Designing secure and robust gr ouping-proof protocols based o n RFID characte ristics becomes a hotspot in the research of security in Internet of Things (IOT). The proposed grouping-proof protocol s recently have security and/or privacy omission and these schemes afford order-dependence by relaying message among tags through an RFID reader. In consequence, aiming at enhancing the robustness, i...

We present a new general multiparty computation protocol for the cryptographic scenario which is universally composable — in particular, it is secure against an active and adaptive adversary, corrupting any minority of the parties. The protocol is as efficient as the best known statically secure solutions, in particular the number of bits broadcast (which dominates the complexity) is Ω(nk|C|), ...

Secure multiparty computation (MPC) allows a set of n parties to securely compute an agreed function, even if up to t parties are under the control of an adversary. In this paper, we propose a new Asynchronous secure multiparty computation (AMPC) protocol that provides information theoretic security with n = 4t+ 1, where t out of n parties can be under the influence of a Byzantine (active) adve...

Multiparty computation is a computation between multiple players which want to compute a common function based on private input. It was first proposed over 20 years ago and has since matured into a well established science. The goal of this thesis has been to develop efficient protocols for different operations used in multiparty computation and to propose uses for multiparty computation in rea...

Secure two-party and multiparty computation has long stood at the center of the foundations of theoretical cryptography. Recently, however, interest has grown regarding the efficiency of such protocols and their application in practice. As a result, there has been significant progress on this problem and it is possible to actually carry out secure computation for non-trivial tasks on reasonably...

Many researches on privacy preserving data mining have been done. Privacy preserving data mining can be achieved in various ways by use of randomization techniques, cryptographic algorithms, anonymization methods, etc. Further, in order to increase the security of data mining, secure multiparty computation (SMC) has been introduced. Most of works in SMC are developed on applying the model of SM...

Recently, Desmedt et al. studied the problem of achieving secure nparty computation over non-Abelian groups. They considered the passive adversary model and they assumed that the parties were only allowed to perform black-box operations over the finite group G. They showed three results for the n-product function fG(x1, . . . , xn) := x1 · x2 · . . . · xn, where the input of party Pi is xi ∈ G ...

In the setting of unconditionally-secure MPC, where dishonest players are unbounded and no cryptographic assumptions are used, it was known since the 1980’s that an honest majority of players is both necessary and sufficient to achieve privacy and correctness, assuming secure point-to-point and broadcast channels. The main open question that was left is to establish the exact communication comp...

We focus on how to securely outsource computation task to the cloud and propose a secure outsourcing multiparty computation protocol on lattice-based encrypted data in two-cloud-servers scenario. Our main idea is to transform the outsourced data respectively encrypted by different users' public keys to the ones that are encrypted by the same two private keys of the two assisted servers so that ...