTEMS WITH APPLICATIONS
- Statistics-based outlier detection for wireless sensor networks
- (2012) Y. Zhang et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- Streaming analysis in wireless sensor networks
- (2012) Masud Moshtaghi et al. WIRELESS COMMUNICATIONS & MOBILE COMPUTING
- Spatiotemporal Models for Data-Anomaly Detection in Dynamic Environmental Monitoring Campaigns
- (2011) Ethan W. Dereszynski et al. ACM Transactions on Sensor Networks
- Anomaly Detection in Environmental Monitoring Networks [Application Notes]
- (2011) James Bezdek et al. IEEE Computational Intelligence Magazine
- Anomaly detection in wireless sensor networks: A survey
- (2011) Miao Xie et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- Elliptical anomalies in wireless sensor networks
- (2010) Sutharshan Rajasegarar et al. ACM Transactions on Sensor Networks
- Sensor faults
- (2010) Abhishek B. Sharma et al. ACM Transactions on Sensor Networks
- A collaborative event detection scheme using fuzzy logic in clustered wireless sensor networks
- (2010) Kieu-Xuan Thuc et al. AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS
- Pattern recognition for detecting distributed node exhaustion attacks in wireless sensor networks
- (2010) Z.A. Baig COMPUTER COMMUNICATIONS
- The Internet of Things: A survey
- (2010) Luigi Atzori et al. Computer Networks
- Outlier Detection Techniques for Wireless Sensor Networks: A Survey
- (2010) Yang Zhang et al. IEEE Communications Surveys and Tutorials
- Centered Hyperspherical and Hyperellipsoidal One-Class Support Vector Machines for Anomaly Detection in Sensor Networks
- (2010) Sutharshan Rajasegarar et al. IEEE Transactions on Information Forensics and Security
- Clustering ellipses for anomaly detection
- (2010) Masud Moshtaghi et al. PATTERN RECOGNITION
- Online anomaly detection for sensor systems: A simple and efficient approach
- (2010) Yuan Yao et al. PERFORMANCE EVALUATION
- Ensuring high sensor data quality through use of online outlier detection techniques
- (2010) Yang Zhang et al. International Journal of Sensor Networks
- Anomaly detection
- (2009) Varun Chandola et al. ACM COMPUTING SURVEYS
- Sensor network data fault types
- (2009) Kevin Ni et al. ACM Transactions on Sensor Networks
- Distributed detection of replica node attacks with group deployment knowledge in wireless sensor networks
- (2009) Jun-Won Ho et al. Ad Hoc Networks
- Sensor network security: a survey
- (2009) Xiangqian Chen et al. IEEE Communications Surveys and Tutorials
- Wireless sensor network survey
- (2008) Jennifer Yick et al. Computer Networks
- Anomaly detection in wireless sensor networks
- (2008) S. Rajasegarar et al. IEEE WIRELESS COMMUNICATIONS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started