• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6121-6144
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• 2019

Numerous privacy-preserving authentication schemes have been proposed but vehicular ad hoc networks (VANETs) still suffer from security and privacy issues as well as computation and communication overheads. In this paper, we proposed a robust conditional privacy-preserving authentication scheme based on pseudonym root with cuckoo filter to meet security and privacy requirements and reduce computation and communication overheads. In our proposed scheme, we used a new idea to generate pseudonyms for vehicles where each on-board unit (OBU) saves one pseudonym, named as "pseudonym root," and generates all pseudonyms from the same pseudonym. Therefore, OBU does not need to enlarge its storage. In addition, the scheme does not use bilinear pairing operation that causes computation overhead and has no certification revocation list that leads to computation and communication overheads. The proposed scheme has lightweight mutual authentication among all parties and just for once. Moreover, it provides strong anonymity to preserve privacy and resists ordinary attacks. We analyzed our proposed scheme and showed that it meets security and privacy requirements of VANETs and is more efficient than traditional schemes. The communication and computation overheads were also discussed to show the cost-effectiveness of the proposed scheme.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.12
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• pp.632-641
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• 2001

In this paper, we introduce new methods for hiding computation overheads involved in load redistributing for parallel computer of hypercube, mesh and tree topologies. The basic idea is either coalescing some phases of load redistributing to overlap the transfer on different links or dividing each phase into steps to pipeline the transfer of load unit by unit for maximum utilization of links. They proved effective in making links busy transmitting load as soon as possible, hence reducing the computation overheads involved in balancing. Proposed techniques experimented on hypercube, mesh or tree topologies reduce communication overheads by 20% to 50% compared with known methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.1157-1177
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• 2014

Convertible authenticated encryption (CAE) schemes enable the signer to send a confidential message and its corresponding signature to the designated recipient. The recipient can also convert the signature into a conventional one which can be verified by anyone. Integrating the properties of self-certified public key systems, this paper presents efficient and computationally indistinguishable self-certified CAE schemes for strengthening the security of E-Commerce applications. Additionally, we also adapt the proposed schemes to elliptic curve systems for facilitating the applications of limited computing power and insufficient storage space. The proposed schemes are secure against known existential active attacks, satisfy the semantic security requirement, and have the following advantages: (i) No extra certificate is required since the tasks of authenticating the public key and verifying the signature can be simultaneously carried out within one step, which helps reducing computation efforts and communication overheads. (ii) In case of a later dispute, the recipient can convert the signature into an ordinary one for the public arbitration. (iii) The signature conversion can be solely performed by the recipient without additional computation efforts or communication overheads. (iv) The recipient of the signature can prove himself, if needed, to anyone that he is actually the designated recipient.

• Journal of Communications and Networks
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• v.14 no.4
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• pp.418-428
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• 2012

With the requirement for providing multiple levels of access control for group members, many group key management schemes designed for hierarchical access control have been put forward. However, most of these schemes focus on the efficiency of group key establishment and rekeying in centralized environments. This paper proposes an integrated group key agreement (IGK) scheme for contributory environments. The IGK scheme employs the integrated key graph to remove key redundancies existing in single key trees, and reduces key establishment and rekeying time while providing hierarchical access control. Performance analyses and simulations conducted with respect to computation and communication overheads indicate that our proposed IGK scheme is more efficient than the independent group key agreement scheme.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.962-970
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• 2000

Multithreading is attractive in that it can tolerate memory latency and synchronization by effectively overlapping communication with computation. While several compiler techniques have been developed to produce multithreaded codes from functional languages programs, there still remains a lot of works to implement loops effectively. Executing lops in a style of multithreading usually causes some overheads, which can reduce severely the effect of multirheading. This paper suggests several methods in terms of architectures or compilers which can optimize loop execution by multithreading. We then simulate and analyze them for the matrix multiplication program.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.5
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• pp.351-359
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• 2009

Recently with increase of data in the Internet, platform technologies that can process huge data effectively such as Google platform and Hadoop are regarded as worthy of notice. In this kind of platform, there exist network I/O overheads to send task outputs due to the MapReduce operation which is a programming model to support parallel computation in the large cluster system. In this paper, we suggest applying of TIPC (Transparent Inter-Process Communication) protocol for reducing network I/O overheads and increasing network performance in the distributed computing environments. TIPC has a lightweight protocol stack and it spends relatively less CPU time than TCP because of its simple connection establishment and logical addressing. In this paper, we analyze main features of the Hadoop-based distributed computing system, and we build an experimental model which can be used for experiments to compare the performance of various protocols. In the experimental result, TIPC has a higher bandwidth and lower CPU overheads than other protocols.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.3
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• pp.63-73
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• 2004

This paper proposes an efficient authentication scheme for multicast packet using recovery layer to provide source authentication. The problems of the existing schemes are as follows ： TESLA requires time synchronization between the sender and the receiver, md hash-based schemes have high communication overheads due to additional hash values and require many buffers and delay for verification on receivers. Our main focus is reducing the buffer size, communication and computation burden of the receiver. The proposed scheme in this paper is highly robust to packet loss using the recovery layer based on XOR operation. It also provides low communication overhead, low verification cost, non-repudiation of the origin, immediate verification and robustness against DoS attack on the receiver.

• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.373-380
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• 2007

In this paper we propose a new efficient authentication protocol that reduces overheads of computation for digital signature generation/verification on mobile devices in the Personal Area Network (PAN). In particular, we focus on eliminating the traditional public key operations on mobile devices without any assistance of a signature server. Moreover, the proposed protocol provides a simplified procedure for certificate status management to alleviate communication and computational costs on mobile devices in the PAN.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4345-4363
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• 2021

Deep Learning as a Service (DLaaS), utilizing the cloud-based deep neural network models to provide customer prediction services, has been widely deployed on mobile cloud computing (MCC). Such services raise privacy concerns since customers need to send private data to untrusted service providers. In this paper, we devote ourselves to building an efficient protocol to classify users' images using the convolutional neural network (CNN) model trained and held by the server, while keeping both parties' data secure. Most previous solutions commonly employ homomorphic encryption schemes based on Ring Learning with Errors (RLWE) hardness or two-party secure computation protocols to achieve it. However, they have limitations on large communication overheads and costs in MCC. To address this issue, we present LeHE4SCNN, a scalable privacy-preserving and communication-efficient framework for CNN-based DLaaS. Firstly, we design a novel low-expansion rate homomorphic encryption scheme with packing and unpacking methods (LeHE). It supports fast homomorphic operations such as vector-matrix multiplication and addition. Then we propose a secure prediction framework for CNN. It employs the LeHE scheme to compute linear layers while exploiting the data shuffling technique to perform non-linear operations. Finally, we implement and evaluate LeHE4SCNN with various CNN models on a real-world dataset. Experimental results demonstrate the effectiveness and superiority of the LeHE4SCNN framework in terms of response time, usage cost, and communication overhead compared to the state-of-the-art methods in the mobile cloud computing environment.