Visible to the public De Duplication Scalable Secure File Sharing on Untrusted Storage in Big Data

TitleDe Duplication Scalable Secure File Sharing on Untrusted Storage in Big Data
Publication TypeConference Paper
Year of Publication2017
AuthorsKeerthana, S., Monisha, C., Priyanka, S., Veena, S.
Conference Name2017 International Conference on Information Communication and Embedded Systems (ICICES)
ISBN Number978-1-5090-6135-8
Keywordsancient secret writing, Big Data, ciphertexts, cloud computing, composability, confluent key, convergent secret writing, cryptographical hash price, cryptography, data privacy, decryption, deduplication scalable secure file sharing, Embedded systems, encoding, Encryption, hashkey, Human Behavior, information copy, knowledge confidentiality, knowledge copy, knowledge deduplication, Metrics, Peer-to-peer computing, privacy issues, pubcrawl, Public key, resilience, Resiliency, Secure File Sharing, security, security issues, sensitive data, storage, Token, untrusted storage, Writing
Abstract

Data Deduplication provides lots of benefits to security and privacy issues which can arise as user's sensitive data at risk of within and out of doors attacks. Traditional secret writing that provides knowledge confidentiality is incompatible with knowledge deduplication. Ancient secret writing wants completely different users to encode their knowledge with their own keys. Thus, identical knowledge copies of completely different various users can result in different ciphertexts that makes Deduplication not possible. Convergent secret writing has been planned to enforce knowledge confidentiality whereas creating Deduplication possible. It encrypts/decrypts a knowledge copy with a confluent key, that is obtained by computing the cryptographical hash price of the content of the information copy. Once generation of key and encryption, the user can retain the keys and send ciphertext to cloud.

URLhttps://ieeexplore.ieee.org/document/8070763/
DOI10.1109/ICICES.2017.8070763
Citation Keykeerthana_duplication_2017