Mining sensor data in cyber-physical systems

Abstract

A Cyber-Physical System (CPS) integrates physical devices (i.e., sensors) with cyber (i.e., informational) components to form a context sensitive system that responds intelligently to dynamic changes in real-world situations. Such a system has wide applications in the scenarios of traffic control, battlefield surveillance, environmental monitoring, and so on. A core element of CPS is the collection and assessment of information from noisy, dynamic, and uncertain physical environments integrated with many types of cyber-space resources. The potential of this integration is unbounded. To achieve this potential the raw data acquired from the physical world must be transformed into useable knowledge in real-time. Therefore, CPS brings a new dimension to knowledge discovery because of the emerging synergism of the physical and the cyber. The various properties of the physical world must be addressed in information management and knowledge discovery. This paper discusses the problems of mining sensor data in CPS: With a large number of wireless sensors deployed in a designated area, the task is real time detection of intruders that enter the area based on noisy sensor data. The framework of IntruMine is introduced to discover intruders from untrustworthy sensor data. IntruMine first analyzes the trustworthiness of sensor data, then detects the intruders' locations, and verifies the detections based on a graph model of the relationships between sensors and intruders.