A Real-Time Intelligent Jamming Attack of Wireless Sensor Networks

Abstract

In recent years, multimedia forensics and security in Internet cloud environment have attached increasing attention. As a quintessential application of the Internet of Things, a wireless sensor network (WSN) provides means to facilitate human life and industrial development, but it also brings forward a lot of security issues. The majority of existing researches in the WSN security focus on link layer, network layer and application layer, but few deals with physical layer in real applications. In this work, we explore physical layer jamming and present an intelligent jamming model to attack against the WSN. We establish three key technologies to implement a practical intelligent jamming system: (1) burst signal detection based on waveform matching, (2) accurate waveform reconstruction and (3) monitoring the network status. We evaluate the performance of system in an indoor WSN test platform. Empirical results demonstrate that our system can immediately interfere with the packets already on the air, jam specific nodes and achieve adaptive jamming effects through adjustment of jamming power, jamming distance and jamming data length. Consequently, our intelligent jamming scheme is a real threat to wireless multimedia network security, requiring countermeasures for prevention.