Abstract
The Internet of Things has broad application in military field, commerce, environmental monitoring, and many other fields. However, the open nature of the information media and the poor deployment environment have brought great risks to the security of wireless sensor networks, seriously restricting the application of wireless sensor network. Internet of Things composed of wireless sensor network faces security threats mainly from Dos attack, replay attack, integrity attack, false routing information attack, and flooding attack. In this paper, we proposed a new intrusion detection system based onK-nearest neighbor (K-nearest neighbor, referred to as KNN below) classification algorithm in wireless sensor network. This system can separate abnormal nodes from normal nodes by observing their abnormal behaviors, and we analyse parameter selection and error rate of the intrusion detection system. The paper elaborates on the design and implementation of the detection system. This system has achieved efficient, rapid intrusion detection by improving the wireless ad hoc on-demand distance vector routing protocol (Ad hoc On-Demand Distance the Vector Routing, AODV). Finally, the test results show that: the system has high detection accuracy and speed, in accordance with the requirement of wireless sensor network intrusion detection.
Highlights
Internet of Things refers to the network which combines various sensing devices, such as radio frequency identification (RFID) devices, infrared sensors, global positioning systems, laser scanners, and other various devices with the Internet
This paper focuses on the security of Internet of Things composed of wireless sensor networks (WSN)
Firstly we propose a new intrusion detection system based on K-Nearest Neighbor (KNN) classification algorithm in wireless sensor network
Summary
Internet of Things refers to the network which combines various sensing devices, such as radio frequency identification (RFID) devices, infrared sensors, global positioning systems, laser scanners, and other various devices with the Internet. Firstly we propose a new intrusion detection system based on KNN classification algorithm in wireless sensor network. This system separates abnormal nodes from normal nodes by observing their abnormal behaviors, and we analyse parameter selection and error rate of the intrusion detection system based on KNN classification algorithm [3]. (1) We have identified and presented a new intrusion detection system based on KNN classification algorithm in wireless sensor network. It separates abnormal nodes from normal nodes by observing their abnormal behaviors.
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