• Review of KIISC
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• v.25 no.1
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• pp.18-25
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• 2015

컴퓨터와 네트워크가 보안 상 안전하려면 무엇보다 사용되는 시스템 및 응용 프로그램에 보안약점이 없어야 한다. 보안약점은 공격자가 이용하여 제어 흐름을 탈취하거나 원하는 정보를 유출할 수 있게 하는 프로그램 상의 불완전한 부분을 뜻한다. 보안약점이 없는 프로그램을 만들기 위한 방법으로 시큐어 코딩 규칙을 정의하고, 프로그램 개발 단계에서 이를 적용하게 할 수 있다. 코딩 과정에서 시큐어 코딩 규칙을 준수하여 보안약점 발생을 억제하는 방법은 예방적 조치이다. 아무런 규칙 없이 코딩을 진행한 후 보안약점을 분석, 제거하는 방법보다 프로그래머들에게 부담이 적고, 정적 분석을 사용하여 보안약점을 분석하는 도구들의 치명적인 약점인 오탐 비율을 낮춘다. 이 글은 2014년까지 소프트웨어 개발 보안 센터를 중심으로 진행된 행정자치부의 C/C++, Java, PHP 프로그래밍 언어를 위한 시큐어 코딩 가이드에 대하여 설명한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.531-536
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• 2002

In this paper, we have applied Genetic Algorithms(GAs) to Intrusion Detection System(TDS), and then proposed and simulated the misuse detection model firstly. We have implemented with the KBD contest data, and tried to simulated in the same environment. In the experiment, the set of record is regarded as a chromosome, and GAs are used to produce the intrusion patterns. That is, the intrusion rules are generated. We have concentrated on the simulation and analysis of classification among the Data Mining techniques and then the intrusion patterns are produced. The generated rules are represented by intrusion data and classified between abnormal and normal users. The different rules are generated separately from three models "Time Based Traffic Model", "Host Based Traffic Model", and "Content Model". The proposed system has generated the update and adaptive rules automatically and continuously on the misuse detection method which is difficult to update the rule generation. The generated rules are experimented on 430M test data and almost 94.3% of detection rate is shown.3% of detection rate is shown.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.351-360
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• 2006

Proposed security system attacks it, and detect it, and a filter generation, a business to be prompt of interception filtering dates at attack information public information. inner IPS to attack detour setting and a traffic band security, different connection security system, and be attack packet interceptions and service and port interception setting. Exchange new security rule and packet filtering for switch type implementation through dynamic reset memory by real time, and deal with a packet. The attack detection about DDoS, SQL Stammer, Bug bear, Opeserv worm etc. of the 2.5 Gbs which was an attack of a hacker consisted in network performance experiment by real time. Packet by attacks of a hacker was cut off, and ensured the normal inside and external network resources besides the packets which were normal by the results of active renewal.

• Korean Journal of Child Education & Care
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• v.19 no.3
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• pp.171-182
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• 2019

Objective: The purpose of this study was to investigate the effects of empathy, aggression, and self-esteem on social preference and social impact in preschoolers. Methods: The participants were 307 five year olds who were recruited from day care centers and preschools located in Seoul and Gyeonggi province. Social preference and social impact was measured with peer nominations. Empathy and aggression were measured by teacher ratings. Moreover, self-esteem was asessed using self-reports. The data was analysed using Pearson correlation and hierarchial regression. Results: Findings indicate that social preference is associated with empathy, however, social impact was associated with physical as well as relational aggression. Conclusion/Implications: The findings suggest that the practice of physical and relational aggression may be related with peer status as early as preschool.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.5
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• pp.1169-1178
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• 2012

Recently, since the most software intensive systems are using internet environment for data exchange, the software security is being treated as a big issue. And, to minimize vulnerability of software system, security ensuring steps which are applying secure coding rules, are introduced in the software development process. But, since actual attacks are using a variety of software vulnerabilities, it is hard to analyze software weakness by monotonic analysis. In this paper, it is tried to against the complex attack on the variety of software vulnerability using the coupling which is one of the important characteristic of software. Furthermore, pre-analysis of the complex attack patterns using a combination of various attack methods, is carried out to predict possible attack patterns in the relationship between software modules. And the complex attack pattern analysis method is proposed based on this result.

• Convergence Security Journal
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• v.5 no.2
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• pp.1-8
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• 2005

Network event analysis gives useful information on the network status that helps protect attacks. It involves finding sets of frequently used packet information such as IP addresses and requires real-time processing by its nature. Apriori algorithm used for data mining can be applied to find frequent item sets, but is not suitable for analyzing network events on real-time due to the high usage of CPU and memory and thus low processing speed. This paper develops a network event audit module by applying association rules to network events using a new algorithm instead of Apriori algorithm. Test results show that the application of the new algorithm gives drastically low usage of both CPU and memory for network event analysis compared with existing Apriori algorithm.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.5
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• pp.1167-1177
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• 2019

In this paper, the improved security operation model based on the vulnerability database is studied. The proposed model consists of information protection equipment, vulnerability database, and a dashboard that visualizes and provides the results of interworking with detected logs. The evaluation of the model is analyzed by setting up a simulated attack scenario in a virtual infrastructure. In contrast to the traditional method, it is possible to respond quickly to threats of attacks specific to the security vulnerabilities that the asset has, and to find redundancy between detection rules with a secure agent, thereby creating an optimal detection rule.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.663-664
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• 2009

OWASP에서 발표한 2007년 웹 애플리케이션 취약점 중 하나인 XSS 공격이 사용자 브라우저에서 스크립트를 실행하게 함으로써 사용자의 세션을 가로채거나 웜을 업로드하여 악성코드를 삽입하는 공격이다[2]. 하지만 많은 XSS 방어 기법에서는 단순 스크립트 우회기법과 강제적인 스크립트 차단 방법을 채택하고 있다. 또한 강제적인 XSS 필터 적용으로 과탐지로 인한 정상적인 웹 페이지가 출력 되지 않는 사례가 나타나고 있다. 따라서 본 연구는 효율적인 정규식을 이용하여 XSS 공격 특징을 분석하여 특징점들을 추출하고 이 특징점들을 기반으로 특정한 규칙을 가진 문자열들을 모든 문자가 유효한지 확인할 수 있는 정규식 표현 방법을 이용하여 다양한 응용프로그램에 적용할 수 있는 기술을 연구하고자 한다. 또한 이를 기반으로 포털 사이트와 브라우저에서 제공하는 XSS 필터들과 비교하여 과탐지율 및 오탐지율 서로 비교하여 본 연구가 효율성 면에서 효과가 있는지 우위를 둘 것이며, 브라우저 벤더, 포털 사이트, 개인 PC 등 충분한 시험 평가와 수정을 통해서 응용할 수 있는 계기를 마련할 것이다

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.48-59
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• 2018

Recently, network technology has been used in various fields due to development of network technology. However, there has been an increase in the number of attacks targeting public institutions and companies by exploiting the evolving network technology. Meanwhile, the existing network intrusion detection system takes much time to process logs as the amount of network log increases. Therefore, in this paper, we propose a Spark-based network log analysis system that detects unstructured network attack pattern. by using Snort. The proposed system extracts and analyzes the elements required for network attack pattern detection from large amount of network log data. For the analysis, we propose a rule to detect network attack patterns for Port Scanning, Host Scanning, DDoS, and worm activity, and can detect real attack pattern well by applying it to real log data. Finally, we show from our performance evaluation that the proposed Spark-based log analysis system is more than two times better on log data processing performance than the Hadoop-based system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.459-466
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• 2011

In this paper, we proposed a data mining framework for the management of alerts in order to improve the performance of the intrusion detection systems. The proposed alert data mining framework performs alert correlation analysis by using mining tasks such as axis-based association rule, axis-based frequent episodes and order-based clustering. It also provides the capability of classify false alarms in order to reduce false alarms. We also analyzed the characteristics of the proposed system through the implementation and evaluation of the proposed system. The proposed alert data mining framework performs not only the alert correlation analysis but also the false alarm classification. The alert data mining framework can find out the unknown patterns of the alerts. It also can be applied to predict attacks in progress and to understand logical steps and strategies behind series of attacks using sequences of clusters and to classify false alerts from intrusion detection system. The final rules that were generated by alert data mining framework can be used to the real time response of the intrusion detection system.