• Journal of Internet Computing and Services
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• v.12 no.4
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• pp.157-172
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• 2011

The latest active studies on distributed OLAP to adopt a distributed environment are mainly focused on DHT P2P OLAP and Grid OLAP. However, these approaches have its weak points, the P2P OLAP has limitations to multidimensional range queries in the cloud computing environment due to the nature of structured P2P. On the other hand, the Grid OLAP has no regard for adjacency and time series. It focused on its own sub set lookup algorithm. To overcome the above limits, this paper proposes an efficient central managed P2P approach for a cloud computing environment. When a multi-level hybrid P2P method is combined with an index load distribution scheme, the performance of a multi-dimensional range query is enhanced. The proposed scheme makes the OLAP query results of a user to be able to reused by other users' volatile cube search. For this purpose, this paper examines the combination of an aggregation cube hierarchy tree, a quad-tree, and an interval-tree as an efficient index structure. As a result, the proposed cloud P2P OLAP scheme can manage the adjacency and time series factor of an OLAP query. The performance of the proposed scheme is analyzed by a series of experiments to identify its various characteristics.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.12
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• pp.287-296
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• 2019

Due to the development and increased usage of Internet services such as IoT and cloud computing, a large number of packets are being generated on the Internet. In order to create a safe Internet environment, malicious data that may exist among these packets must be processed and detected quickly. In this paper, we apply MongoDB, which is specialized for unstructured data analysis and big data processing, to intrusion detection system for rapid processing of big data security events. In addition, building the intrusion detection system(IDS) using some of the private cloud resources which is the target of protection, elastic and dynamic reconfiguration of the IDS is made possible as the number of security events increase or decrease. In order to evaluate the performance of MongoDB - based IDS proposed in this paper, we constructed prototype systems of IDS based on MongoDB as well as existing relational database, and compared their performance. Moreover, the number of virtual machine has been increased to find out the performance change as the IDS is distributed. As a result, it is shown that the performance is improved as the number of virtual machine is increased to make IDS distributed in MongoDB environment but keeping the overall system performance unchanged. The security event input rate based on distributed MongoDB was faster as much as 60%, and distributed MongoDB-based intrusion detection rate was faster up to 100% comparing to the IDS based on relational database.

• Annual Conference of KIPS
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• 2016.10a
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• pp.47-49
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• 2016

최근 SNS(social networking service)의 사용이 급증함에 따라 SNS에서 발생하는 데이터의 분석이 활발해졌다. 하지만 SNS 데이터는 빠르게 생성되며 정형화 되어 있지 않은 빅데이터이기 때문에 그대로 수집할 경우 분석하기가 어렵다. 본 논문은 분산 스트리밍 처리 기술인 Storm을 사용하여 트위터에서 실시간으로 발생하는 데이터를 수집 및 집계하고, 태그 클라우드를 사용하여 집계 결과를 동적으로 시각화하고자 한다. 또한 사용자가 쉽게 키워드를 입력하고 시각화 결과를 실시간으로 확인할 수 있도록 웹 인터페이스를 구현한다. 그리고 결과를 통해 태그 클라우드의 결과가 시간에 따라 바르게 시각화되었는지 확인한다. 본 논문은 빠르게 발생하는 SNS 데이터로부터 각 키워드와 관련된 정보를 시각화하여 각 사용자에게 제공할 수 있는 우수한 결과가 사료된다.

• Annual Conference of KIPS
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• 2012.11a
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• pp.164-167
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• 2012

합의는 분산 시스템 환경에서 해결해야 할 근본적인 문제 중 하나이다. 특히 노드 또는 프로세스의 임의적인 실패 즉, 비잔틴 실패가 발생하였을 때 합의 문제는 더 복잡해진다. 본 연구에서는 동적인 노드의 가입과 탈퇴가 자유로운 클라우드 환경에서 비잔틴 합의 문제를 해결하기 위한 가쉽 알고리즘을 제안한다. 제안하는 알고리즘에서 확장성과 결함 포용의 특성을 내재한 가쉽 알고리즘을 적용함으로써 클라우드 환경에서의 비잔틴 합의 문제를 확장적이고 결함 포용적으로 해결할 수 있다. 알고리즘의 성능을 분석하기 위해 성능 평가를 수행하였다.

• Annual Conference of KIPS
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• 2009.11a
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• pp.695-696
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• 2009

최근 증가하고 있는 클라우드 컴퓨팅 환경에서는 동일한 하드웨어 플랫폼에서 운용되는 다수의 가상머신들이 악성코드에 감염되어 분산서비스거부 공격을 위한 좀비로 악용될 위험이 있다. 그러나, 기존의 가상머신에 대한 보안 기술은 악성코드 감염에 대해 능동적으로 대응하지 못하는 한계가 있다. 이에 따라 본 논문에서는 Xen 하이퍼바이저를 기반으로 구축된 클라우드 컴퓨팅 환경에서 다수의 가상머신이 악성코드에 감염되는 것을 차단하기 위한 보안 시스템의 설계 방법을 제안한다.

• Journal of Digital Contents Society
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• v.14 no.4
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• pp.505-511
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• 2013

Recently, cloud computing is being emerged paradigm that a support computing resource flexible and scalable to users as the want in distributed computing environment. Actually, cloud computing can be implemented and provided by virtualization technology. In this paper, we studied open source based cloud computing and built a educational practice system through cloud computing. Virtualization-based cloud computing provides optimized computing resources, as well as easy to manage practical resource and result. Therefore, we can save the time for configuration of practice environment. In the view of faculty, they can easily handle the practice result. Also, those practice condition reuse comfortably and apply to various configuration simply. And then we can increase capabilities and availabilities of limited resources.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.1-9
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• 2017

Innovations from current researches on cloud computing such as applying bio-inspired computing techniques have brought new level solutions in offloading mechanisms. With the growing trend of mobile devices, mobile cloud computing can also benefit from applying bio-inspired techniques. Energy-efficient offloading mechanisms on mobile cloud systems are needed to reduce the total energy consumption but previous works did not consider energy consumption in the decision-making of task distribution. This paper proposes the Particle Swarm Optimization (PSO) as an offloading strategy of cloudlet to data centers where each task is represented as a particle during the process. The collected tasks are classified using K-means clustering on the cloudlet before applying PSO in order to minimize the number of particles and to locate the best data center for a specific task, instead of considering all tasks during the PSO process. Simulation results show that the proposed PSO excels in choosing data centers with respect to energy consumption, while it has accumulated a little more processing time compared to the other approaches.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.5
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• pp.737-751
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• 2023

The importance of digital forensics in the cloud environment is increasing as businesses and individuals move their data from On-premise to the cloud. Cloud data can be stored on various devices, including mobile devices and desktops, and encompasses a variety of user behavior artifacts, such as information generated from linked accounts and cloud services. However, there are limitations in securing and analyzing digital evidence due to environmental constraints of the cloud, such as distributed storage of data and lack of artifact linkage. One solution to address this is archiving services, and Google's Takeout is prime example. In this paper, user behavior data is analyzed for cloud forensics based on archiving data and necessary items are selected from an investigation perspective. Additionally, we propose the process of analyzing selectively collected data based on time information and utilizing web-based visualization to meaningfully assess artifact associations and multi-behaviors. Through this, we aim to demonstrate the value of utilizing archiving data in response to the increasing significance of evidence collection for cloud data.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.2
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• pp.41-56
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• 2019

Cloud manufacturing is a new concept of manufacturing process that works like a single factory with connected multiple factories. The cloud manufacturing system is a kind of large-scale CPS that produces products through the collaboration of distributed manufacturing facilities based on technologies such as cloud computing, IoT, and virtualization. It utilizes diverse and distributed facilities based on centralized information systems, which allows flexible composition user-centric and service-oriented large-scale systems. However, the cloud manufacturing system is composed of a large number of highly heterogeneous subsystems. It has difficulties in interconnection, data exchange, information processing, and system verification for system construction. In this paper, we derive the user requirements of various aspects of the cloud manufacturing system, such as functional, human, trustworthiness, timing, data and composition, based on the CPS Framework, which is the analysis methodology for CPS. Next, by analyzing the user requirements we define the system requirements including scalability, composability, interactivity, dependability, timing, interoperability and intelligence. We map the defined CPS system requirements to the requirements of oneM2M, which is the platform standard for IoT, so that the support of the system requirements at the level of the IoT platform is verified through Mobius, which is the implementation of oneM2M standard. Analyzing the verification result, finally, we propose a large-scale cloud manufacturing platform based on oneM2M that can meet the cloud manufacturing requirements to support the overall features of the Cloud Manufacturing CPS with dependability.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.841-849
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• 2012

Cloud computing that provides IT service and computer resource based on internet is now getting attention. However, the encrypted data can be exposed because it is saved in cloud server, even though it is saved as an encrypted data. In this paper, user certification protocol is proposed to prevent from illegally using of secret data by others while user who locates different physical position is providing secret data safely. The proposed protocol uses one way hash function and XOR calculation to get user's certification information which is in server when any user approaches to particular server remotely. Also it solves user security problem of cloud.