• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.5
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• pp.1117-1127
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• 2017

With the advent of Internet of Things (IoT), the number of devices connected to Internet has rapidly increased, but the security for IoT is still vulnerable. It is difficult to integrate existing security technologies due to generating a large amount of traffic by using different protocols to use various IoT devices according to purposes and to operate in a low power environment. Therefore, in this paper, we propose a normal network behavior profiling method based on big data analysis techniques. The proposed method utilizes a Hadoop/Hive for Big Data analytics and an R for statistical computing. Also we verify the effectiveness of the proposed method through a simulation.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.658-673
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• 2021

Data deduplication technology improves data storage efficiency while storing and managing large amounts of data. It reduces storage requirements by determining whether replicated data is being added to storage and omitting these uploads. Data deduplication technologies require data confidentiality and integrity when applied to cloud storage environments, and they require a variety of security measures, such as encryption. However, because the source data cannot be transformed, common encryption techniques generally cannot be applied at the same time as data deduplication. Various studies have been conducted to solve this problem. This white paper describes the basic environment for data deduplication technology. It also analyzes and compares multiple proposed technologies to address security threats.

• Korean Security Journal
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• no.8
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• pp.197-218
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• 2004

This study has been conducted to provide data that contribute to increasing efficiency of 'Private Security', which is cooperated by customer, security companies and the police which carried out 'Public Law Enforcement' and controls security companies. To reach this purpose, we investigated the status of the 'Security Alarm Systems' operated by security service companied in Korea, analyzed arising problems, considered the polices for improving the operational quality. 'Electronic Security Systems' will increase working efficiency in performing 'Private Security'. There can be no two opinions on this matter. Therefore, it can be supposed that the improvement of operational quality of 'Electronic Security System' is an important factor to accomplish security services. 'Security Alarm System' is one of the 'Electronic Security System'. The critical problems in operating 'Security Alarm system' are unnecessary response by false alarm and nuisance alarm. To reduce the problems, it is suggested that security specialist officially licensed should improve security planning, installation and maintenance, and the 'Alarm Verification System' should be introduced with appropriate facilities.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1399-1410
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• 2015

Gartner is requiring companies to considerably change their survival paradigms insisting that companies need to understand and provide again the upcoming era of data competition. With the revealing of successful business cases through statistic algorithm-based predictive analytics, also, the conversion into preemptive countermeasure through predictive analysis from follow-up action through data analysis in the past is becoming a necessity of leading enterprises. This trend is influencing security analysis and log analysis and in reality, the cases regarding the application of the big data analysis framework to large-scale log analysis and intelligent and long-term security analysis are being reported file by file. But all the functions and techniques required for a big data log analysis system cannot be accommodated in a Hadoop-based big data platform, so independent platform-based big data log analysis products are still being provided to the market. This paper aims to suggest a framework, which is equipped with a real-time and non-real-time predictive analysis engine for these independent big data log analysis systems and can cope with cyber attack preemptively.

• Convergence Security Journal
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• v.12 no.2
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• pp.61-70
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• 2012

The objective of this study is to achieve the most optimal data mining for effective analysis of false alarm event on mechanical security system. To perform this, this study searches the cause of false alarm and suggests the data conversion and analysis methods to apply to several algorithm of WEKA, which is a data mining program, based on statistical data for the number of case on movement by false alarm, false alarm rate and cause of false alarm. Analysis methods are used to estimate false alarm and set more effective reaction for false alarm by applying several algorithm. To use the suitable data for effective analysis of false alarm event on mechanical security analysis this study uses Decision Tree, Naive Bayes, BayesNet Apriori and J48Tree algorithm, and applies the algorithm by deducting the highest value.

• The Journal of Society for e-Business Studies
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• v.6 no.3
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• pp.101-113
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• 2001

Security is very important in EC(Electronic Commerce) environment because exchanged information(that is transaction details, private data, charges data(card-no, accounts), etc) is various and is very sensitive. So, In this paper, we propose Secure-ReXpis(Reliable St excellent Xh3 Processing Infrastructure) System that transfer message and support Message Level Security(Encryption/Decryption and Digital Signature). And we implement Message Confidentiality Service, User Authentication ＆ Message Integrity Service and Non-Repudiation Service among the various Security Services. This system support XML message format and EDI message, WEB Data and Private Format Data, etc.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.215-217
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• 2016

With the popularity of smart device, mobile applications are playing more and more important role in people's daily life, these applications stores various information which greatly facilitate the user's daily life. However due to the frequent transmission of data in the network also increases the risk of data leakage, more and more developers began to focus on how to protect user data. Current mainstream development models include Native development, Web development and Hybrid development. Hybrid development is based on JavaScript and HTML5, it has a cross platform advantages similar to Web Apps and a good user experience similar to Native Apps. In this paper according to the features of Hybrid applications, we proposed a security scheme in Hybrid development model implements message-level data encryption to protect user information. And through the performance evaluation we found that in some scenario the proposed security scheme has a better performance.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.435-441
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• 2013

This paper review about kerberos security authentication scheme and policy for big data service. It analyzed problem for security technology based on Hadoop framework in big data service environment. Also when it consider applying problem of kerberos security authentication system, it analyzed deployment policy in center of main contents, which is occurred in commercial business. About the related applied Kerberos policy in US, it is researched about application such as cross platform interoperability support, automated Kerberos set up, integration issue, OPT authentication, SSO, ID, and so on.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.358-368
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• 2022

Social media is a window for everyone, individuals, communities, and companies to spread ideas and promote trends and products. With these opportunities, challenges and problems related to security, privacy and rights arose. Also, the data accumulated from social media has become a fertile source for many analytics, inference, and experimentation with new technologies in the field of data science. In this chapter, emphasis will be given to methods of trend analysis, especially ensemble learning methods. Ensemble learning methods embrace the concept of cooperation between different learning methods rather than competition between them. Therefore, in this chapter, we will discuss the most important trends in ensemble learning and their applications in analysing social media data and anticipating the most important future trends.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.120-144
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• 2023

With the expansion of digital communication networks, a considerable number of randomization techniques have been invented and implemented to enhance the different data transmission algorithms' levels of security. Steganography is among the data transmissions techniques used to hide secret data. Nowadays, several randomization techniques have been used in steganography to elevate the security of transmitted data. Unfortunately, the majority of these techniques lack some simplicity, efficiency, and flexibility, in addition to other limitations. This research presents a new randomization technique called Rand-Stego. Rand-Stego could be applied/practiced over any steganography technique. It provides simplicity and efficiency and elevates the security level. Examples of implementing the proposed technique on some steganography algorithms will be explored. The proposed and current techniques will be compared. The obtained results show Rand-Stego's superiority in terms of efficiency and flexibility when compared to the current techniques.