In the increasingly connected world, cyber-physical systems (CPS) have been quickly adapted in many application domains, such as smart grids or healthcare. There will be more and more highly sensitive data important to the users being collected and processed in the cloud computing environments. Homomorphic Encryption (HE) offers a potential solution to safeguard privacy through cryptographic means while allowing the service providers to perform computations on the encrypted data. Throughout the process, only authorized users have access to the unencrypted data. In this paper, we provide an overview of three recent HE schemes, analyze the new optimization techniques, conduct performance evaluation, and share lessons learnt from the process of implementing these schemes. Our experiments indicate that the YASHE scheme outperforms the other two schemes we studied. The findings of this study can help others to identify a suitable HE scheme for developing solutions to safeguard private data generated or consumed by CPS.
With the growing popularity of mobile devices that have sophisticated localization capability, it becomes more convenient and tempting to give away location data in exchange for recognition and status in the social networks. Geosocial networks, as an example, offer the ability to notify a user or trigger a service when a friend is within geographical proximity. In this paper, we present two methods to support secure distance computation on encrypted location data; that is, computing distance functions without knowing the actual coordinates of users. The underlying security is ensured by the homomorphic encryption scheme which supports computation on encrypted data. We demonstrate feasibility of the proposed approaches by conducting various performance evaluations on platforms with different specifications. We argue that the novelty of this work enables a new breed of pervasive and mobile computing concepts, which was previously not possible due to the lack of feasible mechanisms that support computation on encrypted location data.
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