Remote Identification (RID) regulations recently promulgated worldwide are forcing commercial drones to broadcast wirelessly the location of the pilot in plaintext. However, in many real-world use cases, the plaintext availability of such information leads to privacy issues, allowing the extraction of sensitive information about the pilot and confidential details about the drone's business. To address this issue, this paper proposes SNELL, a RID-compliant solution for selective authenticated pilot location disclosure. Using SNELL, a drone can disclose RID messages providing encrypted information about the pilot's location. At the same time, thanks to the smart integration of Ciphertext-Policy Attribute-Based Encryption (CP-ABE) techniques, the data about the pilot location can be decrypted only by receivers with a set of attributes satisfying an access control policy chosen by the drone at run-time. Thanks to an extensive experimental assessment carried out on a real medium-end drone (Lumenier QAV-R) and a constrained chip (ESP32), we demonstrate that SNELL can fulfil all the requirements imposed by RID and relevant standardization authorities in terms of pilot location update time and message size while also requiring negligible energy toll on RID-compliant drones.

The Federal Aviation Administration (FAA) recently introduced a new standard, namely, remote identification, to improve accountability for unmanned aerial vehicles (UAVs) operations. This rule requires UAV operators to broadcast messages revealing sensitive data, such as identity and location on the wireless channel. However, this leads to security and privacy concerns among UAV operators. Unauthorized parties may easily discover the location and identity of a UAV flying in a specific area and launch attacks on it such as using wireless jamming or tracking its activity. This review investigates and systematizes the main weaknesses affecting the Remote ID capability required of modern UAVs, and the approaches through which attackers can exploit these weaknesses to disrupt safety and accountability. Moreover, this article analyzes current solutions that mitigate privacy issues associated with Remote ID. Finally, we identify multiple challenges that require to be addressed by both industry and academia, and we propose future research directions to improve the security and privacy of UAVs.

Discovering mutual proximity and avoiding collisions is one of the most critical services needed by the next generation of Unmanned Aerial Vehicles (UAVs). However, currently available solutions either rely on sharing mutual locations, neglecting the location privacy of involved parties, or are applicable for fully autonomous vehicles only—leaving unaddressed Remotely-Piloted UAVs’ safety needs. Alternatively, proximity can be discovered by adding sensing capabilities. However, in addition to the cost of the sensors, the complexity of integration, and the toll on the energy budget, the effectiveness of such solutions is usually limited by short detection ranges, making them hardly useful in high-mobility scenarios. In this paper, we propose LPPD (an acronym for Lightweight Privacy-preserving Proximity Discovery), a unique solution for privacy-preserving proximity discovery among remotely piloted UAVs based on the exchange of wireless messages. LPPD integrates two main building blocks: (i) a custom space tessellation technique based on randomized spheres; and, (ii) a lightweight cryptographic primitive for private-set intersection. Another feature enjoyed by LPPD is that it does not require online third parties. LPPD is rooted in sound theoretical results and is supported by an experimental assessment performed on a real drone. In particular, experimental results show that LPPD achieves 100% proximity discovery while taking only 39.66 milliseconds in the most lightweight configuration and draining only the 5 · 10− 6% of the UAV’s battery capacity. In addition, LPPD’s security properties are formally verified.

The recent worldwide introduction of RemoteID (RID) regulations forces all unmanned aircrafts (UAs), also known as drones, to broadcast in plaintext on the wireless channel their identity and real-time location, for accounting and monitoring purposes. Although improving drones’ monitoring and situational awareness, the RID rule also generates significant privacy concerns for UAs’ operators, threatened by the ease of tracking of UAs and related confidentiality and privacy concerns connected with the broadcasting of plaintext identity information. In this article, we propose anonymous direct authentication and remote identification ($A^{2}RID$), a protocol suite for$A^{2}RID$of heterogeneous commercial UAs.$A^{2}RID$integrates and adapts protocols for anonymous message signing to work in the UA domain, coping with the constraints of commercial drones and the tight real-time requirements imposed by the RID regulation. Overall, the protocols in the$A^{2}RID$suite allow a UA manufacturer to pick the configuration that best suits the capabilities and constraints of the drone, i.e., either a processing-intensive but memory-lightweight solution (namely,$CS-A^{2}RID$) or a computationally friendly but memory-hungry approach (namely,$DS-A^{2}RID$). Besides formally defining the protocols and formally proving their security in our setting, we also implement and test them on real heterogeneous hardware platforms, i.e., the Holybro X-500 and the ESPcopter, releasing open-source the produced code. For all the protocols, we demonstrated experimentally the capability of generating anonymous RemoteID messages well below the time bound of 1 s required by RID, while at the same time having quite a limited impact on the energy budget of the drone.

A plethora of contact tracing apps have been developed and deployed in several countries around the world in the battle against Covid-19. However, people are rightfully concerned about the security and privacy risks of such applications. To address these issues, in this paper we provide two main contributions. First, we present an in-depth analysis of the security and privacy characteristics of the most prominent contact tracing protocols, under both passive and active adversaries. The results of our study indicate that all protocols are vulnerable to a variety of attacks, mainly due to the deterministic nature of the underlying cryptographic protocols. Our second contribution is the design and implementation of SpreadMeNot, a novel contact tracing protocol that can defend against most passive and active attacks, thus providing strong (provable) security and privacy guarantees that are necessary for such a sensitive application. Our detailed analysis, both formal and experimental, shows that SpreadMeNot satisfies security, privacy, and performance requirements, hence being an ideal candidate for building a contact tracing solution that can be adopted by the majority of the general public, as well as to serve as an open-source reference for further developments in the field.

Current collision avoidance techniques deployed on Unmanned Aerial Vehicles (UAVs) rely on short-range sensors, such as proximity sensors, cameras, and microphones. Unfortunately, their efficiency is significantly limited in several situations; for instance, when a remote UAV approaches at high velocity, or when the surrounding environment is impaired (e.g., fog, noise). In the cited cases, to avoid collisions and maintain self-separation, UAVs often rely on the indiscriminate broadcast of their location. Therefore, an adversary could easily identify the location of the UAV and attack it, e.g., by physically shutting it down, launching wireless jamming attacks, or continuing tracking its movements. To address the above-introduced threats, in this article we present PPCA, a lightweight, distributed, and privacy-preserving scheme to avoid collisions among UAVs. Our solution, based on an ingenious tessellation of the space, is accompanied by a thorough analytical model and is supported by an extensive experimental campaign performed on a real 3DR-Solo drone. The achieved results are striking: PPCA can efficiently and effectively avoid collisions among UAVs, by requiring a limited bandwidth and computational overhead (84.85% less than traditional privacy-preserving proximity testing approaches), while providing unique benefits in terms of privacy of the participating UAVs.

Wireless enabling technologies in critical infrastructures are increasing the efficiency of communications. Most of these technologies are vulnerable to jamming attacks. Jamming attacks are among the most effective countermeasures to attack and compromise their availability. Jamming is an interfering signal that limits the intended receiver from correctly receiving the messages. Localizing a jammer deployed by the adversary in wireless sensor networks becomes difficult, if not impossible, due to the inaccessibility of the affected sensors in the network. This paper proposes an effective yet efficient jammer localization scheme where battery-free Radio-Frequency Identification (RFID) sensor tags harvest the energy from the signal emitted by a powerful jammer. We compute the distance and estimate the actual jammer location based on the power received at each energy-harvesting node. We conduct extensive simulations campaign to test and illustrate the effectiveness of the proposed scheme. Finally, we demonstrate the possibility of deploying the proposed scheme with off-shelf equipment and consuming only 0.2175 mJ,

Satellite-based Communication (SATCOM) systems are gaining renewed momentum in Industry and Academia, thanks to innovative services introduced by leading tech companies and the promising impact they can deliver towards the global connectivity objective tackled by early 6G initiatives. On the one hand, the emergence of new manufacturing processes and radio technologies promises to reduce service costs while guaranteeing outstanding communication latency, available bandwidth, flexibility, and coverage range. On the other hand, cybersecurity techniques and solutions applied in SATCOM links should be updated to reflect the substantial advancements in attacker capabilities characterizing the last two decades. However, business urgency and opportunities are leading operators towards challenging system trade-offs, resulting in an increased attack surface and a general relaxation of the available security services. In this paper, we tackle the cited problems and present a comprehensive survey on the link-layer security threats, solutions, and challenges faced when deploying and operating SATCOM systems. Specifically, we classify the literature on security for SATCOM systems into two main branches, i.e., physical-layer security and cryptography schemes. Then, we further identify specific research domains for each of the identified branches, focusing on dedicated security issues, including, e.g., physical-layer confidentiality, anti-jamming schemes, anti-spoofing strategies, and quantum-based key distribution schemes. For each of the above domains, we highlight the most essential techniques, peculiarities, advantages, disadvantages, lessons learned, and future directions. Finally, we also identify emerging research topics whose additional investigation by Academia and Industry could further attract researchers and investors, ultimately unleashing the full potential behind ubiquitous satellite communications.

Automatic Identification System (AIS) is the de-facto communication standard used by vessels to broadcast identification and position information. However, being AIS communications neither encrypted nor authenticated, they can be eavesdropped and spoofed by adversaries, leading to potentially threatening scenarios. Existing solutions, including the ones conceived in the avionics domain, do not consider integration with the AIS standard, and they do not provide protection against rogue messages flooding. In this article, we propose Auth-AIS, a secure, flexible, standard-compliant, and backward-compatible authentication framework to secure AIS broadcast messages. Auth-AIS leverages existing sound cryptographic tools, including TESLA and Bloom Filters, inheriting their security properties while contextualizing them in the AIS technology. Auth-AIS is a software-only solution, that can be seamlessly integrated into existing AIS deployments, without requiring any hardware replacement. Its innovative design also provides backward-compatibility—i.e., Auth-AIS messages can be received also by AIS users not adopting Auth-AIS, while renouncing at its security guarantees. Auth-AIS can work in either two configuration modes: Deterministic Security Configuration, able to achieve low-delay authentication with a message overhead of 75 percent, or Probabilistic Security Configuration, reducing the message overhead down to 35.71 percent, while experiencing a marginal increase in the authentication delay. All these security configurations guarantee an 80 bits equivalent security level and false-positive rate less than 2--40. Note that these latter security parameters can easily be tuned to fit different security requirements. Finally, the source code of Auth-AIS in the GNURadio ecosystem has been released as open-source, to foster research activities from both Industry and Academia on secure AIS communications.

To enable enhanced accountability of Unmanned Aerial Vehicles (UAVs) operations, the US-based Federal Avionics Administration (FAA) recently published a new dedicated regulation, namely RemoteID, requiring UAV operators to broadcast messages reporting their identity and location. The enforcement of such a rule, mandatory by 2022, generated significant concerns on UAV operators, primarily because of privacy issues derived by the indiscriminate broadcast of the plain-text identity of the UAV on the wireless channel.

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 preconfigured with secret keys, usually stored locally on the TTP for following maintenance tasks. Despite some contributions already proposed for the adoption of CL-PKC schemes in constrained IoT devices, current solutions generally require high message overhead, are computationally demanding, and 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: 1) ephemeral cryptographic materials; 2) support for intermittent connectivity with the TTP; 3) lightweight rekeying operations; and 4) robustness against impersonation attacks, even when information stored on the TTP is 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 an 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.