A Research On IoT Security Authentication Mechanism Based On Signal Physical Layer Signatures

The vigorous development of low-power Internet of Things(Io T)technology has prompted various lightweight Io T devices to be widely used in smart homes and smart factories.The minimalist design of Io T devices opens up many opportunities,but makes the communication extremely vulnerable to malicious active attacks,which poses severe security challenges to Io T systems.However,lightweight Io T devices lack user interfaces such as touch screens and input keyboards,making it difficult to support traditional PreShared Key(PSK)security protocols.Existing physical layer authentication schemes require Io T devices to be equipped with relatively expensive and bulky multi-antenna arrays or specific embedded sensors,which is not suitable for lightweight Io T devices limited by power consumption,size,and cost.To this end,we make full use of the advantages of backscatter communication technology in power consumption and cost,and propose a lightweight physical layer security authentication mechanism,which does not require the modification of commercial Io T devices,and does not require specific sensors.According to different scenarios,the corresponding authentication schemes are designed for fixed and mobile wireless Io T devices respectively.(1)In the scenario where fixed Io T devices are paired with the access gateway(AG),we propose to deploy low-power and small-size backscatter tags around the AG,and construct the multipath propagation signatures to distinguish the location of the signals' arrival,so as to uniquely identify the Io T device.We first detect and accurately segment the backscatter signal from the received signal to extract fine-grained representative features.Then,the feature sequence warping method is deployed to mitigate the impact of the offset between the multipath propagation feature sequences on the similarity matching,and the suspicious signals are accurately and effectively identified based on the anomaly detection algorithm.Furthermore,a random working mechanism of backscatter tags and a multi-device combination detection mechanism are proposed to improve the security of the system.Based on the above scheme,we implement the hardware prototype of backscatter tags to evaluate the performance of our system.The results show that even if the powerful attacker is close to the legitimate device,our proposed solution can detect 95% of active attacks.(2)In the scenario where mobile Io T devices are paired with hazardous industrial devices,on the premise of keeping a safe distance between the transmitting device and hazardous industrial devices,we propose to deploy a backscatter tag to capture the received signal strength(RSS)variation characteristics caused by the user shaking the transmitting device,and fuse the device position information captured by the camera to achieve a secure pairing between devices.We extract fine-grained features that can characterize the amplitude and frequency of user actions.To mitigate the impact of action differences and environmental noise on feature matching,a feature transformation scheme based on Principal Components Analysis(PCA)is further developed to achieve robust device authentication.The results show that our proposed scheme can achieve an overall accuracy of 94% for device authentication.