Secure multiparty computation considers the problem of different parties computing a joint function of their separate, private inputs without revealing any extra information about these inputs than that is leaked by just the result of the computation. This setting is well motivated, and captures many different applications. Considering some of these applications will provide intuition about how...

1.1. Secure Two-Party Computation. In essence, secure multiparty computation is the solution to the problem how to compute on private inputs from several parties when we do not trust other parties and we don’t have a central authority who can get inputs, perform computations and give outputs to those that need them. Here we will talk about secure twoparty computation, where Alice, holding xa an...

The round complexity of secure computation has been a fundamental problem in cryptography. Katz and Ostrovsky proved that 5 rounds are both necessary and sufficient for secure computation in the stand alone setting, thus resolving the exact round complexity of standalone secure computation. In contrast, round complexity of secure computation in the concurrent setting, where several protocols ma...

Secure computation consists of protocols for secure arithmetic: secret values are added and multiplied securely by networked processors. The striking feature of secure computation is that security is maintained even in the presence of an adversary who corrupts a quorum of the processors and who exercises full, malicious control over them. One of the fundamental primitives at the heart of secure...

Secure Multiparty Computation (SMC) allows parties to know the result of cooperative computation while preserving privacy of individual data. Secure sum computation is an important application of SMC. In our proposed protocols parties are allowed to compute the sum while keeping their individual data secret with increased computation complexity for hacking individual data. In this paper the dat...

Motivated by the impossibility of achieving fairness in secure computation [Cleve, STOC 1986], recent works study a model of fairness in which an adversarial party that aborts on receiving output is forced to pay a mutually predefined monetary penalty to every other party that did not receive the output. These works show how to design protocols for secure computation with penalties that guarant...

Consider a set of parties who do not trust each other but want to compute some agreed function of their inputs in a secure way. This problem is known as multi-party computation. It has various interesting applications including election over the internet, electric contracts, private and secret database, joint signatures, and others. A number of techniques for the problem have been proposed. Sec...

Title of dissertation: TRACE OBLIVIOUS PROGRAM EXECUTION Chang Liu, Doctor of Philosophy, 2016 Dissertation directed by: Professor Michael Hicks Department of Computer Science, University of Maryland and Professor Elaine Shi Department of Computer Science, Cornell University The big data era has dramatically transformed our lives; however, security incidents such as data breaches can put sensit...

Secure two-party computation enables two parties to evaluate a function cooperatively without revealing to either party anything beyond the function’s output. The garbled-circuit technique, a generic approach to secure two-party computation for semi-honest participants, was developed by Yao in the 1980s, but has been viewed as being of limited practical significance due to its inefficiency. We ...

The popularity of internet as a communication medium whether for personal or business requires anonymous communication in various ways. Businesses also have legitimate reasons to make communication anonymous and avoid the consequences of identity revelation. The problem of sharing privately held data so that the individuals who are the subjects of the data cannot be identified has been research...