While existing security protocols were designed with a focus on the core network, the enhancement of the security of the B5G access network becomes of critical importance. Despite the strengthening of 5G security protocols with respect to LTE, there are still open issues that have not been fully addressed. This work is articulated around the premise that rethinking the security design bottom up, starting at the physical layer, is not only viable in 6G but importantly, arises as an efficient way to overcome security hurdles in novel use cases, notably massive machine type communications (mMTC), ultra reliable low latency communications (URLLC) and autonomous cyberphysical systems. Unlike existing review papers that treat physical layer security orthogonally to cryptography, we will try to provide a few insights of underlying connections. Discussing many practical issues, we will present a comprehensive review of the state-of the-art in i) secret key generation from shared randomness, ii) the wiretap channels and fundamental limits, iii) authentication of devices using physical unclonable functions (PUFs), localization and multi-factor authentication, and, iv) jamming attacks at the physical layer. We finally conclude with the proposers' aspirations for the 6G security landscape, in the hyper-connectivity and semantic communications era.

With the emergence of 5G low-latency applications, such as haptics and V2X, low-complexity and low-latency security mechanisms are needed. Promising lightweight mechanisms include physical unclonable functions (PUF) and secret key generation (SKG) at the physical layer, as considered in this paper. In this framework, we propose (i) a zero round trip time (0-RTT) resumption authentication protocol combining PUF and SKG processes, (ii) a novel authenticated encryption (AE) using SKG, and (iii) pipelining of the AE SKG and the encrypted data transfer in order to reduce latency. Implementing the pipelining at PHY, we investigate a parallel SKG approach for multi-carrier systems, where a subset of the subcarriers are used for SKG and the rest for data transmission. The optimal solution to this PHY resource allocation problem is identified under security, power, and delay constraints, by formulating the subcarrier scheduling as a subset-sum 0−1 knapsack optimization. A heuristic algorithm of linear complexity is proposed and shown to incur negligible loss with respect to the optimal dynamic programming solution. All of the proposed mechanisms have the potential to pave the way for a new breed of latency aware security protocols.

In this article we present the evolutionary journey of physical layer security (PLS), starting from its theoretical foundations in wiretap coding and secret key generation followed by to the revolutionary advancements in authentication using physical unclonable functions (PUFs), localization and RF fingerprinting. Since the middle of last century the theory behind PLS has been constantly evolving, however, practical solutions are still scarce. Through a critical review, we identify the key hurdles hindering the widespread adoption of PLS. Moreover, we highlight important research directions and possible solutions that can bridge the gap between theory and practice.

Lightweight physical layer security schemes that have recently attracted a lot of attention include physical unclonable functions (PUFs), RF fingerprinting / proximity based authentication and secret key generation (SKG) from wireless fading coefficients. In this paper, we propose a fast, privacy-preserving, zero-round-trip-time (0-RTT), multi-factor authentication protocol, that for the first time brings all these elements together, i.e., PUFs, proximity estimation and SKG. We use Kalman filters to extract proximity estimates from real measurements of received signal strength (RSS) in an indoor environment to provide soft fingerprints for node authentication. By leveraging node mobility, a multitude of such fingerprints are extracted to provide resistance to impersonation type of attacks e.g., a false base station. Upon removal of the proximity fingerprints, the residual measurements are then used as an entropy source for the distillation of symmetric keys and subsequently used as resumption secrets in a 0-RTT fast authentication protocol. Both schemes are incorporated in a challenge-response PUF-based mutual authentication protocol, shown to be secure through formal proofs using Burrows, Abadi, and Needham (BAN) and Mao and Boyd (MB) logic, as well as the Tamarin-prover. Our protocol showcases that in future networks purely physical layer security solutions are tangible and can provide an alternative to public key infrastructure in specific scenarios.

Lightweight session key agreement schemes are expected to play a central role in building Internet of things (IoT) security in sixth-generation (6G) networks. A well-established approach deriving from the physical layer is a secret key generation (SKG) from shared randomness (in the form of wireless fading coefficients). However, although practical, SKG schemes have been shown to be vulnerable to active attacks over the initial “advantage distillation” phase, throughout which estimates of the fading coefficients are obtained at the legitimate users. In fact, by injecting carefully designed signals during this phase, a man-in-the-middle (MiM) attack could manipulate and control part of the reconciled bits and thus render SKG vulnerable to brute force attacks. Alternatively, a denial of service attack can be mounted by a reactive jammer. In this paper, we investigate the impact of injection and jamming attacks during the advantage distillation in a multiple-input–multiple-output (MIMO) system. First, we show that a MiM attack can be mounted as long as the attacker has one extra antenna with respect to the legitimate users, and we propose a pilot randomization scheme that allows the legitimate users to successfully reduce the injection attack to a less harmful jamming attack. Secondly, by taking a game-theoretic approach we evaluate the optimal strategies available to the legitimate users in the presence of reactive jammers.

A machine learning enabled link adaption (LA) and scheduling framework is presented for Industrial Internet of Things (IIoT), leveraging quasi-periodicity of traffic in IIoT. The following steps are introduced: i) a reduced complexity link establishment accounting jointly for beamforming and load management; ii) interference prediction using long short-term memory neural networks; iii) semi-coordinated scheduling based on node grouping for interference avoidance. Through numerical evaluation it is demonstrated that the proposed approach can substantially improve average spectral efficiency by as much as 62% in a realistic IIoT scenario at negligible overhead.