Tutorial I: Security and privacy of big data in a cloud environment

Abstract

Security and privacy of big data is of primary concern for many applications. For example, in case of smart meters, data of the consumers must be protected else private information can be leaked. Similarly, due to the cost-efficiency, reduced overhead management and dynamic resource needs, content owners are outsourcing their data to the cloud who can act as a service provider on their behalf. However, by outsourcing their data to the cloud, the owners may lose access control and privacy of data as cloud becomes a third party. By using these data storage services, the data owners can relieve the burden of local data storage and maintenance. However, since data owners and the cloud servers are not in the same trusted domain, the outsourced data may be at risk as the cloud server may no longer be fully trusted. Therefore, data integrity is of critical importance. Cloud should let the owners or a trusted third party to check for the integrity of their data storage without demanding a local copy of the data. Owners often replicate their data on the cloud servers across multiple data centers to provide a higher level of scalability, availability, and durability. However, the data owners need to be strongly convinced that the cloud is storing data copies agreed on in the service level contract, and data-updates have been correctly executed on all the remotely stored copies. In this tutorial, some of these problems will be explored. Some of the topics to be covered include: Security and Privacy Issues in Big Data Management, Secure Data Processing and Access Control of Big Data in Cloud, Data Integrity Verification of Big Data in Cloud, and Security and Privacy of Sensing Data for Big Data Applications.