SARRC: Secure Auditing and Re-signing of Revoked Customer Chunks by Cloud Using Regression Method
Conference
Geeta, CM, Usharani, Shreyas Raju, RG et al. (2018). SARRC: Secure Auditing and Re-signing of Revoked Customer Chunks by Cloud Using Regression Method
. 10.1109/ICINPRO43533.2018.9096696
Geeta, CM, Usharani, Shreyas Raju, RG et al. (2018). SARRC: Secure Auditing and Re-signing of Revoked Customer Chunks by Cloud Using Regression Method
. 10.1109/ICINPRO43533.2018.9096696
The demand of deploying information has enormously increased within the last decade. Numerous distributed computing service suppliers have emerged (for eg., Microsoft Azure, Dropbox) in order to satisfy the requirements for information repository and high performance computation. The customers using the cloud repository services can conveniently arrange as a cluster and distribute information among themselves. Information proprietor computes the signatures for every chunk and deploys in the distributed server in order to allow the public verifier to perform public integrity verification on the information stored on the cloud server. In Panda scheme [1], by using the proxy re-signatures, Cloud Service Provider (CSP) verifies and re-signs the revoked customer chunks in favor of the existing customers. The malicious CSP might use the Resign key deliberately to transform the signature of one customer to another. Apart from this, conspiracy amidst the mischievous cloud server and the repudiated customer reveals the private key information of the customers present in the cluster. We propose Secure Auditing and Re-signing of Revoked Customer Chunks by Cloud Using Regression Method. Re-key computed by the information proprietor using regression method is highly secure and the mischievious cloud cannot detect the private information of the customers in the cluster. Our mechanism is collusion resistant, reduces computation cost of re-sign key by information proprietor and in addition CSP securely performs auditing and re-signing of repudiated customer chunks.
