With the advent of cloud storage and computing, adopting cloud services to reduce operational, maintenance and storage costs, is becoming increasingly common --- both for individuals and corporations. However, the fact that the data owner is not in physical possession of the data anymore raises important challenges in terms of integrity of data. Moreover, this is more than just a theoretical risk, since third party service providers are typically allowed to access the remotely stored data. Such risks raise obvious privacy issues. Along with such important security and privacy concerns, efficiency is also a major factor in such settings, as the main motivations for adopting cloud computing—namely scalability and computation offloading—are defeated otherwise. 

In this talk I will discuss our work on efficient privacy-preserving protocols addressing the above challenges for a large class of data queries. I will first describe our proposed model and then discuss protocols for set queries, order queries for trees and DAG's and range queries. This talk is based on the following papers:

    1.     E. Ghosh, O. Ohrimenko, and R. Tamassia. Zero-knowledge authenticated order queries and order statistics on a list. In Applied Cryptography and Network Security, 2015. 
    2.     E. Ghosh, M. T. Goodrich, O. Ohrimenko, and R. Tamassia. Fully-dynamic verifiable zero-knowledge order queries for network data. Cryptology ePrint Archive, Report 2015/283, 2015. In submission. 
    3.     E. Ghosh, O. Ohrimenko, D. Papadopoulos, R. Tamassia, and N. Triandopoulos. Zero-knowledge accumulators and set operations. Cryptology ePrint Archive, Report 2015/404, 2015. In submission. 
    4.     E. Ghosh, O. Ohrimenko, and R. Tamassia. Authentiated range & closest point queries in zero-knowledge, 2015. In submission.