HAC: Model for privacy-preserving outsourced data over cloud

Abstract

Organizations, companies, even individuals can benefit the amazing advantages of the cloud only when they find that their data is securely processed and stored in the cloud. This makes it necessary to build and develop techniques and models to effectively maintain data privacy before outsourcing it to the cloud. Most of the current techniques seek to avoid data disclosures that lead to privacy leakage. Unfortunately, these techniques still suffer from some types of attacks, adding to the issue of data utility that decreases due to execute the privacy preservation operations. This paper presents a model that avoids two types of data disclosures to prevent privacy leakage. The proposed model is based on combining one of the encryption techniques, which is partial homomorphic encryption, with the anonymization technique, which is k-anonymity. The results demonstrated the effectiveness of the proposed model in improving the level of privacy-preserving at the same time reducing the percentage of the lost data compared to a similar modern model.