Online citations, reference lists, and bibliographies.

DOI: 10.1002/cpe.3338

Dynamic Malicious Node Detection With Semi‐supervised Multivariate Classification In Cognitive Wireless Sensor Networks

Hongjun Dai, Huabo Liu, Z. Jia

Published 2015 · Computer Science

Cite This

Download PDF

Analyze on Scholarcy

Share

Usually, wireless sensor networks are distributed massively with a number of nodes in an open large‐scale environment, and they are vulnerable to malicious attacks because the communications change dynamically and unpredictably. In this paper, we present a detection method based on multivariate classification to find out the malicious sensor nodes. It learns the features of a few type‐known node, classifies them with dynamical multivariate classification, and then establishes the sample space of all sensor nodes in the network activities to deduce the malicious nodes. The experiment results show that as long as the value of sensor node preferences and the number of active sensor nodes is stable, the false detection rate is stabilized below 0.5%. This proves that the algorithm can be used to the cognitive wireless sensor networks widely. Copyright © 2014 John Wiley & Sons, Ltd.

This paper references

10.1016/j.asoc.2012.11.041

An adaptive and efficient dimension reduction model for multivariate wireless sensor networks applications

Murad A. Rassam (2013)

10.1109/MC.2002.1039518

Denial of Service in Sensor Networks

10.1109/TCOMM.2012.031912.110179

Hierarchical Trust Management for Wireless Sensor Networks and its Applications to Trust-Based Routing and Intrusion Detection

Some properties of a classification system for multivariate life distributions

10.1109/MNET.2009.4804323

A simple and efficient hidden Markov model scheme for host-based anomaly intrusion detection

Hatzinakos D. Ensemble empirical mode decomposition for time Goel G (2014)

10.1002/wcm.422

Security in wireless sensor networks

V. C. Giruka (2008)

10.1145/345910.345953

GPSR: greedy perimeter stateless routing for wireless networks

10.1109/GLOCOM.2008.ECP.408

A Machine Learning Based Reputation System for Defending Against Malicious Node Behavior

R. Akbani (2008)

10.1109/JSEN.2012.2192425

Semi-Supervised Learning Techniques in Artificial Olfaction: A Novel Approach to Classification Problems and Drift Counteraction

S. De Vito (2012)

10.1109/JPROC.2010.2068530

Environmental Wireless Sensor Networks

P. Corke (2010)

10.1145/2491288.2491289

Balancing lifetime and classification accuracy of wireless sensor networks

Kush R. Varshney (2013)

10.1109/TDSC.2009.48

Cross-Layer Detection of Sinking Behavior in Wireless Ad Hoc Networks Using SVM and FDA

J. Joseph (2011)

10.1109/MCSA.1999.749281

Ad-hoc on-demand distance vector routing

C. Perkins (1999)

10.1109/INFCOM.2007.225

Insider Attacker Detection in Wireless Sensor Networks

Anomaly Detection in Wireless Sensor Networks

Miao Xie (2013)

10.1109/MNET.2011.5772056

Packet traffic: a good data source for wireless sensor network modeling and anomaly detection

Qinghua Wang (2011)

10.1109/TC.2012.229

MuSA: Multivariate Sampling Algorithmfor Wireless Sensor Networks

André L. L. de Aquino (2014)

10.1109/TDSC.2011.65

ZoneTrust: Fast Zone-Based Node Compromise Detection and Revocation in Wireless Sensor Networks Using Sequential Hypothesis Testing

Jun-Won Ho (2012)

10.1109/ICCNC.2014.6785403

Ensemble Empirical Mode Decomposition for time series prediction in wireless sensor networks

10.1109/JSEN.2010.2052033

Cognition in Wireless Sensor Networks: A Perspective

G. Vijay (2011)

10.1109/TNET.2011.2163730

Topological detection on wormholes in wireless ad hoc and sensor networks

Dezun Dong (2009)

10.1109/IPDPS.2004.1302934

Malicious node detection in wireless sensor networks

Waldir Ribeiro Pires Júnior (2004)

10.1109/TAC.2009.2034929

Modeling and Unsupervised Classification of Multivariate Hidden Markov Chains With Copulas

Nicolas Brunel (2010)

10.1109/TPDS.2013.74

Distributed Detection in Mobile Access Wireless Sensor Networks under Byzantine Attacks

M. Abdelhakim (2014)

10.1109/24.963130

Some properties of a classification system for multivariate life distributions

10.1109/JSAC.2005.861389

Information theoretic framework of trust modeling and evaluation for ad hoc networks

10.1109/SURV.2010.021510.00088

Outlier Detection Techniques for Wireless Sensor Networks: A Survey

Y. Zhang (2010)

This paper is referenced by

10.1002/cpe.3458

Frontier technologies of trust computing and network security

Y. Xiang (2015)

Some data provided by SemanticScholar