Privacy, Access Control, and Data Integrity for Large Graph Databases
Graph data is extensively utilized in social networks, collaboration networks, geo-social networks, and communication networks, etc. Their growing usage in cyberspaces poses daunting security and privacy challenges. Data publication requires privacy-protection mechanisms to guard against information breaches. In addition, access control mechanisms can be used to allow controlled sharing of data. Provision of privacy-protection, access control, and data integrity for graph data require a holistic approach for data management and secure query processing.
In this talk, I will address two notable challenges for graph databases, which are: (i) how to ensure users’ privacy in published graph data under an access control policy enforcement?, and (ii) how to verify the integrity and query results of graph datasets? To address the first challenge, a privacy-protection framework under role-based access control (RBAC) policy constraints is proposed. The design of such a framework poses a trade-off problem, which is proved to be NP-complete. Novel heuristic solutions are provided to solve the constraint problem. To the best of our knowledge, this is the first scheme that studies the trade-off between RBAC policy constraints and privacy-protection for graph data. To address the second challenge, a cryptographic security model based on Hash Message Authentic Codes (HMACs) is proposed. The model ensures integrity and completeness verification of data and query results under both two-party and third-party data distribution environments. Unique solutions based on HMACs for integrity verification of graph data are developed and a detailed security analysis is provided for the proposed schemes. Extensive experimental evaluations are conducted to illustrate the performance of proposed algorithms.
Muhammad Umer Arshad received the BSc and MSc degrees in electrical engineering from the University of Engineering and Technology, Lahore, Pakistan, and the MS and PhD degrees in computer engineering from Purdue University, West Lafayette, Indiana, in 2002, 2005, 2014 and 2016, respectively. During the summer of 2015, he was an R&D intern with the Converged Infrastructure Group at VMWare, Palo Alto, CA. He is currently a senior member of technical staff at Salesforce, San Francisco, CA. His current research interests include cloud computing and the web-scale data management and systems.