Multi-cloud Storage Research Articles

Design and Implement Enhancing Security in Multi Cloud Storage System using Distributed File System

Distributed computing is a quickest developing engineering. It permits business associations to utilize or access diverse applications, store data without access their individual documents. While considering the force, strength and the security of cloud one can't disregard diverse dangers to client's information on distributed storage. Document access guarantee in true procedure to the record assurance because of entrust cloud servers. In distributed storage framework document doorway system is all the more difficult issue. This framework in result produces repetitive duplicates of comparative documents or includes a totally dependable cloud server. Assaults from enemy client are hard to stop in distributed storage. In proposed framework we are actualizing the idea of various distributed storage alongside improved security utilizing encryption strategies where rather putting away finish record on single cloud framework. The framework will part the record in distinctive lumps then encode it and store on diverse cloud. The information needed for unscrambling and revamping that document will be put away in metadata administration server for effective recovery of unique record.

Adding long-term availability, obfuscation, and encryption to multi-cloud storage systems

Nowadays, storage services offer a new way for Cloud providers to do business. This new trend is proved by the number of Cloud storage providers that are continuously appearing on the market. By now, using Cloud storage services is becoming a common practice for end-users. However, the current Cloud storage providers do not offer any guarantees regarding long-term availability and privacy. In fact, data stored in the Cloud could be locked-in, lost, or violated in terms of privacy. In this work, we present an innovative system that on one hand allows end-users to simultaneously rely on different Cloud storage providers in a transparent way and on the other hand to enforce long-term availability, obfuscation, and encryption. Our system is highly reliable, in fact, if a provider is not temporarily or permanently available, end-users continue accessing their data in a secure way. In addition, only the end-users have the full control of the overall security of their data and no sensitive information are disclosed to Cloud storage providers. Several experiments allow us to discuss the performance of our system compared against existing solutions.

Survey of Integrity Verification in Multi-Cloud Storage by Efficient Cooperative Provable Data Possession

Provable data possession (PDP) is one of the techniques to ensure the integrity of data in storage outsourcing. Here in this paper, we speak to the creation of an efficient PDP method for distributed cloud storage to maintain the scalability of service and data migration. On the basis on homomorphic verifiable response and hash index hierarchy we projected a cooperative PDP (CPDP) method. We confirm the security of our method based on multi-prover zero- knowledge proof scheme, which can satisfy knowledge soundness, fullness , and zero-knowledge properties. As well, we expressive performance optimization mechanisms for our method, and in particular present an capable method for selecting finest parameter values to reduce the addition expenses of storage service providers and client. Our experiment shows that our solution introduces lower addition and communication overheads in evaluation with non- cooperative approaches. KeywordsData Migration, Homomorphic, Multi-Prover

On the Knowledge Soundness of a Cooperative Provable Data Possession Scheme in Multicloud Storage

Provable data possession (PDP) is a probabilistic proof technique for cloud service providers (CSPs) to prove the clients' data integrity without downloading the whole data. In 2012, Zhu et al. proposed the construction of an efficient PDP scheme for multicloud storage. They studied the existence of multiple CSPs to cooperatively store and maintain the clients' data. Then, based on homomorphic verifiable response and hash index hierarchy, they presented a cooperative PDP (CPDP) scheme from the bilinear pairings. They claimed that their scheme satisfied the security property of knowledge soundness. It is regretful that this comment shows that any malicious CSP or the malicious organizer (O) can generate the valid response which can pass the verification even if they have deleted all the stored data, i.e., Zhu et al.'s CPDP scheme cannot satisfy the property of knowledge soundness. Then, we discuss the origin and severity of the security flaws. It implies that the attacker can get the pay without storing the clients' data. It is important to clarify the scientific fact to design more secure and practical CPDP scheme in Zhu et al.'s system architecture and security model.

Advanced Cooperative Provable Data Possession based Data Integrity Verification for Multi-Cloud Storage

Cloud computing is an emerging field which is raising its importance in the field of storage of data. Every individual, firm or organization wants to store data that has the limited storage capacity. For that purpose, there is need to outsource data to some Cloud Service Provider, there arises a problem of security of data. Security comes with 3 main parameters confidentiality, integrity and availability. For these issues, there is term called Provable Data Possession, it is nothing but the proof given by service provider to the data owner when there is demand by owner. Paper proposes an effective PDP model for integrity verification of data on distributed multicloud storage by using web-servers and Trusted Third Party. Here proposed the use of techniques such as, Advanced Cooperative Provable Data Possession (Advanced CPDP), Homomorphic Verifiable Response and Hash Index Hierarchy for Multiprover Zero Knowledge Proof System which is an Interactive Proof System. General Terms Security, Data Integrity on multi cloud

Cooperative Demonstrable Data Retention for Integrity Verification in Multi-Cloud Storage

Demonstrable data retention (DDR) is a technique which certain the integrity of data in storage outsourcing. In this paper we propose an efficient DDR protocol that prevent attacker in gaining information from multiple cloud storage node. Our technique is for distributed cloud storage and support the scalability of services and data migration. This technique Cooperative store and maintain the client’s data on multi cloud storage. To insure the security of our technique we use zero-knowledge proof system, which satisfies zero-knowledge properties, knowledge soundness and completeness. We present a Cooperative DDR (CDDR) protocol based on hash index hierarchy and homomorphic verification response. In order to optimize the performance of our technique we use a novel technique for selecting optimal parameter values to reduce the storage overhead and computation costs of client for service providers. Keyword: Demonstrable Data Retention, homomorphic, zero knowledge, storage outsourcing, multiple cloud, Cooperative, data Retention.

Cooperative Provable Data Possession for Integrity Verification in Multicloud Storage

Provable data possession (PDP) is a technique for ensuring the integrity of data in storage outsourcing. In this paper, we address the construction of an efficient PDP scheme for distributed cloud storage to support the scalability of service and data migration, in which we consider the existence of multiple cloud service providers to cooperatively store and maintain the clients' data. We present a cooperative PDP (CPDP) scheme based on homomorphic verifiable response and hash index hierarchy. We prove the security of our scheme based on multiprover zero-knowledge proof system, which can satisfy completeness, knowledge soundness, and zero-knowledge properties. In addition, we articulate performance optimization mechanisms for our scheme, and in particular present an efficient method for selecting optimal parameter values to minimize the computation costs of clients and storage service providers. Our experiments show that our solution introduces lower computation and communication overheads in comparison with noncooperative approaches.