Abstract. We present an efficient secure and privacy-enhancing protocol for car access provision, named SePCAR. The protocol is fully decentralised and allows users to share their cars conveniently without sacrifising their security and privacy. It provides generation, update, revocation, and distribution mechanisms for access tokens to shared cars, as well as procedures to solve disputes and to deal with law enforcement requests, for instance in the case of car incidents. We prove that SeP-CAR meets its appropriate security and privacy requirements and that it is efficient: our practical efficiency analysis through a proof-of-concept implementation shows that SePCAR takes only 1.55 seconds for a car access provision.

Smart grid allows fine-grained smart metering data collection which can improve the efficiency and reliability of the grid. Unfortunately, this vast collection of data also impose risks to users' privacy. In this paper, we propose a novel protocol that allows suppliers and grid operators to collect users' aggregate metering data in a secure and privacy-preserving manner. We use secure multiparty computation to ensure privacy protection. In addition, we propose three different data aggregation algorithms that offer different balances between privacy-protection and performance. Our protocol is designed for a realistic scenario in which the data need to be sent to different parties, such as grid operators and suppliers. Furthermore, it facilitates an accurate calculation of transmission, distribution and grid balancing fees in a privacy-preserving manner. We also present a security analysis and a performance evaluation of our protocol based on existing multiparty computation algorithms.

In this work, we examine the efficiency of protocols for secure evaluation of basic mathematical functions (sqrt, sin, arcsin, amongst others), essential to various application domains. e.g., Artificial Intelligence. Furthermore, we have incorporated our code in state-of-the-art Multiparty Computation (MPC) software, so we can focus on the algorithms to be used as opposed to the underlying MPC system. We make use of practical approaches that, although, some of them, theoretically can be regarded as less efficient, can, nonetheless, be implemented in such software libraries without further adaptation. We focus on basic scientific operations, and introduce a series of data-oblivious protocols based on fixed point representation techniques. Our protocols do not reveal intermediate values and do not need special adaptations from the underlying MPC protocols. We include extensive computational experimentation under various settings and MPC protocols.