• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.638-639
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• 2013

Anymon Plus(ver 3.0)은 통합 로그 분석 시스템으로 대용량 로그 및 빅데이터의 실시간 수집 저장 분석할 수 있는 제품(초당 40,000 이벤트 처리)으로서, 방화벽 로그 분석을 통한 비정상 네트워크 행위 탐지, 웹 로그 분석을 통한 사용 패턴 분석, 인터넷 쇼핑몰 사기 주문 분석 및 탐지, 내부 정부 유출 분석 및 탐지 등과 같은 다양한 분야로 응용이 확대되고 있다. 본 논문에서는 보안관련 인프라 로그를 분석하고 예측하여 예상 보안사고 시기에 집중적 경계를 통한 선제적 대응을 모색하기 위해 통계적 이론에 기반한 통합 로그 분석 시스템을 개발하기 위해, 회귀분석 및 시계열 분석이 가능한 예측 엔진 시스템을 설계하고 구현한다.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.137-152
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• 2018

It is a measure to overcome limitations that occur in the activity of detecting and blocking abnormal information leakage activity by collecting the activity log generated by the security solution to detect the leakage of existing financial information and analyzing it by pattern analysis. First, it monitors real-time execution programs in PC that are used as information leakage path (read from the outside, save to the outside, transfer to the outside, etc.) in the PC. Second, it determines whether it is a normal controlled exception control circumvention by interacting with the related security control process at the time the program is executed. Finally, we propose a risk management model that can control the risk of financial information leakage through the process procedure created on the basis of scenario.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.141-142
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• 2014

Recently, personal information issue has been increased. When personal information is taken, it is very important to prevent secondary damage. In this paper, I suggest new logging system using typing pattern that each user has different. So even if someone knows my password and tries to log in to my account, this system rejects it because the intruder has different typing pattern from mine. To justify my research, I develop algorithm extracting personal typing pattern and finding pattern to synchronize with the original user's pattern.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.275-278
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• 2013

Log is a file system, a system that uses all remaining data. Want situation now being issued in the IT, media Nate on information disclosure, the press agency server hack by numbness crime occurred. Hacking crisis that's going through this log analysis software professionally for professional analysis is needed. The present study, about APT attacks happening intelligently Log In case of more than traceback in advance to prevent the technology to analyze the pattern for log analysis techniques.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1311-1319
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• 2019

Currently, the web environment is a commonly used area for sharing information and conducting business. It is becoming an attack point for external hacking targeting on personal information leakage or system failure. Conventional signature-based detection is used in cyber threat but signature-based detection has a limitation that it is difficult to detect the pattern when it is changed like polymorphism. In particular, injection attack is known to the most critical security risks based on web vulnerabilities and various variants are possible at any time. In this paper, we propose a novelty detection technique to detect abnormal state that deviates from the normal state on web-server log dataset(WSLD). The proposed method is a machine learning-based technique to detect a minor anomalous data that tends to be different from a large number of normal data after replacing strings in web-server log dataset with vectors using machine learning-based embedding algorithm.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.845-853
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• 2022

As the memory capacity of smartphone increases, the type and amount of privacy stored in the smartphone is also increasing. but recently there is an increasing possibility that various personal information such as photos and videos of smartphones may be leaked due to malicious apps by malicious attackers or other people such as repair technicians. This paper analyzed and studied the security and vulnerability of these vault apps by analyzing the cryptography algorithm and data protection function. We analyzed 5.3.7(June 13, 2022) and 3.3.2(December 30, 2020) versions of AppLock, the most downloaded information-hidding apps registered with Google Play, and found various vulnerabilities. In the case of access control, there was a vulnerability in that values for encrypting patterns entered by users were hardcoded into plain text in the source code, and encrypted pattern values were stored in xml files. In addition, in the case of the vault function, there was a vulnerability in that the files and log files for storing in the vault were not encrypted.

• The KIPS Transactions:PartC
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• v.9C no.6
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• pp.831-840
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• 2002

Due to the advance of computer and communication technology, intrusions or crimes using a computer have been increased rapidly while tremendous information has been provided to users conveniently Specially, for the security of a database which stores important information such as the private information of a customer or the secret information of a company, several basic suity methods of a database management system itself or conventional misuse detection methods have been used. However, a problem caused by abusing the authority of an internal user such as the drain of secret information is more serious than the breakdown of a system by an external intruder. Therefore, in order to maintain the sorority of a database effectively, an anomaly defection technique is necessary. This paper proposes a method that generates the normal behavior profile of a user from the database log of the user based on an association mining method. For this purpose, the Information of a database log is structured by a semantically organized pattern tree. Consequently, an online transaction of a user is compared with the profile of the user, so that any anomaly can be effectively detected.

• Journal of Korea Game Society
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• v.16 no.2
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• pp.51-60
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• 2016

The incidents of massive personal information being leaked are occurring continuously over recent years. Personal information leaked outside is used for an illegal use of other's name and account theft. Especially it is happening on online games whose virtual goods, online game money and game items can be exchanged with real cash. When we research the real identity theft cases that happened in an online game, we can see that they happen massively in a short time. In this study, we define the characteristics of the mass attacks of the automated identity theft cases that occur in online games. Also we suggest a system to detect and prevent identity theft attacks in real time.