• Journal of KIISE
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• v.45 no.3
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• pp.294-302
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• 2018

With the emergence of the new service industry due to the development of information and communication technology, cyber space risks such as personal information infringement and industrial confidentiality leakage have diversified, and the security problem has emerged as a critical issue. In this paper, we propose a behavior-based anomaly detection method that is suitable for real-time and large-volume data analysis technology. We show that the proposed detection method is superior to existing signature security countermeasures that are based on large-capacity user log data according to in-company personal information abuse and internal information leakage. As the proposed behavior-based anomaly detection method requires a technique for processing large amounts of data, a real-time search engine is used, called Elasticsearch, which is based on an inverted index. In addition, statistical based frequency analysis and preprocessing were performed for data analysis, and the DBSCAN algorithm, which is a density based clustering method, was applied to classify abnormal data with an example for easy analysis through visualization. Unlike the existing anomaly detection system, the proposed behavior-based anomaly detection technique is promising as it enables anomaly detection analysis without the need to set the threshold value separately, and was proposed from a statistical perspective.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.3
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• pp.493-500
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• 2015

Personal information exposed in the Internet is increasing by the public data opening and sharing, vitalization of SNS(Social Network Service) and growth of information shared between users. Exposed personal information in the Internet can infringe upon targeted users using linkage attack or background attack. To prevent these attack De-identification models were appeared a few years ago. The 'k-anonymity' has been introduced in the first place, and the '${\ell}$-diversity' and 't-closeness' have been followed up as solutions, and diverse algorithms have been being suggested for performance improvement nowadays. However, industry or public sectors actually needs a whole solution as a system for the de-identification process rather than performance of the de-identification algorithm. This paper explains a way of de-identification techique for 'k-anonymity', '${\ell}$-diversity', and 't-closeness' algorithm using QI(Quasi-Identifier) grouping method in the relational database.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.1983-1988
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• 2006

There are gradually built on electronic commerce and business information system for the effective and automated use of internet while the mainstream of industry moves on information. It is necessary that a company should develop a electronic approval system because the business documents have application to an electronic commerce, business information system as well Currently, electronic approval system on groupware is using the way of inserting the image of an approval signature, which is vulnerable on a security by attacks of fraudulent use of electrical signature and eavesdropping on electronic documents. In this paper, we implementation XML form generator based on DTD having business documents structure for creating a valid business XML documents. we designed electronic approval system based on secured XML which transfers encrypted documents. For the security issues of written XML business documents, it makes use of the crypto algorithm having high performance transaction by the interchange of public key between a server and a client.

• Convergence Security Journal
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• v.23 no.3
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• pp.57-64
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• 2023

Due to the COVID-19 pandemic, the broadcasting industry has been greatly affected, to the extent that the footprint of travel programs has disappeared. Although travel programs have been back on the air since 2022, there remains a task of recovering the stagnant desire for travel. Based on a study that travel programs have a positive impact on viewers' travel intentions, this study examined a data service that provides preferred additional information on travel programs, considering the broadcasting environment of satellite broadcasters that transmit multiple travel programs through various channels. Specifically, preferred additional information was investigated for travel programs of various genres and formats, and a feature model based on FODA was designed to be used when the satellite broadcaster decides the data service configuration. In addition, the necessary information for operating the data service was defined based on the feature model, and a method of transmitting it using the DVB-S SI, a domestic satellite broadcasting standard, was devised. The feasibility of this study was also confirmed using a DVB-MHP based data service prototype.

• The Journal of Information Systems
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• v.26 no.2
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• pp.123-142
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• 2017

Purpose The development of the Fintech industry can be on the basis of the development in IT technologies such as Big data, IoT, cloud computing, it can be considered that the financial industry is repeating the evolution into Fintech. But the awareness of the consumers is still very low. Therefore the current dissertation, tries to deduce the suggestions for invigoration measures for Fintech by conducting an empirical study on the factors that influence the intention of reuse of Fintech on the consumer's point of view. Design/methodology/approach This study made a design of the research model by integrating the factors deducted from the Expectation Confirmation Theory. This paper empirically analyzes the impact of Continuous Usage Intention for Improvement of Fintech. The 302 survey responses were used to verify research hypotheses through covariate structural equation model. Findings According to the empirical analysis result, this study confirmed that the ultimate purpose of the Fintech service is to eliminate the social cost's waste element occurring from issue of money by not using or reducing the usage of cash. Since many Fintech users have pointed out security as the priority task, a direction for the related institutions has been proposed. Second, the content of the current dissertation will be the opportunity of broadening the perception of the current consumers that perceive Fintech as only a NFC simple payment service.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.4
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• pp.613-620
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• 2017

The power grid has been changed to a smart grid system to satisfy the growing need for power grid complexity, demand, reliability, security, and efficiency with a combination of existing power and ICT technology. This study analyzes the research trends in smart grid technology in the period since the introduction of the smart grid system and compares it with industrial trends to grasp the progress and characteristics of Smart Grid technology and look for ways to innovate the technology. To do this, we analyze the research trends using dynamic topic modeling, which is capable of time-series research topic analysis. Next, we compare the results of research trends with industrial trends analyzed by Gartner's experts to demonstrate that smart grid research is evolving to the level of industrialization. The results of this study are quantitative analysis through data mining, and it is expected that it will be used in many fields such as companies that want to participate in industry and government agencies that need to establish policies by showing more objective analysis results.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.89-95
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• 2016

Recent growth of hacking threats and development in software and technology put Network security under threat, In addition, intrusion, malware and worm virus have been increased due to the existence of variety of sophisticated hacking methods. The goal of this study is to compare Snort Alpha version with Suricata 2.0.11 version whereas previous study focuses on comparison between snort 2. x version under thread environment and Suricata under multi-threading environment. This thesis' experiment environment is set as followed. Intel (R) Core (TM) i5-4690 3. 50GHz (4threads) of CPU, 16GB of RAM, 3TB of Seagate HDD, Ubuntu 14.04 are used. According to the result, Snort Alpha version is superior to Suricata in performance, but Snort Alpha had some glitches when executing pcap files which created core dump errors. Therefore this experiment seeks to analyze which performs better between Snort Alpha version that supports multi packet processing threads and Suricata that supports multi-threading. Through this experiment, one can expect the better performance of beta and formal version of Snort in the future.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.2
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• pp.41-49
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• 2016

Lossless encryption methods are more applicable than lossy encryption methods when marginal distortion is not tolerable. In this research, the author propose a novel lossless symmetric key encryption/decryption technique. In the proposed algorithm, the image is transformed into the frequency domain using the lifting wavelet transform, then the image sub-bands are encrypted in a such way that guarantees a secure, reliable, and an unbreakable form. The encryption involves scattering the distinguishable frequency data in the image using a reversible weighting factor amongst the rest of the frequencies. The algorithm is designed to shuffle and reverse the sign of each frequency in the transformed image before the image frequencies are transformed back to the pixel domain. The results show a total deviation in pixel values between the original and encrypted image. The decryption algorithm reverses the encryption process and restores the image to its original form. The proposed algorithm is evaluated using standard security and statistical methods; results show that the proposed work is resistant to most known attacks and more secure than other algorithms in the cryptography domain.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.21-29
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• 2012

Mobile voting can reduce the costs spent in elections, and it can encourage people to participate in the elections more actively because it allows them to vote anytime at anywhere. The trial of mobile voting in 2012 by Democratic United Party in Korea, showed the possibilities of mobile democracy but it also showed very critical problems such as illegal voting by proxy, source code open, open to nationwide for local parliamentary candidate ballot, privacy and hacking. In this paper, we analyze the result of the mobile ballot trial, and introduce the problems that has been revealed. After that we propose some system requirements for the new mobile voting system to prevent the problems according to the stages of voting: system development, voting stage, and counting and validating stage. At each stage, there are several requirements to be met for reliable mobile voting. Our research contribute to mobile democracy and implementation of mobile voting systems in that we analyzed the real case and raised issues for the real problems.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.31-40
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• 2012

Face recognition refers to the process of identifying individuals based on their facial features. It has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous consumer applications, such as access control, surveillance, security, credit-card verification, and criminal identification. However, illumination variation on face generally cause performance degradation of face recognition systems under practical environments. Thus, this paper proposes an novel face recognition system using a fusion approach based on local binary pattern and two-dimensional principal component analysis. To minimize illumination effects, the face image undergoes the local binary pattern operation, and the resultant image are divided into two sub-images. Then, two-dimensional principal component analysis algorithm is separately applied to each sub-images. The individual scores obtained from two sub-images are integrated using a weighted-summation rule, and the fused-score is utilized to classify the unknown user. The performance evaluation of the proposed system was performed using the Yale B database and CMU-PIE database, and the proposed method shows the better recognition results in comparison with existing face recognition techniques.