On the authentication of devices in the Internet of things

Reaping the benefits of the Internet of things (IoT) system is contingent upon developing IoT-specific security and privacy solutions. Conventional security solutions fail to meet the IoT security requirements due to the computationally limited and portable nature of IoT objects. In this paper, an object authentication framework is proposed to exploit device-specific information, called fingerprints, to authenticate objects in the IoT. The proposed framework is shown to effectively track the effects of physical environment on objects' fingerprints via a transfer learning tool to differentiate between security attacks and normal change in fingerprints. Simulation results show that the proposed framework improves the authentication accuracy.

[1]  Walid Saad,et al.  Toward Massive Machine Type Cellular Communications , 2017, IEEE Wireless Communications.

[2]  Rolf H. Weber,et al.  Internet of Things - New security and privacy challenges , 2010, Comput. Law Secur. Rev..

[3]  T. Kailath The Divergence and Bhattacharyya Distance Measures in Signal Selection , 1967 .

[4]  Gabi Nakibly,et al.  Mobile Device Identification via Sensor Fingerprinting , 2014, ArXiv.

[5]  Qiang Yang,et al.  A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.

[6]  Raheem A. Beyah,et al.  A passive technique for fingerprinting wireless devices with Wired-side Observations , 2013, 2013 IEEE Conference on Communications and Network Security (CNS).

[7]  Hiren Patel,et al.  Non-parametric feature generation for RF-fingerprinting on ZigBee devices , 2015, 2015 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA).

[8]  Walid Saad,et al.  Device Fingerprinting in Wireless Networks: Challenges and Opportunities , 2015, IEEE Communications Surveys & Tutorials.