• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.205-213
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• 2024

As the Restaurant industry is growing rapidly. The demand for an effortless POS (Point Of Sale) system which can make management easy is increasing. So, the purpose of this study is to digitalise the growing industry of restaurants and its consumers by utilizing cross-platform development. Crossplatform development frameworks provide great opportunities to solve the issues of handling ubiquitous devices with minimum efforts to reduce the cost and increase the stability, accessibility of the end consumers. By availing those opportunities, an Integrated POS system with cross platform is proposed. This integrated cross-platform POS system is originally designed for a single restaurant managed by its own private cloud server. This research solves the 2 major problems. One of them is the accessibility of the system on modern devices without even writing platform-specific code with the help of cross-platform development. This included web, mobile, desktops & tablets at the same time with the same codebase. Second one is handling data consistency with ubiquitous devices with the help of cloud infrastructure to make data safe and consistent more than ever. In the Development of this system Dart will be used as the primary programming language for cross-platform development. On the Cloud server system apache will be used as the web server and PHP as server side language. System will be using MySQL as the database server.

• Journal of KIISE
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• v.43 no.10
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• pp.1165-1172
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• 2016

In cloud storage environment, deduplication enables efficient use of the storage. Also, in order to save network bandwidth, cloud storage service provider has introduced client-side deduplication. Cloud storage service users want to upload encrypted data to ensure confidentiality. However, common encryption method cannot be combined with deduplication, because each user uses a different private key. Also, client-side deduplication can be vulnerable to security threats because file tag replaces the entire file. Recently, proof of ownership schemes have suggested to remedy the vulnerabilities of client-side deduplication. Nevertheless, client-side deduplication over encrypted data still causes problems in efficiency and security. In this paper, we propose a secure and practical client-side encrypted data deduplication scheme that has resilience to brute force attack and performs proof of ownership over encrypted data.

• Convergence Security Journal
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• v.15 no.5
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• pp.3-8
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• 2015

Most mobile cloud computing system use public key cryptography to provide data security and mutual authentication. A variant of traditional public key technologies called Identity-Based Cryptography(IBC) has recently received considerable attention. The certificate-free approach of IBC may well match the dynamic qualities of cloud environment. But, there is a need for a lightweight secure framework that provides security with minimum processing overhead on mobile devices. In this paper, we propose to use hierarchical ID-Based Encryption in mobile cloud computing. It is suitable for a mobile network since it can reduce the workload of root Public Key Generators by delegating the privilege of user authentication and private key generation. The Identity-Based Encryption and Identity-Based Signature are also proposed and an ID-Based Authentication scheme is presented to secure data processing. The proposed scheme is designed by one-way hash functions and XOR operations, thus has low computation costs for mobile users.

• Journal of Convergence for Information Technology
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• v.8 no.3
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• pp.63-69
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• 2018

Recently, healthcare services are using cloud services to efficiently manage users' healthcare data. However, research to ensure the stability of the user's healthcare data processed in the cloud environment is insufficient. In this paper, we propose a partial random encryption scheme that efficiently encrypts healthcare data in a cloud environment. The proposed scheme generates two random keys (p, q) generated by the user to optimize for the hospital medical service and reflects them in public key and private key generation. The random key used in the proposed scheme improves the efficiency of user 's healthcare data processing by encrypting only part of the data without encrypting the whole data. As a result of the performance evaluation, the proposed method showed 21.6% lower than the existing method and 18.5% improved the user healthcare data processing time in the hospital.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.18 no.7
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• pp.11-21
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• 2013

Recently operating a large scale computing resource like a data center becomes easier because of the virtualization technology that virtualize servers and enable flexible resource provision. The most of public cloud services provides automatic scaling in the form of scale-in or scale-out and these scaling approaches works well to satisfy the service level agreement (SLA) of users. However, a novel scaling approach is required to operate private clouds that has smaller amount of computing resources than vast resources of public clouds. In this paper, we propose a hybrid server scaling architecture and related algorithms using both scale-in and scale-out to achieve higher resource utilization rate for private clouds. We uses dynamic resource allocation and live migration to run our proposed algorithm. Our propose system aims to provide a fine-grain resource scaling by steps. Thus private cloud systems are able to keep stable service and to reduce server management cost by optimizing server utilization. The experiment results show that our proposed approach performs better in resource utilization than the scale-out approach based on the number of users.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.679-680
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• 2021

본 논문에서는 개인용 하드웨어를 통해 인증을 강화하고 이를 활용하여 개인 클라우드를 제공할 수 있는 개인용 보안장비인 DONO를 제안한다. 또한 DONO를 활용하여 보다 규모가 확장된 클라우드 서비스를 제안하고 이를 활용하여 실제 서비스가 가능함을 보여주도록 한다. DONO가 사용하는 환경은 기존의 네트워크 시스템을 따르는 대신 콘텐츠 중심의 통신을 통해 면역 기반 보안 시스템을 구축한다. 데이터 전송은 CCN(Content Centric Network)을 통해 이루어지며 CCNx 그룹이 검증한 프로토콜을 활용한다. DONO에 의해 보호되는 영역은 일반적인 네트워크 통신을 사용하지 않고 CCN 프로토콜에 따라서 운영하며 이를 통해 기존의 보안 공격과 추가적으로 알 수 없는 공격으로부터 시스템을 보호할 수 있다. 이러한 새로운 방식을 활용해 클라우드 시스템을 제공하며 보다 안전한 서비스를 활용할 수 있음을 보이도록 한다.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.325-340
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• 2022

Amid the unprecedented situation of COVID-19 around the world, online education has established itself as an essential element in the era of zero contact and the importance of various content and changes of the system that are appropriate for the era of the 4^th industrial revolution has increased. Although universities are making their efforts to combine ICT technologies and design and achieve new systems, the recognition and atmosphere for establishing the cloud computing system are falling short. The purpose of this research importance of success factors of "Building a cloud computing system of cyber university in Korea" by classifying the work characteristics and scale, and to derive and analyze the importance cloud rankings considering the organization and individual dimension. Therefore, this study has drawn 14 major factors in the previous researches and models through the survey on experts with knowledge related to the cloud computing. The analysis was conducted to see what differences there are in factors for the successful establishment of the cloud computing system using AHP. It is expected that the factors for success presented through this study would be used as systemic strategies and tools for the purpose of drawing factors for the success of establishing the private cloud computing system for the higher education institutions and public information systems.

• The Transactions of the Korea Information Processing Society
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• v.13 no.7
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• pp.291-298
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• 2024

Despite its wide application, cloud computing raises privacy leakage concerns because users should send their private data to the cloud. Homomorphic encryption (HE) can resolve the concerns by allowing cloud servers to compute on encrypted data without decryption. However, due to the huge computation overhead of HE, simply executing an entire cloud program with HE causes significant computation. Manually partitioning the program and applying HE only to the partitioned program for the cloud can reduce the computation overhead. However, the manual code partitioning and HE-transformation are time-consuming and error-prone. This work proposes a new homomorphic encryption enabled annotation-guided code partitioning compiler, called Heapa, for privacy preserving cloud computing. Heapa allows programmers to annotate a program about the code region for cloud computing. Then, Heapa analyzes the annotated program, makes a partition plan with a variable list that requires communication and encryption, and generates a homomorphic encryptionenabled partitioned programs. Moreover, Heapa provides not only two region-level partitioning annotations, but also two instruction-level annotations, thus enabling a fine-grained partitioning and achieving better performance. For six machine learning and deep learning applications, Heapa achieves a 3.61 times geomean performance speedup compared to the non-partitioned cloud computing scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.3068-3085
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• 2021

The economics of big data knowledge, especially cloud computing and statistical data of consumer preferences, has attracted increasing academic and industry practitioners' attention. Firms nowadays require purchasing not only external private patent knowledge from other firms, but also proprietary big data knowledge to support their new product development. Extant research investigates pricing strategies of external private patent knowledge and proprietary big data knowledge separately. Yet, a comprehensive investigation of pricing strategies of these two types of knowledge is in pressing need. This research constructs an overarching pricing model of external private patent knowledge and proprietary big data knowledge through the lens of firm profitability as a knowledge transaction recipient. The proposed model can help those firms who purchase external knowledge choose the optimal knowledge structure and pricing strategies of two types of knowledge, and provide theoretical and methodological guidance for knowledge transaction recipient firms to negotiate with knowledge providers.