Multi-party Quantum Computation

We investigate definitions of and protocols for multi-party quantum computing in the scenario where the secret data are quantum systems. We work in the quantum information-theoretic model, where no assumptions are made on the computational power of the adversary. For the slightly weaker task of verifiable quantum secret sharing, we give a protocol which tolerates any t < n/4 cheating parties (out of n). This is shown to be optimal. We use this new tool to establish that any multi-party quantum computation can be securely performed as long as the number of dishonest players is less than n/6.Comment: Masters Thesis. Based on Joint work with Claude Crepeau and Daniel Gottesman. Full version is in preparatio

Secret Sharing for Cloud Data Security

Cloud computing helps reduce costs, increase business agility and deploy solutions with a high return on investment for many types of applications. However, data security is of premium importance to many users and often restrains their adoption of cloud technologies. Various approaches, i.e., data encryption, anonymization, replication and verification, help enforce different facets of data security. Secret sharing is a particularly interesting cryptographic technique. Its most advanced variants indeed simultaneously enforce data privacy, availability and integrity, while allowing computation on encrypted data. The aim of this paper is thus to wholly survey secret sharing schemes with respect to data security, data access and costs in the pay-as-you-go paradigm

A Randomized Kernel-Based Secret Image Sharing Scheme

This paper proposes a ($k,n$)-threshold secret image sharing scheme that offers flexibility in terms of meeting contrasting demands such as information security and storage efficiency with the help of a randomized kernel (binary matrix) operation. A secret image is split into $n$ shares such that any $k$ or more shares ($k\leq n$) can be used to reconstruct the image. Each share has a size less than or at most equal to the size of the secret image. Security and share sizes are solely determined by the kernel of the scheme. The kernel operation is optimized in terms of the security and computational requirements. The storage overhead of the kernel can further be made independent of its size by efficiently storing it as a sparse matrix. Moreover, the scheme is free from any kind of single point of failure (SPOF).Comment: Accepted in IEEE International Workshop on Information Forensics and Security (WIFS) 201

An Effective Private Data storage and Retrieval System using Secret sharing scheme based on Secure Multi-party Computation

Privacy of the outsourced data is one of the major challenge.Insecurity of the network environment and untrustworthiness of the service providers are obstacles of making the database as a service.Collection and storage of personally identifiable information is a major privacy concern.On-line public databases and resources pose a significant risk to user privacy, since a malicious database owner may monitor user queries and infer useful information about the customer.The challenge in data privacy is to share data with third-party and at the same time securing the valuable information from unauthorized access and use by third party.A Private Information Retrieval(PIR) scheme allows a user to query database while hiding the identity of the data retrieved.The naive solution for confidentiality is to encrypt data before outsourcing.Query execution,key management and statistical inference are major challenges in this case.The proposed system suggests a mechanism for secure storage and retrieval of private data using the secret sharing technique.The idea is to develop a mechanism to store private information with a highly available storage provider which could be accessed from anywhere using queries while hiding the actual data values from the storage provider.The private information retrieval system is implemented using Secure Multi-party Computation(SMC) technique which is based on secret sharing. Multi-party Computation enable parties to compute some joint function over their private inputs.The query results are obtained by performing a secure computation on the shares owned by the different servers.Comment: Data Science & Engineering (ICDSE), 2014 International Conference, CUSA

Ideal Tightly Couple (t,m,n) Secret Sharing

As a fundamental cryptographic tool, (t,n)-threshold secret sharing ((t,n)-SS) divides a secret among n shareholders and requires at least t, (t<=n), of them to reconstruct the secret. Ideal (t,n)-SSs are most desirable in security and efficiency among basic (t,n)-SSs. However, an adversary, even without any valid share, may mount Illegal Participant (IP) attack or t/2-Private Channel Cracking (t/2-PCC) attack to obtain the secret in most (t,n)-SSs.To secure ideal (t,n)-SSs against the 2 attacks, 1) the paper introduces the notion of Ideal Tightly cOupled (t,m,n) Secret Sharing (or (t,m,n)-ITOSS ) to thwart IP attack without Verifiable SS; (t,m,n)-ITOSS binds all m, (m>=t), participants into a tightly coupled group and requires all participants to be legal shareholders before recovering the secret. 2) As an example, the paper presents a polynomial-based (t,m,n)-ITOSS scheme, in which the proposed k-round Random Number Selection (RNS) guarantees that adversaries have to crack at least symmetrical private channels among participants before obtaining the secret. Therefore, k-round RNS enhances the robustness of (t,m,n)-ITOSS against t/2-PCC attack to the utmost. 3) The paper finally presents a generalized method of converting an ideal (t,n)-SS into a (t,m,n)-ITOSS, which helps an ideal (t,n)-SS substantially improve the robustness against the above 2 attacks