• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.6
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• pp.333-340
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• 2014

Despite the security weakness of reusing passwords, many Internet users are likely to use a single ID and password on various sites to avoid the inconvenience of remembering multiple credentials. This paper proposes a scheme for securely storing, retrieving, and updating randomly chosen (ID, password) pairs by using smart cards as secure and portable storages. The scheme makes a user free from remembering her (ID, password) pairs for Internet accesses. By splitting and scattering the (ID, password) pairs of a user across the user's smart card memory and a remote server's storage, it can protect the logon credentials even from the theft or loss of the smart card. Also, a user, if deemed necessary, can issue and let the server to delete all information belonging to the user. Hence even an attacker who cracked the smart card memory would not be able to obtain any (ID, password) pair of the victim thereafter. The scheme requires a user to input a site information and pass-phrase to her smart card to obtain the logon credentials, but it should be an acceptable overhead considering the benefits of not remembering the freely chosen (ID, password) pairs at all.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.617-627
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• 2016

Many kinds of OGC-based web standards have been utilized in the lots of geo-spatial application fields for sharing and interoperable processing of large volume of data sets containing satellite images. As well, the number of cloud-based application services by on-demand processing of virtual machines is increasing. However, remote sensing applications using these two huge trends are globally on the initial stage. This study presents a practical linkage case with both aspects of OGC-based standard and cloud computing. Performance test is performed with the implementation result for cloud detection processing. Test objects are WPS 2.0 and two types of geo-based service environment such as web server in a single core and multiple virtual servers implemented on OpenStack cloud computing environment. Performance test unit by JMeter is five requests of GetCapabilities, DescribeProcess, Execute, GetStatus, GetResult in WPS 2.0. As the results, the performance measurement time in a cloud-based environment is faster than that of single server. It is expected that expansion of processing algorithms by WPS 2.0 and virtual processing is possible to target-oriented applications in the practical level.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.209-228
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• 2011

Web search behavior has evolved. People now search using many diverse information devices in various situations. To monitor these scattered and shifting search patterns, an improved way of learning and analysis are needed. Traditional web search studies relied on the server transaction logs and single query instance analysis. Since people use multiple smart devices and their searching occurs intermittently through a day, a bundled query research could look at the whole context as well as penetrating search needs. To observe and analyze bundled queries, we developed a proprietary research software set including a log catcher, query bundling tool, and bundle monitoring tool. In this system, users' daily search logs are sent to our analytic server, every night the users need to log on our bundling tool to package his/her queries, a built in web survey collects additional data, and our researcher performs deep interviews on a weekly basis. Out of 90 participants in the study, it was found that a normal user generates on average 4.75 query bundles a day, and each bundle contains 2.75 queries. Query bundles were categorized by; Query refinement vs. Topic refinement and 9 different sub-categories.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.1
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• pp.97-104
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• 2016

Because of rapid growth of data size, the number of data storage has been increased. When using multiple data storages, a distribute file system is essential to insure the availability of data files. The power consumption is a major problem when using a distributed file system with many data storages. Previous works have aimed at reducing the energy consumption with efficient file block layout by changing some data servers into stand-by mode. The file block migration has not been seriously considered because migration causes large cost. But when we consider addition of a new data server or file, file block migration is needed. This paper formulates the minimization of data block migration as an ILP optimization problem and solves it using branch-and-bound method. Using this technique, we can maximize the number of stand-by data servers with the minimum number of file block movement. However, computation time of branch-and-bound method of an ILP optimization problem increases exponentially as the problem size grows. Therefore this paper also proposes a data block and data server grouping method to solve many small ILP problems.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.514-520
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• 2018

Presence service provides various information about users such as locations, status of on/offline and network access methods, and number of presence resources required by each users increases largely in mobile environment. Therefore an effective method which can reduce load of presence servers is needed. In this paper, a large scale distributed presence service system which can distribute effectively total presence system load of presence servers using message control session has been presented. This large scale distributed presence service system provides various presence information for massive volumes of users. In this study, a new message control session architecture which can dynamically distribute loads of the presence servers to multiple servers has been presented, and a new presence information data architecture for controlling load of the presence servers has been designed. In this architecture, each presence server can exchange current load level in real time to get variance of the total system load change according to user numbers, and can distribute system load to maintain load level of each server evenly. The performance of the proposed large scale distributed presence service system has been analysed by experiments. The results has been showed that average presence resource subscription processing time reduced from 42.6% to 73.6%, and average presence notification processing time reduced from 37.6% to 64.8%.

• The Journal of Engineering Research
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• v.4 no.1
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• pp.5-22
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• 2002

With the rapid advance of internet service and the corresponding migration of service environment from the text-based one to WWW (World Wide Web) environment, the number of internet users is growing rapidly due to its easy usage. Accordingly, usage of internet as services for sending electronic mails to the other party over the network is becoming increasingly prevalent. Web-based electronic mailing system is comprised of a server and a client. The former provides the users with e-mail accounts and services, while the latter serves as a user interface. In other words, it enables those public users who dos not own e-mail accounts on the existing mail server to have an access to the mailing service through the web. In this paper, we designed a effective web-based electronic mailing system which is based on the internet explorer and linux operating system, which overcomes limitations of the existing e-mail systems and meets the need of a cost-efficient alternative. Our electronic mailing system also supports the convenience of users through appropriate handling of preregistered spam e-mails and multiple e-mails, and this facilitates the development of a stable e-mail system by being able to avoiding the low system performance due to the bursty characteristics of e-mail messages and the increasing number of users

• Journal of Digital Convergence
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• v.19 no.4
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• pp.151-157
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• 2021

Recently, IoT technology has been applied to various cloud environments, requiring accurate verification of various information generated by IoT devices. However, due to the convergence of IoT technologies and 5G technologies, accurate analysis is required as IoT information processing is rapidly processed. This paper proposes a blockchain-based multi-IoT verification model for overlay cloud environments. The proposed model multi-processes IoT information by further classifying IoT information two layers (layer and layer) into bits' blockchain to minimize the bottleneck of overlay networks while ensuring the integrity of information sent and received from embedded IoT devices within local IoT groups. Furthermore, the proposed model allows the layer to contain the weight information, allowing IoT information to be easily processed by the server. In particular, transmission and reception information between IoT devices facilitates server access by distributing IoT information from bits into blockchain to minimize bottlenecks in overlay networks and then weighting IoT information.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.305-316
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• 2022

With the flood of digital data owing to the Internet of Things and big data, cloud service providers that process and store vast amount of data from multiple users can apply duplicate data elimination technique for efficient data management. The user experience can be improved as the notion of edge computing paradigm is introduced as an extension of the cloud computing to improve problems such as network congestion to a central cloud server and reduced computational efficiency. However, the addition of a new edge device that is not entirely reliable in the edge computing may cause increase in the computational complexity for additional cryptographic operations to preserve data privacy in duplicate identification and elimination process. In this paper, we propose an efficiency-improved duplicate data elimination protocol while preserving data privacy with an optimized user-edge-cloud communication framework by utilizing a trusted execution environment. Direct sharing of secret information between the user and the central cloud server can minimize the computational complexity in edge devices and enables the use of efficient encryption algorithms at the side of cloud service providers. Users also improve the user experience by offloading data to edge devices, enabling duplicate elimination and independent activity. Through experiments, efficiency of the proposed scheme has been analyzed such as up to 78x improvements in computation during data outsourcing process compared to the previous study which does not exploit trusted execution environment in edge computing architecture.

• The Journal of Bigdata
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• v.9 no.1
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• pp.101-113
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• 2024

Federated learning has garnered attention as an efficient method for training machine learning models in a distributed environment while maintaining data privacy and security. This study proposes a novel FedRFBagging algorithm to optimize the performance of random forest models in such federated learning environments. By dynamically adjusting the trees of local random forest models based on client-specific data characteristics, the proposed approach reduces communication costs and achieves high prediction accuracy even in environments with numerous clients. This method adapts to various data conditions, significantly enhancing model stability and training speed. While random forest models consist of multiple decision trees, transmitting all trees to the server in a federated learning environment results in exponentially increasing communication overhead, making their use impractical. Additionally, differences in data distribution among clients can lead to quality imbalances in the trees. To address this, the FedRFBagging algorithm selects only the highest-performing trees from each client for transmission to the server, which then reselects trees based on impurity values to construct the optimal global model. This reduces communication overhead and maintains high prediction performance across diverse data distributions. Although the global model reflects data from various clients, the data characteristics of each client may differ. To compensate for this, clients further train additional trees on the global model to perform local optimizations tailored to their data. This improves the overall model's prediction accuracy and adapts to changing data distributions. Our study demonstrates that the FedRFBagging algorithm effectively addresses the communication cost and performance issues associated with random forest models in federated learning environments, suggesting its applicability in such settings.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.4
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• pp.775-783
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• 2017

As interest in cloud computing grows, the number of users using cloud computing services is increasing. However, cloud computing technology has been steadily challenged by security concerns. Therefore, various security breaches are springing up to enhance the system security for cloud services users. In particular, research on detection of malicious VM (Virtual Machine) is actively underway through the introspecting virtual machines on the cloud platform. However, memory analysis technology is not used as a monitoring tool in the environments where multiple virtual machines are run on a single server platform due to obstructive monitoring overhead. As a remedy to the challenging issue, we proposes a computationally efficient instance memory introspection scheme to minimize the overhead that occurs in memory dump and monitor it through a partial memory monitoring based on the well-defined kernel memory map library.