Ciarán McGoldrick

Josh Joy, Dylan Gray, Ciaran McGoldrick et al.

Future autonomous vehicles will generate, collect, aggregate and consume significant volumes of data as key gateway devices in emerging Internet of Things scenarios. While vehicles are widely accepted as one of the most challenging mobility contexts in which to achieve effective data communications, less attention has been paid to the privacy of data emerging from these vehicles. The quality and usability of such privatized data will lie at the heart of future safe and efficient transportation solutions. In this paper, we present the XYZ Privacy mechanism. XYZ Privacy is to our knowledge the first such mechanism that enables data creators to submit multiple contradictory responses to a query, whilst preserving utility measured as the absolute error from the actual original data. The functionalities are achieved in both a scalable and secure fashion. For instance, individual location data can be obfuscated while preserving utility, thereby enabling the scheme to transparently integrate with existing systems (e.g. Waze). A new cryptographic primitive Function Secret Sharing is used to achieve non-attributable writes and we show an order of magnitude improvement from the default implementation.

Sean Rowan, Michael Clear, Mario Gerla et al.

Autonomous and self-driving vehicles are appearing on the public highways. These vehicles commonly use wireless communication techniques for both vehicle-to-vehicle and vehicle-to-infrastructure communications. Manufacturers, regulators and the public are understandably concerned about large-scale systems failure or malicious attack via these wireless vehicular networks. This paper explores the use of sensing and signalling devices that are commonly integrated into modern vehicles for side-channel communication purposes. Visible light (using a CMOS camera) and acoustic (ultrasonic audio) side-channel encoding techniques are proposed, developed and evaluated in this context. The side-channels are examined both theoretically and experimentally and an upper bound on the line code modulation rate that is achievable with these side channel schemes in the vehicular networking context is established. A novel inter-vehicle session key establishment protocol, leveraging both side-channels and a blockchain public key infrastructure, is then presented. In light of the limited channel capacity and the interoperability/security requirements for vehicular communications, techniques for constraining the throughput requirement, providing device independence and validating the location of the intended recipient vehicle, are presented. These reduce the necessary device handshake throughput to 176 bits for creating symmetric encryption and message authentication keys and in verifying a vehicle's certificate with a recognised certification authority.

Joshua Joy, Ciaran McGoldrick, Mario Gerla

Smart cities rely on dynamic and real-time data to enable smart urban applications such as intelligent transport and epidemics detection. However, the streaming of big data from IoT devices, especially from mobile platforms like pedestrians and cars, raises significant privacy concerns. Future autonomous vehicles will generate, collect and consume significant volumes of data to be utilized in delivering safe and efficient transportation solutions. The sensed data will, inherently, contain personally identifiable and attributable information - both external (other vehicles, environmental) and internal (driver, passengers, devices). The autonomous vehicles are connected to the infrastructure cloud (e.g., Amazon), the edge cloud, and also the mobile cloud (vehicle to vehicle). Clearly these different entities must co-operate and interoperate in a timely fashion when routing and transferring the highly dynamic data. In order to maximise the availability and utility of the sensed data, stakeholders must have confidence that the data they transmit, receive, aggregate and reason on is appropriately secured and protected throughout. There are many different metaphors for providing end-to-end security for data exchanges, but they commonly require a management and control sidechannel. This work proposes a scalable smart city privacy-preserving architecture named Authorized Analytics that enables each node (e.g. vehicle) to divulge (contextually) local privatised data. Authorized Analytics is shown to scale gracefully to IoT scope deployments.