Privacy Preserving Data Offloading Based on Transformation

Abstract

Mobile Cloud Computing (MCC) provides a scalable solution for both storage and computation of data over the Cloud. Though offloading benefits the execution performance, it raises new challenges regarding security. Privacy leakage risks prevent users from sharing their private data with third-party services. State-of-the-art approaches used for secure data storage are cryptography based, having an overhead of key management as well as do not support computation on encrypted data on the cloud server. However, homomorphic techniques support computation on encrypted data and generate an encrypted result, are compute intensive and not advisable due to resource constraint nature of mobile devices. This paper proposes a light-weight technique for privacy-preserving data offloading to the mobile cloud servers supporting computation. Our technique offloads the data to multiple servers instead of a single server. We have performed the security analysis for correctness, secrecy and unknown shares using various similarity measures. © 2019, Springer Nature Switzerland AG.