Mining Lines In The Sand: On Trajectory Discovery From Untrustworthy Data In Cyberphysical System

A Cyber-Physical System (CPS) integrates physical (i.e.. sensor) devices with cyber (i.e., informational) components to form a context sensitive s3,,stern that responds intelligently to dynamic changes in real-world situations. The CPS has wide applications in scenarios such as ertvirontnent monitoring. battlefield surveillance and traffic control. One key research problem of CPS is called -tinning lines in the sand". With a large immber of sensors (sand) deployed in a designated area. the CPS is required to discover all the trajectories (lines) of passing intruders in real time. There are two crucial challenges that need to be addressed: (1) the collected sensor data are not trustworthy: (2) the intruders do not send out any identification information. The system needs to distinguish multiple intruders and track their movements. In this study, we propose a method called LiSAI (Line-in-the-Sand Miner) to discover trajectories from untrustworthy sensor data. LtS111 constructs a watching network from sensor data arid computes the locations of intruder appearances based on the link information of the network. The system retrieves a cone -model from the historical trajectories and tracks multiple intruders based on this model. Finally the system validates the mining results and updates the sensor's reliability in a feedback process. Extensive experiments on big datasets demonstrate the feasibility and applicability of the proposed methods.