A Solution for Privacy-Preserving and Security in Cloud for Document Oriented Data (By Using NoSQL Database)

Cloud computing delivers massively scalable computing resources as a service with Internet based technologies those can share resources within the cloud users. The cloud offers various types of services that majorly include infrastructure as services, platform as a service, and software as a service and security as a services and deployment model as well. The foremost issues in cloud data security include data security and user privacy, data protection, data availability, data location, and secure transmission. In now day, preserving-privacy of data and user, and manipulating query from big-data is the most challenging problem in the cloud. So many researches were conducted on privacy preserving techniques for sharing data and access control; secure searching on encrypted data and verification of data integrity. This work  included preserving-privacy of document oriented data security, user privacy in the three phases those are data security at rest, at process and at transit by using Full Homomorphic encryption and decryption scheme to achieve afore most mentioned goal. This work implemented on document oriented data only by using NoSQL database and  the encryption/decryption algorithm such as RSA and Paillier’s cryptosystem in Java package with MongoDB, Apache Tomcat Server 9.1, Python, Amazon Web Service mLab for MongoDB as remote server.  Keywords: Privacy-Preserving, NoSQL, MongoDB, Cloud computing, Homomorphic encryption/decryption, public key, private key, RSA Algorithm, Paillier’s cryptosystem DOI: 10.7176/CEIS/11-3-02 Publication date:May 31st 202

D1.3 - SUPERCLOUD Architecture Implementation

In this document we describe the implementation of the SUPERCLOUD architecture. The architecture provides an abstraction layer on top of which SUPERCLOUD users can realize SUPERCLOUD services encompassing secure computation workloads, secure and privacy-preserving resilient data storage and secure networking resources spanning across different cloud service providers' computation, data storage and network resources. The components of the SUPERCLOUD architecture implementation are described. Integration between the different layers of the architecture (computing security, data protection, network security) and with the facilities for security self-management is also highlighted. Finally, we provide download and installation instructions for the released software components that can be downloaded from our common SUPERCLOUD code repository

Leveraging OpenStack and Ceph for a Controlled-Access Data Cloud

While traditional HPC has and continues to satisfy most workflows, a new generation of researchers has emerged looking for sophisticated, scalable, on-demand, and self-service control of compute infrastructure in a cloud-like environment. Many also seek safe harbors to operate on or store sensitive and/or controlled-access data in a high capacity environment. To cater to these modern users, the Minnesota Supercomputing Institute designed and deployed Stratus, a locally-hosted cloud environment powered by the OpenStack platform, and backed by Ceph storage. The subscription-based service complements existing HPC systems by satisfying the following unmet needs of our users: a) on-demand availability of compute resources, b) long-running jobs (i.e., $> 30$ days), c) container-based computing with Docker, and d) adequate security controls to comply with controlled-access data requirements. This document provides an in-depth look at the design of Stratus with respect to security and compliance with the NIH's controlled-access data policy. Emphasis is placed on lessons learned while integrating OpenStack and Ceph features into a so-called "walled garden", and how those technologies influenced the security design. Many features of Stratus, including tiered secure storage with the introduction of a controlled-access data "cache", fault-tolerant live-migrations, and fully integrated two-factor authentication, depend on recent OpenStack and Ceph features.Comment: 7 pages, 5 figures, PEARC '18: Practice and Experience in Advanced Research Computing, July 22--26, 2018, Pittsburgh, PA, US

DRSIG: Domain and Range Specific Index Generation for encrypted Cloud data

One of the most fundamental services of cloud computing is Cloud storage service. Huge amount of sensitive data is stored in the cloud for easy remote access and to reduce the cost of storage. The confidential data is encrypt before uploading to the cloud server in order to maintain privacy and security. All conventional searchable symmetric encryption(SSE) schemes enable the users to search on the entire index file. In this paper, we propose the Domain and Range Specific Index Generation(DRSIG) scheme that minimizes the Index Generation time. This scheme adopts collection sort technique to split the index file into D Domains and R Ranges. The Domain is based on the length of the keyword; the Range splits within the domain based on the first letter of the keyword. A mathematical model is used to encrypt the indexed keyword that eliminates the information leakage. The time complexity of the index generation is O(NT × 3) where NT - Number of rows in index document and 3 is Number of columns in index document. Experiments have been conducted on real world dataset to validate proposed DRSIG scheme. It is observed that DRSIG scheme is efficient and provide more secure data than Ranked Searchable Symmetric Encryption(RSSE) Scheme