• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5616-5630
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• 2019

Fully homomorphic encryption allows a third-party to perform arbitrary computation over encrypted data and is especially suitable for secure outsourced computation. This paper investigates secure outsourced computation of multiple matrix multiplication based on fully homomorphic encryption. Our work significantly improves the latest Mishra et al.'s work. We improve Mishra et al.'s matrix encoding method by introducing a column-order matrix encoding method which requires smaller parameter. This enables us to develop a binary multiplication method for multiple matrix multiplication, which multiplies pairwise two adjacent matrices in the tree structure instead of Mishra et al.'s sequential matrix multiplication from left to right. The binary multiplication method results in a logarithmic-depth circuit, thus is much more efficient than the sequential matrix multiplication method with linear-depth circuit. Experimental results show that for the product of ten 32×32 (64×64) square matrices our method takes only several thousand seconds while Mishra et al.'s method will take about tens of thousands of years which is astonishingly impractical. In addition, we further generalize our result from square matrix to non-square matrix. Experimental results show that the binary multiplication method and the classical dynamic programming method have a similar performance for ten non-square matrices multiplication.

• Journal of KIISE
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• v.41 no.10
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• pp.799-809
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• 2014

In this paper, we address the problem of computing Pearson correlation coefficients and Spearman's rank correlation coefficients in a secure manner while data providers preserve privacy of their own data in distributed environment. For a data mining or data analysis in the distributed environment, data providers(data owners) need to share their original data with each other. However, the original data may often contain very sensitive information, and thus, data providers do not prefer to disclose their original data for preserving privacy. In this paper, we formally define the secure correlation computation, SCC in short, as the problem of computing correlation coefficients in the distributed computing environment while preserving the data privacy (i.e., not disclosing the sensitive data) of multiple data providers. We then present SCC solutions for Pearson and Spearman's correlation coefficients using secure scalar product. We show the correctness and secure property of the proposed solutions by presenting theorems and proving them formally. We also empirically show that the proposed solutions can be used for practical applications in the performance aspect.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.431-443
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• 2016

Secure multi-party computation (MPC) has been a research focus of cryptography in resent studies. However, hiding the topology of the network in secure computation is a rather novel goal. Inspired by a seminal paper [1], we proposed a topology-hiding broadcast protocol based on NTRUEncrypt and secret sharing. The topology is concealed as long as any part of the network is corrupted. And we also illustrated the merits of our protocol by performance and security analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.3
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• pp.411-427
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• 2010

Data sharing is an essential process for collaborative works particularly in the banking, finance and healthcare industries. These industries require many collaborative works with their internal and external parties such as branches, clients, and service providers. When data are shared among collaborators, security and privacy concerns becoming crucial issues and cannot be avoided. Privacy is an important issue that is frequently discussed during the development of collaborative systems. It is closely related with the security issues because each of them can affect the other. The tradeoff between privacy and security is an interesting topic that we are going to address in this paper. In view of the practical problems in the existing approaches, we propose a collaborative framework which can be used to facilitate concurrent operations, single point failure problem, and overcome constraints for two-party computation. Two secure computation protocols will be discussed to demonstrate our collaborative framework.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.61-66
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• 2019

FinTech has expanded to the extent that not only businesses but almost everyone can feel the impact. The spread of the scope of use has introduced a variety of new financial services that are changing the way we live. In these environments, it is important to develop reliable security measures to protect against cyber attacks. The number of mobile financial transactions in the financial sector is also increasing, making security vulnerable. In this study, we studied security through mutual authentication method that can safely handle financial security and focused on FinTech's security processing through multi-party mutual authentication method that strongly prevents leakage of information even in the event of continuous and sophisticated attacks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.878-894
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• 2013

Secure multimedia multicast applications involve group communications where group membership requires secured dynamic key generation and updating operations. Such operations usually consume high computation time and therefore designing a key distribution protocol with reduced computation time is necessary for multicast applications. In this paper, we propose a new key distribution protocol that focuses on two aspects. The first one aims at the reduction of computation complexity by performing lesser numbers of multiplication operations using a ternary-tree approach during key updating. Moreover, it aims to optimize the number of multiplication operations by using the existing Karatsuba divide and conquer approach for fast multiplication. The second aspect aims at reducing the amount of information communicated to the group members during the update operations in the key content. The proposed algorithm has been evaluated based on computation and communication complexity and a comparative performance analysis of various key distribution protocols is provided. Moreover, it has been observed that the proposed algorithm reduces the computation and communication time significantly.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.833-840
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• 2015

In this paper, we are interested in a generalization of zero-knowledge interactive protocols between prover and verifier, especially to show that the product of an encrypted polynomial and a random polynomial, but published by a secure commitment scheme was correctly computed by the prover. To this end, we provide a generalized protocol for proving that the resulting polynomial is correctly computed by an encrypted polynomial and another committed polynomial. Further we show that the protocol is also secure in the random oracle model. We expect that our generalized protocol can play a role of building blocks in implementing secure multi-party computation including private set operations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5B
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• pp.526-531
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• 2009

In this paper, we propose new novel technique (ILCT: Instruction-Level Correlation Technique) which can detect tempered instructions by software attacks or hardware attacks before their execution. In conventional works, due to both high complex computation of cipher process and low processing speed of cipher modules, existing secure processor architecture applying cipher technique can cause serious performance degradation. While, the secure processor architecture applying ILCT with FEC does not incur excessive performance decrease by complexity of computation and speed of tampering detection modules. According to experimental results, total memory overhead including parity are increased in average of 26.62%. Also, secure programs incur CPI degradation in average of $1.20%{\sim}1.97%$.

• Journal of KIISE
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• v.42 no.7
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• pp.919-928
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• 2015

In recent years, many research efforts have been made on privacy-preserving data mining (PPDM) in data of large volume. In this paper, we propose a PPDM solution based on principal component analysis (PCA), which can be widely used in computing correlation among sensitive data sets. The general method of computing PCA is to collect all the data spread in multiple nodes into a single node before starting the PCA computation; however, this approach discloses sensitive data of individual nodes, involves a large amount of computation, and incurs large communication overheads. To solve the problem, in this paper, we present an efficient method that securely computes PCA without the need to collect all the data. The proposed method shares only limited information among individual nodes, but obtains the same result as that of the original PCA. In addition, we present a dimensionality reduction technique for the proposed method and use it to improve the performance of secure similar document detection. Finally, through various experiments, we show that the proposed method effectively and efficiently works in a large amount of multi-dimensional data.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.77-84
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• 2023

This research originated from the need to enhance the security of secure multiparty computation by ensuring that participants involved in multiparty computations provide truthful inputs that have not been manipulated. While malicious participants can be involved, which goes beyond the traditional security models, malicious behaviors through input manipulation often occur in real-world scenarios, leading to privacy infringements or situations where the accuracy of multiparty computation results cannot be guaranteed. Therefore, in this study, we propose a signature scheme applicable to secure multiparty technologies, combining it with secret sharing to strengthen the accuracy of inputs using authentication techniques. We also investigate methods to enhance the efficiency of authentication through the use of batch authentication techniques. To this end, a scheme capable of input certification was designed by applying a commitment scheme and zero-knowledge proof of knowledge to the CL signature scheme, which is a lightweight signature scheme, and batch verification was applied to improve efficiency during authentication.