Enhancing Data Dynamic Security & Trust for Cloud Computing Storage System

No Abstrac

An Improved Integrated Hash and Attributed based Encryption Model on High Dimensional Data in Cloud Environment

Cloud computing is a distributed architecture where user can store their private, public or any application software components on it. Many cloud based privacy protection solutions have been implemented, however most of them only focus on limited data resources and storage format. Data confidentiality and inefficient data access methods are the major issues which block the cloud users to store their high dimensional data. With more and more cloud based applications are being available and stored on various cloud servers, a novel multi-user based privacy protection mechanism need to design and develop to improve the privacy protection on high dimensional data. In this paper, a novel integrity algorithm with attribute based encryption model was implemented to ensure confidentiality for high dimensional data security on cloud storage. The main objective of this model is to store, transmit and retrieve the high dimensional cloud data with low computational time and high security. Experimental results show that the proposed model has high data scalability, less computational time and low memory usage compared to traditional cloud based privacy protection models

“Implementation on Distorted Fingerprints”

Flexible distortion of fingerprints is the main origin of false non-match. While this origin disturbs all fingerprint recognition applications, it is mainly risk in negative recognition applications, such as watch list duplication applications. In such things, malignant user mayconsciously distort their fingerprints to hide his originality or identification. This paper, suggested novel algorithms to identify and modify skin distortion based on a single fingerprint image. Distortion detection is displayed as a two-class categorization problem, for which the registered ridge orientation map and period map of a fingerprint are beneficial as the feature vector and a SVM classifier is trained to act the classification task. Distortion rectification (or equivalently distortion field estimation) is viewed as a regression complication, where provide the input as a distorted fingerprint and generate the output as distortion field. To clarify this Problem, offline and online stages are important. A database (called reference database) of various distorted reference fingerprints and corresponding distortion fields is built in the offline stage, and then in the online stage, the closest neighbor of the input fingerprint is organized in the reference database and the corresponding distortion field is used to transform (Convert) the input distorted fingerprint into a normal undistorted fingerprints

Audita: A Blockchain-based Auditing Framework for Off-chain Storage

The cloud changed the way we manage and store data. Today, cloud storage services offer clients an infrastructure that allows them a convenient source to store, replicate, and secure data online. However, with these new capabilities also come limitations, such as lack of transparency, limited decentralization, and challenges with privacy and security. And, as the need for more agile, private and secure data solutions continues to grow exponentially, rethinking the current structure of cloud storage is mission-critical for enterprises. By leveraging and building upon blockchain's unique attributes, including immutability, security to the data element level, distributed (no single point of failure), we have developed a solution prototype that allows data to be reliably stored while simultaneously being secured, with tamper-evident auditability, via blockchain. The result, Audita, is a flexible solution that assures data protection and solves challenges such as scalability and privacy. Audita works via an augmented blockchain network of participants that include storage-nodes and block-creators. In addition, it provides an automatic and fair challenge system to assure that data is distributed and reliably and provably stored. While the prototype is built on Quorum, the solution framework can be used with any blockchain platform. The benefit is a system that is built to grow along with the data needs of enterprises, while continuing to build the network via incentives and solving for issues such as auditing and outsourcing