Model of the Network Physical Layer for Modern Wireless Systems

Wireless physical layer security

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1618130114 ◽

2016 ◽

Vol 114 (1) ◽

pp. 19-26 ◽

Cited By ~ 95

Author(s):

H. Vincent Poor ◽

Rafael F. Schaefer

Keyword(s):

Wireless Networks ◽

Physical Layer Security ◽

Secure Communication ◽

Radio Channel ◽

Wireless Systems ◽

Data Encryption ◽

Physical Layer ◽

Fundamental Limits ◽

Security Information ◽

Networking Architectures

Security in wireless networks has traditionally been considered to be an issue to be addressed separately from the physical radio transmission aspects of wireless systems. However, with the emergence of new networking architectures that are not amenable to traditional methods of secure communication such as data encryption, there has been an increase in interest in the potential of the physical properties of the radio channel itself to provide communications security. Information theory provides a natural framework for the study of this issue, and there has been considerable recent research devoted to using this framework to develop a greater understanding of the fundamental ability of the so-called physical layer to provide security in wireless networks. Moreover, this approach is also suggestive in many cases of coding techniques that can approach fundamental limits in practice and of techniques for other security tasks such as authentication. This paper provides an overview of these developments.

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Flexible spectrum use and better coexistence at the physical layer of future wireless systems via a multicarrier platform

IEEE Wireless Communications ◽

10.1109/mwc.2004.1295741 ◽

2004 ◽

Vol 11 (2) ◽

pp. 64-71 ◽

Cited By ~ 18

Author(s):

S. Hijazi ◽

B. Natarajan ◽

M. Michelini ◽

Zhiqiang Wu ◽

C.R. Nassar

Keyword(s):

Wireless Systems ◽

Physical Layer

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Rogue device discrimination in ZigBee networks using wavelet transform and autoencoders

annals of telecommunications - annales des télécommunications ◽

10.1007/s12243-020-00796-x ◽

2020 ◽

Author(s):

Mohammad Amin Haji Bagheri Fard ◽

Jean-Yves Chouinard ◽

Bernard Lebel

Keyword(s):

Data Security ◽

Classification Accuracy ◽

Wavelet Decomposition ◽

Wireless Systems ◽

Physical Layer ◽

Sensitive Information ◽

Model Classification ◽

High Classification Accuracy ◽

Original Dataset ◽

Desktop Computers

Abstract In modern wireless systems such as ZigBee, sensitive information which is produced by the network is transmitted through different wired or wireless nodes. Providing the requisites of communication between diverse communication system types, such as mobiles, laptops, and desktop computers, does increase the risk of being attacked by outside nodes. Malicious (or unintentional) threats, such as trying to obtain unauthorized accessibility to the network, increase the requirements of data security against the rogue devices trying to tamper with the identity of authorized devices. In such manner, focusing on Radio Frequency Distinct Native Attributes (RF-DNA) of features extracted from physical layer responses (referred to as preambles) of ZigBee devices, a dataset of distinguishable features of all devices can be produced which can be exploited for the detection and rejection of spoofing/rogue devices. Through this procedure, distinction of devices manufactured by the different/same producer(s) can be realized resulting in an improvement of classification system accuracy. The two most challenging problems in initiating RF-DNA are (1) the mechanism of features extraction in the generation of a dataset in the most effective way for model classification and (2) the design of an efficient model for device discrimination of spoofing/rogue devices. In this paper, we analyze the physical layer features of ZigBee devices and present methods based on deep learning algorithms to achieve high classification accuracy, based on wavelet decomposition and on the autoencoder representation of the original dataset.

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