Within the paradigm of physical layer security, a physical layer characteristic is used as a common source of randomness to generate the secret key. This key is then used to encrypt the data to hide information from eavesdroppers. In this paper, we survey the most recent common sources of randomness used to generate the secret key. We present the steps used to extract the secret key from the estimated common source of randomness. We describe the metrics used to evaluate the strength of the generated key. We follow that with a qualitative comparison between different common sources of randomness along with a proposed new direction which capitalizes on hybridization of sources of randomness. We conclude by a discussion about current open research problems in secret key generation.
Within the paradigm of physical layer security, a physical layer characteristic is used as a common source of randomness to generate the secret key. This key is then used to encrypt the data to hide information from eavesdroppers. In this paper, we survey the most recent common sources of randomness used to generate the secret key. We present the steps used to extract the secret key from the estimated common source of randomness. We describe the metrics used to evaluate the strength of the generated key. We follow that with a qualitative comparison between different common sources of randomness along with a proposed new direction which capitalizes on hybridization of sources of randomness. We conclude by a discussion about current open research problems in secret key generation.
As an alternative and appealing approach to providing information security in wireless communication systems, secret key generation at physical layer has demonstrated its potential in terms of efficiency and reliability over traditional cryptographic methods. Without the necessity of a management centre for key distribution or reliance on computational complexity, physical layer key generation protocols enable two wireless entities to extract identical and dynamic keys from the randomness of the wireless channels associated with them.\nIn this thesis, the reliability of secret key generation at the physical layer is examined in practical wireless channels with imperfect channel state information (CSI). Theoretical analyses are provided to relate key match rate with channel's signal-to-noise ratio (SNR), degrees of channel reciprocity, and iterations of information reconciliation.\nIn order to increase key match rate of physical layer secret key generation, improved schemes in the steps of channel estimation and sample quantization are proposed respectively. In the channel estimation step, multiple observations of the wireless channels are integrated with a linear processor to provide a synthesized and more accurate estimation of the wireless channel. In the sample quantization step, a magnitude based quantization method with two thresholds is proposed to quantize partial samples, where specific quantization areas are selected to reduce cross-over errors. Significant improvements in key match rate are proven for both schemes in theoretical analysis and numerical simulations. Key match rate can even achieve 100% in both schemes with the assistance of information reconciliation process.\nIn the end, a practical application of physical layer secret key generation is presented, where dynamic keys extracted from the wireless channels are utilized for securing secret data transmission and providing efficient access control.
Abstract: Physical layer key generation, leveraging the reciprocity and randomness of wireless fading channels, has garnered significant research interest in recent years. While theoretical studies have demonstrated its potential to generate informationtheoretically secure keys, challenges remain in translating theory into practice. This paper provides an overview of the physical layer key generation process and discusses its practical challenges. Various passive and active attacks are analyzed and evaluated through numerical studies. A new key generation scheme using random probing signals and combining usergenerated randomness with channel randomness is introduced to counteract active attacks. Numerical results demonstrate that the proposed scheme achieves higher security strength than existing schemes using constant probing signals under active attacks. Secret-key generation relying on wireless channel reciprocity is an intriguing solution as it can be efficiently implemented at the physical layer of emerging wireless communication networks, while providing information-theoretic security guarantees. In this paper, we investigate and compare the secret-key capacity based on the sampling of the entire complex channel state information (CSI) or only its envelope, the received signal strength (RSS).
Physical layer secret key generation (PHYSKG) is a promising technology to provide lightweight and information-theoretically secure key sharing. It has been widely studied in wireless communications and the Internet of Things (IoT). Yet, this technology is nontrivial for large scale wireless networks due to high overhead, insufficient security, and poor adaptability. Recently, artificial intelligence (AI)-based PHYSKG has shown greater performance and higher security with lower overhead than traditional schemes. Although many existing works have been devoted to exploiting AI-based PHYSKG, a scientific review is still missing, but highly anticipated in the literature. In this article, we perform a serious review on AI-based PHYSKG in wireless communications. After a comprehensive introduction to the processing procedure of AI-based PHYSKG, we propose a set of criteria for justifying its performance with regard to key generation efficiency, reliability, security, and generality. Based on these criteria, we review and analyze the state-of-art, focusing on randomness extraction and quantification. On the basis of the review, we further indicate open issues, current challenges, and future research direction in this field.
Secret key generation at physical layer has attracted more and more attentions as an emerging cryptography method. Compared to traditional security approaches, secret key generation at physical layer not only avoids the problem of key distribution, but also holds high efficiency and low complexity in application. Based on the principle of channel reciprocity, Alice and Bob both estimate the channel conditions and extract shared keys from this source of common randomness. In this paper, we first analyze the basic steps (channel estimation, sample quantization and key reconciliation) of secret key generation, key match rate with different quantization levels and key reconciliation times are also simulated. While in practical situations, different non-reciprocity factors affect the channel estimation step, key match rate can be greatly decreased and hardly meet real time cryptography requirements. In order to increase the key match rate, the unified framework of physical layer key generation has been extended to utilizing multiple observations of wireless channels to generate secret keys. An improved key generation approach with multiple observations can well deal with discrepancies between transceivers and keep increasing the key match rate. Theoretical analysis and simulation results both validate the significant improvement due to multiple observations. With an increased number of observations on both sides, the desired key match rate can be achieved much greater than with a single observation, and also the probability of key recovery by Eve can be decreased.
Identification is a new paradigm introduced for goal-oriented communication that verifies the semantics of the intended message rather than just transmitting the message bits, which is traditionally done in classical communication systems. One of the key techniques to improve randomized identification capacity is by introducing Common Randomness (CR). Physical Layer Secret Key (PLSK) is one such CR generation technique, where terminals generate secret keys based on changes in channel reciprocity between the wireless terminals and are mainly used for PHY layer encryption. However, the traditional way of evaluating PLSK techniques through bit discrepancies, bit generation rate, and entropy is not sufficient for evaluating their usefulness for identification. This paper proposes three key novel information theory paradigms that can be used alongside other mentioned parameters to evaluate key PLSK techniques for their usefulness in identification, i.e., CR rate, CR capacity, and cost function, followed by a supporting implementation using Software Defined Radio (SDR)s.
Physical layer key generation that exploits reciprocity and randomness of wireless fading channels has attracted considerable research attention in recent years. Although theoretical study has shown its potential to generate information- theoretic secure keys, great challenges remain when transforming the theory into practice. This article provides an overview of the physical layer key generation process and discusses its practical challenges. Different passive and active attacks are analyzed and evaluated through numerical study. A new key generation scheme using random probing signals, and combining user generated randomness and channel randomness, is introduced as a countermeasure against active attacks. The numerical results show that the proposed scheme achieves higher security strength than existing schemes using constant probing signals under active attacks. Future research topics on physical layer key generation are discussed.