Physical-layer security is regaining traction in the research community, due to the performance boost introduced by deep learning classification algorithms. This is particularly true for sender authentication in wireless communications via radio fingerprinting. However, previous research mainly focused on terrestrial wireless devices while, to the best of our knowledge, none of the previous work considered satellite transmitters. The satellite scenario is generally challenging because, among others, satellite radio transducers feature non-standard electronics (usually aged and specifically designed for harsh conditions). Moreover, the fingerprinting task is specifically difficult for Low-Earth Orbit (LEO) satellites (like the ones we focus in this paper) since they feature a low bit-rate and orbit at about 800 Km from the Earth, at a speed of around 25,000 Km/h, thus making the receiver experiencing a down-link with unique attenuation and fading characteristics. In this paper, we investigate the effectiveness and main limitations of AI-based solutions to the physical-layer authentication of LEO satellites. Our study is performed on massive real data—more than $100M$ I-Q samples—collected from an extensive measurements campaign on the IRIDIUM LEO satellites constellation, lasting 589 hours. Our results show that Convolutional Neural Networks (CNN) and autoencoders (if properly calibrated) can be successfully adopted to authenticate the satellite transducers, with an accuracy spanning between 0.8 and 1, depending on prior assumptions. However, the relatively high number of I-Q samples required by the proposed methodology, coupled with the low bandwidth of satellite link, might prevent the detection of the spoofing attack under certain configuration parameters.

Computational complexity of public key cryptography over sensor nodes is not anymore a blocking concern in modern devices which natively (and efficiently) support elliptic curve cryptography. The problem has rather shifted toward the significant airtime consumption required to exchange multiple messages and certificates so as to perform authentication and key agreement. This letter addresses such problem by exploiting implicit certificates (elliptic curve Qu-Vanstone). We specifically propose a novel key management protocol (KMP) which suitably integrates implicit certificates with a standard elliptic curve Diffie-Hellman exchange, and performs authentication and key derivation. As confirmed by a proof-of-concept implementation and relevant experimental results, the proposed KMP guarantees maximal airtime savings (up to 86.7%) with respect to conventional approaches, robust key negotiation, fast rekeying, and efficient protection against replay attacks.

The recent advancements in hardware miniaturization capabilities have boosted the diffusion of systems based on Energy Harvesting (EH) technologies, as a means to power embedded wireless devices in a sustainable and low-cost fashion. Despite the undeniable management advantages, the intermittent availability of the energy source and the limited power supply has led to challenging system trade-offs, resulting in an increased attack surface and a general relaxation of the available security services. In this paper, we survey the security issues, applications, techniques, and challenges arising in wireless networks powered via EH technologies. We explore the vulnerabilities of EH networks, and we provide a comprehensive overview of the scientific literature, including attack vectors, cryptography techniques, physical-layer security schemes for data secrecy, and additional physical-layer countermeasures. For each of the identified macro-areas, we compare the scientific contributions across a range of shared features, indicating the pros and cons of the described techniques, the research challenges, and a few future directions. Finally, we also provide an overview of the emerging topics in the area, such as Non-Orthogonal Multiple Access (NOMA) and Rate-Splitting Multiple Access (RSMA) schemes, and Intelligent Reconfigurable Surfaces, that could trigger the interest of industry and academia and unleash the full potential of pervasive EH wireless networks.

Certificateless Public Key Cryptography (CL-PKC) schemes are particularly robust against the leakage of secret information stored on a Trusted Third Party (TTP). These security features are particularly relevant for Internet of Things (IoT) domains, where the devices are typically pre-configured with secret keys, usually stored locally on the TTP for following maintenance tasks. Despite some contributions already proposed the adoption of CL-PKC schemes in constrained IoT devices, current solutions generally require high message overhead, are computationally demanding, and generally, place a high toll on the energy budget. To close this gap, we propose LiKe, a lightweight pairing-free certificateless key agreement protocol suitable for integration in the latest Zigbee 3.0 protocol stack and constrained IoT devices. LiKe is an authenticated key agreement protocol characterized by: (i) ephemeral cryptographic materials; (ii) support for intermittent connectivity with the TTP; (iii) lightweight rekeying operations; and, (iv) robustness against impersonation attacks, even when information stored on the TTP are leaked. LiKe has been thoroughly described, and its security properties have been proved via formal tools. Moreover, we have implemented and tested it on real IoT devices, in networks with up to 11 nodes — the source code has been released as open-source. Results are striking: on the OpenMote-b hardware platform, LiKe requires a total time of 3.259 s to establish session keys on each participating device, and at most 0.258% of the overall battery capacity, emerging as a lightweight and energy-friendly solution. Finally, comparisons with competing solutions do show the superior quality and viability of our proposal.

This paper proposes a Key Management Protocol for mobile and industrial Internet of Things systems, targeting, at the same time, robust key negotiation, lightweight node authentication, fast re-keying, and efficient protection against replay attacks. The proposed approach pragmatically leverages widely accepted Elliptic Curve Cryptography constructions, specifically the (Elliptic Curve) \"Fixed\" Diffie Hellman key exchange and the (Elliptic Curve) Qu-Vanstone implicit certificates. Our value added is their suitable integration into a security protocol exchange, designed at layer 2, in the 802.15.4 protocol stack, which permits to i) avoid Elliptic Point multiplications upon rekeying of previously paired devices, and ii) support mutual authentication while securing the protocol exchange. To prove its viability, the proposed Key Management Protocol has been implemented and assessed on severely constrained devices. As expected, but made explicit and quantified by our experimental performance evaluation, the usage of implicit certificates in conjunction with an optimized message exchange yields impressive gains in terms of airtime consumption with respect to state of the art schemes.

While the Internet of Things is breaking into the market, the controlled access to constrained resources still remains a blocking concern. Unfortunately, conventional solutions already accepted for both web and cloud applications cannot be directly used in this context. In fact, they generally require high computational and bandwidth capabilities (that are impossible to reach with constrained devices) and offer poor interoperability against standardized communication protocols for the Internet of Things. To solve this issue, this contribution presents a flexible authentication and authorization framework for the Internet of Things, namely OAuth-IoT. It leverages and properly harmonizes existing open-standards (including the OAuth 2.0 authorization framework, different token formats, and the protocol suite for the Internet of Things tailored by the Internet Engineering Task Force), while carefully taking into account the limited capabilities of constrained devices. Functionalities and benefits offered by OAuth-IoT are pragmatically shown by means of an experimental testbed, and further demonstrated with a very preliminary performance assessment.