A Practical, Secure, and Verifiable Cloud Computing for Mobile Systems

Cloud computing systems, in which clients rent and share computing resources of third party platforms, have gained widespread use in recent years. Furthermore, cloud computing for mobile systems (i.e., systems in which the clients are mobile devices) have too been receiving considerable attention in technical literature. We propose a new method of delegating computations of resource-constrained mobile clients, in which multiple servers interact to construct an encrypted program known as garbled circuit. Next, using garbled inputs from a mobile client, another server executes this garbled circuit and returns the resulting garbled outputs. Our system assures privacy of the mobile client's data, even if the executing server chooses to collude with all but one of the other servers. We adapt the garbled circuit design of Beaver et al. and the secure multiparty computation protocol of Goldreich et al. for the purpose of building a secure cloud computing for mobile systems. Our method incorporates the novel use of the cryptographically secure pseudo random number generator of Blum et al. that enables the mobile client to efficiently retrieve the result of the computation, as well as to verify that the evaluator actually performed the computation. We analyze the server-side and client-side complexity of our system. Using real-world data, we evaluate our system for a privacy preserving search application that locates the nearest bank/ATM from the mobile client. We also measure the time taken to construct and evaluate the garbled circuit for varying number of servers, demonstrating the feasibility of our secure and verifiable cloud computing for mobile systems

A Survey on Homomorphic Encryption Schemes: Theory and Implementation

Legacy encryption systems depend on sharing a key (public or private) among the peers involved in exchanging an encrypted message. However, this approach poses privacy concerns. Especially with popular cloud services, the control over the privacy of the sensitive data is lost. Even when the keys are not shared, the encrypted material is shared with a third party that does not necessarily need to access the content. Moreover, untrusted servers, providers, and cloud operators can keep identifying elements of users long after users end the relationship with the services. Indeed, Homomorphic Encryption (HE), a special kind of encryption scheme, can address these concerns as it allows any third party to operate on the encrypted data without decrypting it in advance. Although this extremely useful feature of the HE scheme has been known for over 30 years, the first plausible and achievable Fully Homomorphic Encryption (FHE) scheme, which allows any computable function to perform on the encrypted data, was introduced by Craig Gentry in 2009. Even though this was a major achievement, different implementations so far demonstrated that FHE still needs to be improved significantly to be practical on every platform. First, we present the basics of HE and the details of the well-known Partially Homomorphic Encryption (PHE) and Somewhat Homomorphic Encryption (SWHE), which are important pillars of achieving FHE. Then, the main FHE families, which have become the base for the other follow-up FHE schemes are presented. Furthermore, the implementations and recent improvements in Gentry-type FHE schemes are also surveyed. Finally, further research directions are discussed. This survey is intended to give a clear knowledge and foundation to researchers and practitioners interested in knowing, applying, as well as extending the state of the art HE, PHE, SWHE, and FHE systems.Comment: - Updated. (October 6, 2017) - This paper is an early draft of the survey that is being submitted to ACM CSUR and has been uploaded to arXiv for feedback from stakeholder

A Blockchain-based Decentralized Electronic Marketplace for Computing Resources

AbstractWe propose a framework for building a decentralized electronic marketplace for computing resources. The idea is that anyone with spare capacities can offer them on this marketplace, opening up the cloud computing market to smaller players, thus creating a more competitive environment compared to today's market consisting of a few large providers. Trust is a crucial component in making an anonymized decentralized marketplace a reality. We develop protocols that enable participants to interact with each other in a fair way and show how these protocols can be implemented using smart contracts and blockchains. We discuss and evaluate our framework not only from a technical point of view, but also look at the wider context in terms of fair interactions and legal implications

System and method for a practical, secure and verifiable cloud computing for mobile systems

Disclosed are systems and methods for delegating computations of resource-constrained mobile clients, in which multiple servers interact to construct an encrypted program representing a garbled circuit. Implementing the garbled circuit, garbled outputs are returned. Such implementations ensure privacy of each mobile client's data, even if an executing server has been colluded. The garbled circuit provides secure cloud computing for mobile systems by incorporating cryptographically secure pseudo random number generation that enables a mobile client to efficiently retrieve a result of a computation, as well as verify that an evaluator actually performed the computation. Cloud computation and communication complexity are analyzed to demonstrate the feasibility of the proposed system for mobile systems.Board of Regents, University of Texas Syste