Security and Privacy of Data In Multi Cloud with Data Backup and Data Recovery Service

Cloud computing is important in IT industry. Cloud service has a widespread acceptance but the fear pertaining to security and privacy of these services still continue to be an open challenge. While talking about cloud security there are many aspects which one needs to consider such as trusted authentication, authorization, data security. There are different algorithms for data encryption like RSA, AES, DES, RC4, 3DES etc. These algorithms are broadly classified as being symmetric or asymmetric in nature. While creating a secure cloud there are faced too many challenges like data protection, loss of data etc. Many security services which are certain by the secure cloud system. In that system hybrid cryptographic approach used which gives benefits of both symmetric and asymmetric encryption. That system is for single cloud and it was implemented on cloud sim framework. In cloud computing, data generated in electronic form are large in amount. To maintain this data efficiently, there is a necessity of data recovery services. This paper is about the reviews on data security and data backup/recovery in multi cloud

An Efficient and Privacy-Preserving Multiuser Cloud-Based LBS Query Scheme

Location-based services (LBSs) are increasingly popular in today’s society. People reveal their location information to LBS providers to obtain personalized services such as map directions, restaurant recommendations, and taxi reservations. Usually, LBS providers offer user privacy protection statement to assure users that their private location information would not be given away. However, many LBSs run on third-party cloud infrastructures. It is challenging to guarantee user location privacy against curious cloud operators while still permitting users to query their own location information data. In this paper, we propose an efficient privacy-preserving cloud-based LBS query scheme for the multiuser setting. We encrypt LBS data and LBS queries with a hybrid encryption mechanism, which can efficiently implement privacy-preserving search over encrypted LBS data and is very suitable for the multiuser setting with secure and effective user enrollment and user revocation. This paper contains security analysis and performance experiments to demonstrate the privacy-preserving properties and efficiency of our proposed scheme

Order-Revealing Encryption and the Hardness of Private Learning

An order-revealing encryption scheme gives a public procedure by which two ciphertexts can be compared to reveal the ordering of their underlying plaintexts. We show how to use order-revealing encryption to separate computationally efficient PAC learning from efficient $(\epsilon, \delta)$-differentially private PAC learning. That is, we construct a concept class that is efficiently PAC learnable, but for which every efficient learner fails to be differentially private. This answers a question of Kasiviswanathan et al. (FOCS '08, SIAM J. Comput. '11). To prove our result, we give a generic transformation from an order-revealing encryption scheme into one with strongly correct comparison, which enables the consistent comparison of ciphertexts that are not obtained as the valid encryption of any message. We believe this construction may be of independent interest.Comment: 28 page