• 반도체디스플레이기술학회지
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• 제20권2호
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• pp.121-125
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• 2021

Cloud service has the characteristic that it must be always available and that it must be able to respond immediately to user requests. This study suggests a method for constructing a proactive and autonomous quality and performance management system to meet these characteristics of cloud services. To this end, we identify quantitative measurement factors for cloud service quality and performance management, define a structure for applying a time series framework to cloud service application quality and performance management for proactive management, and then use big data and artificial intelligence for autonomous management. The flow of data processing and the configuration and flow of big data and artificial intelligence platforms were defined to combine intelligent technologies. In addition, the effectiveness was confirmed by applying it to the cloud service quality and performance management system through a case study. Using the methodology presented in this study, it is possible to improve the service management system that has been managed artificially and retrospectively through various convergence. However, since it requires the collection, processing, and processing of various types of data, it also has limitations in that data standardization must be prioritized in each technology and industry.

• Journal of Computing Science and Engineering
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• 제10권1호
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• pp.21-31
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• 2016

With the application and development of biomedical techniques such as next-generation sequencing, mass spectrometry, and medical imaging, the amount of biomedical data have been growing explosively. In terms of processing such data, we face the problems surrounding big data, highly intensive computation, and high dimensionality data. Fortunately, cloud computing represents significant advantages of resource allocation, data storage, computation, and sharing and offers a solution to solve big data problems of biomedical research. In order to improve the efficiency of resource management in cloud computing, this paper proposes a clustering method and adopts Radial Basis Function in order to compress comprehensive data sets found in biology and medicine in high quality, and stores these data with resource management in cloud computing. Experiments have validated that with such a data-compression-based resource management in cloud computing, one can store large data sets from biology and medicine in fewer capacities. Furthermore, with reverse operation of the Radial Basis Function, these compressed data can be reconstructed with high accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권11호
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• pp.3182-3203
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• 2023

With the growing adoption of cloud-based technologies, maintaining the privacy and security of cloud data has become a pressing issue. Privacy-preserving encryption schemes are a promising approach for achieving cloud data security, but they require careful design and implementation to be effective. The integrated approach to cloud data security that we suggest in this work uses CogniGate: the orchestrated permissions protocol, index trees, blockchain key management, and unique Opacus encryption. Opacus encryption is a novel homomorphic encryption scheme that enables computation on encrypted data, making it a powerful tool for cloud data security. CogniGate Protocol enables more flexibility and control over access to cloud data by allowing for fine-grained limitations on access depending on user parameters. Index trees provide an efficient data structure for storing and retrieving encrypted data, while blockchain key management ensures the secure and decentralized storage of encryption keys. Performance evaluation focuses on key aspects, including computation cost for the data owner, computation cost for data sharers, the average time cost of index construction, query consumption for data providers, and time cost in key generation. The results highlight that the integrated approach safeguards cloud data while preserving privacy, maintaining usability, and demonstrating high performance. In addition, we explore the role of differential privacy in our integrated approach, showing how it can be used to further enhance privacy protection without compromising performance. We also discuss the key management challenges associated with our approach and propose a novel blockchain-based key management system that leverages smart contracts and consensus mechanisms to ensure the secure and decentralized storage of encryption keys.

• International journal of advanced smart convergence
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• 제5권4호
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• pp.26-31
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• 2016

In a cloud computing environment, a cryptographic service allows an information owner to encrypt the information and send it to a cloud server as well as to receive and decode encrypted data from the server which guarantees the confidentiality of shared information. However, if an attacker gains a coded data and has access to an encryption key via cloud server, then the server will be unable to prevent data leaks by a cloud service provider. In this paper, we proposed a key management server which does not allow an attacker to access to a coded key of the owners and prevents data leaks by a cloud service provider. A key management server provides a service where a server receives a coded public key of an information user from an owner and delivers a coded key to a user. Using a key management server proposed in this paper, we validated that the server can secure the confidentiality of an encryption key of data owners and efficiently distribute keys to data users.

• 반도체디스플레이기술학회지
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• 제21권2호
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• pp.133-137
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• 2022

In the smart industry where data plays an important role, cloud computing is being used in a complex and advanced way as a convergence technology because it has and fits well with its strengths. Accordingly, in order to utilize artificial intelligence rather than human beings for quality management of cloud computing services, a consistent standardization method of data collected from various nodes in various areas is required. Therefore, this study analyzed technologies and cases for incorporating artificial intelligence into specific services through previous studies, suggested a plan to use artificial intelligence to comprehensively standardize data in quality management of cloud computing services, and then verified it through case studies. It can also be applied to the artificial intelligence learning model that analyzes the risks arising from the data formalization method presented in this study and predicts the quality risks that are likely to occur. However, there is also a limitation that separate policy development for service quality management needs to be supplemented.

• 디지털융복합연구
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• 제11권12호
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• pp.467-477
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• 2013

클라우드 컴퓨팅 서비스가 대중적으로 보급됨에 따라 공공분야에서 해당 서비스의 도입에 대한 관심이 증가하고 있다. 이에 따라 국내에서는 클라우드 컴퓨팅을 공공분야에 도입하거나 계획하고 있으며 점차 구체적으로 구축하고 있다. 하지만 공공분야에서의 클라우드 도입 및 활성화를 위해서는 서비스 가용성 장애요인 및 인증 받지 않은 사용자의 무단 접근, 불분명한 출처로부터 다운로드 받은 데이터로 인한 클라우드 데이터센터의 신뢰성 저하 등의 보안 위협에 대한 해결방안을 모색할 필요성이 있다. 따라서 본 논문에서는 공공기관 클라우드 데이터센터에서 활용 가능한 공개키 기반의 안전한 데이터 관리 기법에 대해서 제안한다. 이를 통해 공공기관에 클라우드 컴퓨팅을 도입할 때 인증 받은 사용자만 데이터센터를 사용할 수 있고, 공공 데이터의 중요도와 난이도를 공용데이터, 개인데이터, 기밀데이터로 설정해주어 체계적이고 안전하며 효율적으로 데이터 관리를 가능하게 한다. 따라서 공공기관에서의 클라우드 서비스에 대해 전반적인 보안성과 편의성을 향상시킬 수 있을 것으로 기대된다.

• Journal of Information Processing Systems
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• 제15권5호
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• pp.1192-1200
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• 2019

Recently, artificial intelligence techniques have been widely used in the computer science field, such as the Internet of Things, big data, cloud computing, and mobile computing. In particular, resource management is of utmost importance for maintaining the quality of services, service-level agreements, and the availability of the system. In this paper, we review and analyze various ways to meet the requirements of cloud resource management based on artificial intelligence. We divide cloud resource management techniques based on artificial intelligence into three categories: fog computing systems, edge-cloud systems, and intelligent cloud computing systems. The aim of the paper is to propose an intelligent resource management scheme that manages mobile resources by monitoring devices' statuses and predicting their future stability based on one of the artificial intelligence techniques. We explore how our proposed resource management scheme can be extended to various cloud-based systems.

• 대한임베디드공학회논문지
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• 제8권6호
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• pp.303-309
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• 2013

Cloud storage services are used for efficient sharing or synchronizing of user's data across multiple mobile devices. Although cloud storages provide flexibility and scalability in storing data, security issues should be handled. Currently, typical cloud storage services offer data encryption for security purpose but we think such method is not secure enough because managing encryption keys by software and identifying users by simple ID and password are main defectives of current cloud storage services. We propose a secure data access method to cloud storage in mobile environment. Our framework supports hardware-based key management, attestation on the client software integrity, and secure key sharing across the multiple devices. We implemented our prototype using ARM TrustZone and TPM Emulator which is running on secure world of the TrustZone environment.

• 반도체디스플레이기술학회지
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• 제20권4호
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• pp.83-88
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• 2021

Cloud services have become the core infrastructure of the digital economy as a basis for collecting, storing, and processing large amounts of data to trigger artificial intelligence-based services and industrial innovation. Recently, cloud services have been spotlighted as a means of responding to corporate crises and changes in the work environment in a national disaster caused by COVID-19. While the cloud is attracting attention, the speed of adoption and diffusion of cloud services is not being actively carried out due to the lack of trust among users and uncertainty about security, performance, and cost. This study compares and analyzes the "Cloud Service Quality and Performance Management System" and the "Cloud Service Certification System" and suggests complementary points and improvement measures for the cloud service quality and performance management system.

• 디지털산업정보학회논문지
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• 제8권4호
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• pp.107-113
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• 2012

Cloud computing has brought changes to the IT environment. Due to the spread of LTE, users of cloud services are growing more. This which provides IT resources to meet the needs of users of cloud services are noted as a core industry. But it is not activated because of the security of personal data and the safety of the service. In order to solve this, intrusion detection system is constructed as follows. This protects individual data safely which exists in the cloud and also protects information exhaustively from malicious attack. The cause of most attack risk which exists to cloud computing can find in distributed environment. In this study, we analyzed about necessary property of network-based intrusion detection system that process and analyze large amount of data which occur in cloud computing environment. Also, we studied functions which detect and correspond attack occurred in interior of virtualization.