Research on security encryption mechanism of physical Layer based on iterative quantization method

Author:

Jing Weizhe1,Ma Dongjuan1,Yang Hua1,Guo Min1,Xue Qiang1,Liu Wenqing2,Zhang Yanyan2,Ju Yun2

Affiliation:

1. State Grid Shanxi Electric Power Research Institute, Taiyuan, Shanxi, China

2. North China Electric Power University, Beijing, China

Abstract

Third-party eavesdropping is a unsolved problem in the process of data transmission in the physical layer of IoT (Internet of Things) in Power Systems. The security encryption effect is affected by channel noise and the half-duplex nature of the wireless channel, which leads to low key consistency and key generation rate. To address this problem, a reliable solution for physical layer communication security is proposed in this paper. First, the solution improved the key consistency by dynamically adjusting the length of the training sequence during feature extraction; Second, using an iterative quantization method to quantify the RSS (Received Signal Strength) measurements to improve generation rate of the key. Finally, based on the short-time energy method for the extraction of wireless frame interval features, by monitoring the change of inter-frame interval features, we can quickly determine whether there is an eavesdropping device into the link. Simulation results show that the reciprocity of legitimate channels R (R will be explained in detail in the following) is improved by 0.1, the key generation rate is increased by about 70%, and the beacon frames are extracted from the wireless link with good results compared to the methods that do not use dynamic adjustment of the pilot signal during the channel probing phase. The result shows that this method can effectively prevents third-party eavesdropping, effectively improves the key consistency and generation rate, and effectively implements beacon frame detection.

Publisher

IOS Press

Subject

Computational Mathematics,Computer Science Applications,General Engineering

Reference10 articles.

1. Wireless traffic prediction with scalable gaussian process: Framework, algorithms, and verification;Yue;IEEE Journal on Selected Areas in Communications.,2019

2. A Practical Secret Key Generation Scheme Based on Wireless Channel Characteristics for 5G Networks;Qiuhua;IEICE Transactions on Information and Systems.,2020

3. Scalable secret key generation for wireless sensor networks;Altun;IEEE Systems Journal.,2022

4. High-rate secret key generation aided by multiple relays for Internet of things;Xiao;Electronics Letters.,2017

5. Power maximisation technique for generating secret keys by exploiting physical layer security in wireless communication;Xiaoping;IET Communications.,2020

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