• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.233-239
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• 2022

Recently, research is being conducted on the rapid service provision and reliability of the instance-based rather than the existing IP-based structure. Research is mainly conducted through Block cloud, a platform that combines service-centric networking (SCN) and blockchain. In addition, the Internet of Things network has been proposed as a fog computing environment in the structure of the existing cloud computing. Fog computing is an environment suitable for real-time information processing. In this paper, we propose a new Internet network structure based on fog computing that requires real-time for rapid processing of IoT services. The proposed system applies IoTA, the third-generation blockchain based on DAG, to the block cloud. In addition, we want to propose a basic model of the object block chain and check the application services of electric vehicles.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.2
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• pp.11-17
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• 2018

IDS/IPS and networked computer systems are playing an increasingly important role in our society. They have been the targets of a malicious attacks that actually turn into intrusions. That is why computer security has become an important concern for network administrators. Recently, various Detection/Prevention System schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems is useful for existing intrusion patterns on standard-only systems. Therefore, probe detection of private clouds using BlockChain has become a major security protection technology to detection potential attacks. In addition, BlockChain and Probe detection need to take into account the relationship between the various factors. We should develop a new probe detection technology that uses BlockChain to fine new pattern detection probes in cloud service security in the end. In this paper, we propose a probe detection using Fuzzy Cognitive Map(FCM) and Self Adaptive Module(SAM) based on service security using BlockChain technology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.204-226
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• 2018

Big data processing applications have been migrated into cloud gradually, due to the advantages of cloud computing. Hadoop Distributed File System (HDFS) is one of the fundamental support systems for big data processing on MapReduce-like frameworks, such as Hadoop and Spark. Since HDFS is not aware of the co-location of virtual machines in the cloud, the default scheme of block allocation in HDFS does not fit well in the cloud environments behaving in two aspects: data reliability loss and performance degradation. In this paper, we present a novel location-aware data block allocation strategy (LDBAS). LDBAS jointly optimizes data reliability and performance for upper-layer applications by allocating data blocks according to the locations and different processing capacities of virtual nodes in the cloud. We apply LDBAS to two stages of data allocation of HDFS in the cloud (the initial data allocation and data recovery), and design the corresponding algorithms. Finally, we implement LDBAS into an actual Hadoop cluster and evaluate the performance with the benchmark suite BigDataBench. The experimental results show that LDBAS can guarantee the designed data reliability while reducing the job execution time of the I/O-intensive applications in Hadoop by 8.9% on average and up to 11.2% compared with the original Hadoop in the cloud.

• Smart Media Journal
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• v.7 no.4
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• pp.9-16
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• 2018

In order to improve the economics and flexibility of cloud computing, tendency to automate the operation and management of cloud resources has become complicated. However, while automation for cloud storage depends on the manufacturer's storage hardware, it cannot flexibly support the storage type in accordance with users' needs. In this paper, we propose an automatic configuration module that supports block/file/object storages suitable for user environment. In order to automatically install ceph, a cloud storage, we propose an automatic installation and configuration module based on the Chef configuration management tool. In addition to that, we also propose an automatic configuration module based on a shell programming in pursuit of enabling users to use ceph storage of block/file/object. The proposed method can automatically set up and manage shared file, block, and object storages in a virtual or physical user environment with no hardware dependencies.

• Journal of the Korea Society of Computer and Information
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• v.25 no.11
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• pp.139-146
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• 2020

Cloud computing technology provides economic and efficient system operation and management features to deal with rapidly changing IT technologies. However, this is less used in institutes and companies due to low security of cloud computing service. It is recognized that storing and managing important information, which is confidential in external systems is vulnerable to security threats. In order to enhance security of this cloud computing service, this paper suggests a system and user authentication reinforcement model. The suggested technology guarantees integrity of user authentication information and provides users with convenience by creating blocks for each cloud service and connecting service blocks with chains. The block chain user authentication model offers integrity assurance technology of block chains and system access convenience for SSO users. Even when a server providing cloud computing is invaded, this prevents chained invasions not to affect other systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5234-5251
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• 2018

It is well-known that virtualization technology can bring many benefits not only to users but also to service providers. From the view of system security and resource utility, higher resource sharing degree and higher system reliability can be obtained by the introduction of virtualization technology in distributed cloud. The small size time-sharing multiplexing technology which is based on virtual machine in distributed cloud platform can enhance the resource utilization effectively by server consolidation. In this paper, the concept of memory block and user satisfaction is redefined combined with user requirements. According to the unbalanced memory resource states and user preference requirements in multi-virtual machine environments, a model of proper memory resource allocation is proposed combined with memory block and user satisfaction, and at the same time a memory optimization allocation algorithm is proposed which is based on virtual memory block, makespan and user satisfaction under the premise of an orderly physical nodes states also. In the algorithm, a memory optimal problem can be transformed into a resource workload balance problem. All the virtual machine tasks are simulated in Cloudsim platform. And the experimental results show that the problem of virtual machine memory resource allocation can be solved flexibly and efficiently.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4136-4156
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• 2020

Recently, data can be safely shared or stored using the infrastructure of cloud computing in various fields. However, issues such as data security and privacy affect cloud environments. Thus, a variety of security technologies are required, one of them is security technology using CP-ABE. Research into the CP-ABE scheme is currently ongoing, but the existing CP-ABE schemes can pose security threats and are inefficient. In terms of security, the CP-ABE approach should be secure against user collusion attacks and masquerade attacks. In addition, in a dynamic cloud environment where users are frequently added or removed, they must eliminate user access when they leave, and so users will not be able to access the cloud after removal. A user who has left should not be able to access the cloud with the existing attributes, secret key that had been granted. In addition, the existing CP-ABE scheme increases the size of the ciphertext according to the number of attributes specified by the data owner. This leads to inefficient use of cloud storage space and increases the amount of operations carried out by the user, which becomes excessive when the number of attributes is large. In this paper, CP-ABE access control is proposed to block access of withdrawn users in dynamic cloud environments. This proposed scheme focuses on the revocation of the attributes of the withdrawn users and the output of a ciphertext of a constant-size, and improves the efficiency of the user decryption operation through outsourcing.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.11-19
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• 2014

In this paper, we propose a real-time video transcoding scheme for N-Screen service based on cloud computing. This scheme creates an intro-block and several playback blocks by splitting the original video. And there is the first service request, after transmitting the intro-block, transmits the playback blocks that converting the blocks on real-time. In order to completing trans-coding within playback time of each block, we split and allocate the block to node according to performance of each node. Also, in order to provide real-time video playback service, the previous scheme convert original video into all format and resolution. However we show that the proposed scheme can reduce storage usage by converting original video into format with proper resolution suitable to device and platform of client. Through simulation, we show that it is more effective to real-time video playback for N-screen service than the previous method. We also show that the proposed scheme uses less storage usage than previous method.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.49-56
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• 2010

In this paper, we implement a Hadoop based cluster for cloud computing and evaluate the performance of this cluster based on application characteristics by executing RandomTextWriter, WordCount, and PI applications. A RandomTextWriter creates given amount of random words and stores them in the HDFS(Hadoop Distributed File System). A WordCount reads an input file and determines the frequency of a given word per block unit. PI application induces PI value using the Monte Carlo law. During simulation, we investigate the effect of data block size and the number of replications on the execution time of applications. Through simulation, we have confirmed that the execution time of RandomTextWriter was proportional to the number of replications. However, the execution time of WordCount and PI were not affected by the number of replications. Moreover, the execution time of WordCount was optimum when the block size was 64~256MB. Therefore, these results show that the performance of cloud computing system can be enhanced by using a scheduling scheme that considers application's characteristics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4703-4723
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• 2016

The verification of data integrity is an urgent topic in remote data storage environments with the wide deployment of cloud data storage services. Many traditional verification algorithms focus on the block-oriented verification to resolve the dispute of dynamic data integrity between the data owners and the storage service providers. However, these algorithms scarcely pay attention to the data verification charge and the users' verification experience. The users more concern about the availability of accessed files rather than data blocks. Moreover, the data verification charge limits the number of checked data in each verification. Therefore, we propose a mixed verification protocol to verify the data integrity, which rapidly locates the corrupted files by the file-oriented verification, and then identifies the corrupted blocks in these files by the block-oriented verification. Theoretical analysis and simulation results demonstrate that the protocol reduces the cost of the metadata computation and transmission relative to the traditional block-oriented verification at the expense of little cost of additional file-oriented metadata computation and storage at the data owner. Both the opportunity of data extracted and the scope of suspicious data are optimized to improve the verification efficiency under the same verification cost.