Efficient Fault-tolerant Information Barrier Coverage in Internet of Things

Information barrier coverage has been widely adopted to prevent unauthorized invasion of important areas in Internet of Things. As sensors are typically placed outdoors, they are susceptible to getting faulty. Previous works assumed that faulty sensors are easy to recognize, e.g., they may stop functioning or output apparently deviant sensory data. In practice, there exist multiple types of fault that sensors may have during operation. It is, thereby, difficult to recognize faulty sensors as well as their invalid output and attain accurate intrusion detection. We, in this paper, propose a novel fault-tolerant intrusion detection algorithm (TrusDet) based on trust management to address this challenging issue. TrusDet comprises of three steps: i) sensor-level detection, ii) sink-level decision by collective voting, and iii) trust management and fault determination. In the Step i) and ii), TrusDet divides the surveillance area into a set of fine-grained subareas and exploits temporal and spatial correlation of sensory output among sensors in different subareas to yield a more accurate and robust performance of information barrier coverage. In the Step iii), TrusDet builds a trust management based framework to determine the confidence level of sensors being faulty. We implement TrusDet on HC-SR501 infrared sensors, and design hardware and software to build a practical detection system. Extensive experimental results and simulation results validate the information coverage model and demonstrate that TrusDet has a very low false alarm rate.