StableFP:NN-Based Hardware Fingerprint Extractor for LoRa Device Identification

Hardware fingerprint is a new dimension of security mechanisms in low power wide area networks(LPWANs).It is hard to emulate for attackers and does not increase the computing and energy burden of transmitters.long range(LoRa)is a long-range communication technology designed for battery-powered devices.In practice,LoRa is vulnerable to malicious attacks such as replace attack.Therefore,the hardware fingerprint is an excellent supplementary mechanism of LoRa security.However,the variable wireless environment contaminates the extracted fingerprints.The long wireless channel adds a large amount of the environment dependent information to the hardware features extracted from LoRa devices.In this paper,we propose StableFP which is a neural network(NN)based device identifier for long range wide area network(LoRaWAN).StableFP extracts stable and representative hardware features from channel frequency response(CFR)as the fingerprint,and it eliminates the environment dependent information caused by wireless environments.We implement StableFP on a software defined radio(SDR)testbed which consists of 4 commercial LoRa nodes.The result demonstrates that StableFP achieves over 90%identification accuracy in unseen environments under an over 5 dB signal to noise ratio(SNR).

A Secure Device Management Scheme with Audio-Based Location Distinction in IoT

Identifying a device and detecting a change in its position is critical for secure devices management in the Internet of Things(IoT).In this paper,a device management system is proposed to track the devices by using audio-based location distinction techniques.In the proposed scheme,traditional cryptographic techniques,such as symmetric encryption algorithm,RSA-based signcryption scheme,and audio-based secure transmission,are utilized to provide authentication,non-repudiation,and confidentiality in the information interaction of the management system.Moreover,an audio-based location distinction method is designed to detect the position change of the devices.Specifically,the audio frequency response(AFR)of several frequency points is utilized as a device signature.The device signature has the features as follows.(1)Hardware Signature:different pairs of speaker and microphone have different signatures;(2)Distance Signature:in the same direction,the signatures are different at different distances;and(3)Direction Signature:at the same distance,the signatures are different in different directions.Based on the features above,amovement detection algorithmfor device identification and location distinction is designed.Moreover,a secure communication protocol is also proposed by using traditional cryptographic techniques to provide integrity,authentication,and non-repudiation in the process of information interaction between devices,Access Points(APs),and Severs.Extensive experiments are conducted to evaluate the performance of the proposed method.The experimental results show that the proposedmethod has a good performance in accuracy and energy consumption.