In modern large-scale systems comprising multiple heterogeneous devices, the introduction of swarm attestation schemes aims to alleviate the scalability and efficiency issues of traditional single-Prover and single-Verifier attestation. In this paper, we propose PRIVÉ, a privacy-preserving, scalable, and accountable swarm attestation scheme that addresses the limitations of existing solutions. Specifically, we eliminate the assumption of a trusted Verifier, which is not always applicable in real-world scenarios, as the need for the devices to share identifiable information with the Verifier may lead to the expansion of the attack landscape. To this end, we have designed an enhanced variant of the Direct Anonymous Attestation (DAA) protocol, offering traceability and linkability whenever needed. This enables PRIVÉ to achieve anonymous, privacy-preserving attestation while also providing the capability to trace a failed attestation back to the compromised device. To the best of our knowledge, this paper presents the first Universally Composable (UC) security model for swarm attestation accompanied by mathematical UC security proofs, as well as experimental benchmarking results that highlight the efficiency and scalability of the proposed scheme.

Several key exchange methods for wireless channels have been proposed in the literature. They are referred to as physical‐layer security techniques and are usually based on the channel's fading characteristics and the principle of channel reciprocity. In this study, the authors present key exchange algorithms for wireless fading channels whose operation is based on channel estimation. Specifically, the authors present a complete key exchange scheme that includes channel sampling, thresholding and error reconciliation. Two error reconciliation methods are proposed. The first one is based on neural networks and the second one is based on linear block coding. Simulations of the proposed methods’ performances and levels of security are presented and conclusions are drawn regarding their overall utility.

Several key exchange methods for wireless channels have been proposed in the literature. They are referred to as PHY-layer security techniques and are usually based on the channel's fading characteristics and the principle of reciprocity. In this paper, we present a novel PHY-layer security algorithm whose function is based on neural networks. Specifically, we present a full key exchange scheme which includes channel sampling and thresholding and neural network based error reconciliation. The proposed method's performance and offered security are studied through simulations and interesting conclusions are drawn about its overall utility.