PRE+: dual of proxy re-encryption for secure cloud data sharing service

With the rapid development of very large, diverse, complex, and distributed datasets generated from internet transactions, emails, videos, business information systems, manufacturing industry, sensors and internet of things etc., cloud and big data computation have emerged as a cornerstone of modern applications. Indeed, on the one hand, cloud and big data applications are becoming a main driver for economic growth. On the other hand, cloud and big data techniques may threaten people and enterprises’ privacy and security due to ever increasing exposure of their data to massive access. In this paper, aiming at providing secure cloud data sharing services in cloud storage, we propose a scalable and controllable cloud data sharing framework for cloud users (called: Scanf). To this end, we introduce a new cryptographic primitive, namely, PRE+, which can be seen as the dual of traditional proxy re-encryption (PRE) primitive. All the traditional PRE schemes until now require the delegator (or the delegator and the delegatee cooperatively) to generate the re-encryption keys. We observe that this is not the only way to generate the re-encryption keys, the encrypter also has the ability to generate re-encryption keys. Based on this observation, we construct a new PRE+ scheme, which is almost the same as the traditional PRE scheme except the re-encryption keys generated by the encrypter. Compared with PRE, our PRE+ scheme can easily achieve the non-transferable property and message-level based fine-grained delegation. Thus our Scanf framework based on PRE+ can also achieve these two properties, which is very important for users of cloud storage sharing service. We also roughly evaluate our PRE+ scheme’s performance and the results show that our scheme is efficient and practica for cloud data storage applications.Peer ReviewedPostprint (author's final draft

Storage Solutions for Big Data Systems: A Qualitative Study and Comparison

Big data systems development is full of challenges in view of the variety of application areas and domains that this technology promises to serve. Typically, fundamental design decisions involved in big data systems design include choosing appropriate storage and computing infrastructures. In this age of heterogeneous systems that integrate different technologies for optimized solution to a specific real world problem, big data system are not an exception to any such rule. As far as the storage aspect of any big data system is concerned, the primary facet in this regard is a storage infrastructure and NoSQL seems to be the right technology that fulfills its requirements. However, every big data application has variable data characteristics and thus, the corresponding data fits into a different data model. This paper presents feature and use case analysis and comparison of the four main data models namely document oriented, key value, graph and wide column. Moreover, a feature analysis of 80 NoSQL solutions has been provided, elaborating on the criteria and points that a developer must consider while making a possible choice. Typically, big data storage needs to communicate with the execution engine and other processing and visualization technologies to create a comprehensive solution. This brings forth second facet of big data storage, big data file formats, into picture. The second half of the research paper compares the advantages, shortcomings and possible use cases of available big data file formats for Hadoop, which is the foundation for most big data computing technologies. Decentralized storage and blockchain are seen as the next generation of big data storage and its challenges and future prospects have also been discussed