• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.907-913
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• 2022

Approximately 70% of smartphone users around the world use Android operating system-based smartphones, and malicious apps targeting these Android platforms are constantly increasing. Google has provided "Google Play Protect" to respond to the increasing number of Android targeted malware, preventing malicious apps from being installed on smartphones, but many malicious apps are still normal. It threatens the smartphones of ordinary users registered in the Google Play store by disguising themselves as apps. However, most people rely on antivirus programs to detect malicious apps because the average user needs a great deal of expertise to check for malicious apps. Therefore, in this paper, we propose a method to classify unnecessary malicious permissions of apps by using only the categories and permissions that can be easily confirmed by the app, and to easily detect malicious apps through the classified permissions. The proposed method is compared and analyzed from the viewpoint of undiscovered rate and false positives with the "commercial malicious application detection program", and the performance level is presented.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1181-1191
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• 2021

The pandemic has rapidly developed a non-face-to-face environment. However, the sudden transition to a non-face-to-face environment has led to new security issues in various areas. One of the new security issues is the security threat of insiders, and the zero trust security model is drawing attention again as a technology to defend against it.. Software Defined Perimeter (SDP) technology consists of various security factors, of which device validation is a technology that can realize zerotrust by monitoring insider usage behavior. But the current SDP specification does not provide a technology that can perform device validation.. Therefore, this paper proposes a device validation technology using SVDD-based abnormal behavior detection technology through user behavior monitoring in an SDP environment and presents a way to perform the device validation technology in the SDP environment by conducting performance evaluation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.4
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• pp.673-689
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• 2022

We propose an APT attack scoring method as a part of the process for detecting and responding to APT attacks. First, unlike previous work that considered inconsistent and subjective factors determined by cyber security experts in the process of scoring cyber attacks, we identify quantifiable factors from components of MITRE ATT&CK^Ⓡ techniques and propose a method of quantifying each identified factor. Then, we propose a method of calculating the score of the unit attack technique from the quantified factors, and the score of the entire APT attack composed of one or more multiple attack techniques. We present the possibility of quantification to determine the threat level and urgency of cyber attacks by applying the proposed scoring method to the APT attack reports, which contains the hundreds of APT attack cases occurred worldwide. Using our work, it will be possible to determine whether actual cyber attacks have occurred in the process of detecting APT attacks, and respond to more urgent and important cyber attacks by estimating the priority of APT attacks.

• Convergence Security Journal
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• v.22 no.2
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• pp.9-19
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• 2022

As the expansion of digital transformation, we are more exposed to the threat of cyber attacks, and many institution or company is operating a signature-based intrusion prevention system at the forefront of the network to prevent the inflow of attacks. However, in order to provide appropriate services to the related ICT system, strict blocking rules cannot be applied, causing many false events and lowering operational efficiency. Therefore, many research projects using artificial intelligence are being performed to improve attack detection accuracy. Most researches were performed using a specific research data set which cannot be seen in real network, so it was impossible to use in the actual system. In this paper, we propose a technique for classifying major attack keywords in the security event log collected from the actual system, assigning a weight to each key keyword, and then performing a similarity check using TF-IDF to determine whether an actual attack has occurred.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1373-1387
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• 2021

Forest fire poses a significant threat to the environment and society, affecting carbon cycle and surface energy balance, and resulting in socioeconomic losses. Widely used multi-spectral satellite image-based approaches for burned area detection have a problem in that they do not work under cloudy conditions. Therefore, in this study, Sentinel-1 Synthetic Aperture Radar (SAR) data from Europe Space Agency, which can be collected in all weather conditions, were used to identify forest fire damaged area based on a series of processes including Principal Component Analysis (PCA) and K-means clustering. Four forest fire cases, which occurred in Gangneung·Donghae and Goseong·Sokcho in Gangwon-do of South Korea and two areas in North Korea on April 4, 2019, were examined. The estimated burned areas were evaluated using fire reference data provided by the National Institute of Forest Science (NIFOS) for two forest fire cases in South Korea, and differenced normalized burn ratio (dNBR) for all four cases. The average accuracy using the NIFOS reference data was 86% for the Gangneung·Donghae and Goseong·Sokcho fires. Evaluation using dNBR showed an average accuracy of 84% for all four forest fire cases. It was also confirmed that the stronger the burned intensity, the higher detection the accuracy, and vice versa. Given the advantage of SAR remote sensing, the proposed statistical processing and K-means clustering-based approach can be used to quickly identify forest fire damaged area across the Korean Peninsula, where a cloud cover rate is high and small-scale forest fires frequently occur.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.531-540
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• 2021

As cyber attacks and crimes increase exponentially and hacking attacks become more intelligent and advanced, hacking attack methods and routes are evolving unpredictably and in real time. In order to reinforce the enemy's responsiveness, this study aims to propose a method for developing an artificial intelligence-based security control platform by building a next-generation security system using artificial intelligence to respond by self-learning, monitoring abnormal signs and blocking attacks.The artificial intelligence-based security control platform should be developed as the basis for data collection, data analysis, next-generation security system operation, and security system management. Big data base and control system, data collection step through external threat information, data analysis step of pre-processing and formalizing the collected data to perform positive/false detection and abnormal behavior analysis through deep learning-based algorithm, and analyzed data Through the operation of a security system of prevention, control, response, analysis, and organic circulation structure, the next generation security system to increase the scope and speed of handling new threats and to reinforce the identification of normal and abnormal behaviors, and management of the security threat response system, Harmful IP management, detection policy management, security business legal system management. Through this, we are trying to find a way to comprehensively analyze vast amounts of data and to respond preemptively in a short time.

• Convergence Security Journal
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• v.20 no.4
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• pp.27-34
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• 2020

Recently, the fourth industrial revolution technology has not only changed everyday life greatly through technological development, but has also become a major keyword in the establishment of defense policy. In particular, Internet of Things, cloud, big data, mobile and cybersecurity technologies, called ICBMS, were selected as core leading technologies in defense information policy along with artificial intelligence. Amid the growing importance of the fourth industrial revolution technology, research is being carried out to develop the C4I system, which is currently operated separately by the Joint Chiefs of Staff and each military, including the KJCCS, ATCIS, KNCCS and AFCCS, into an integrated system in preparation for future warfare. This is to solve the problem of reduced interoperability for joint operations, such as information exchange, by operating the C4I system for each domain. In addition, systems such as the establishment of an integrated C4I system and the U.S. military's Risk Management Framework (RMF) are essential for efficient control and safe operation of weapons systems as they are being developed into super-connected and super-intelligent systems. Therefore, in this paper, the intelligent cyber threat detection, management of users' access to information, and intelligent management and visualization of cyber threat are presented in the future C4I system based on big data/cloud.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.67-70
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• 2013

스마트폰 보급은 현대인들에게 시간적, 공간적 제약에서 벗어나 언제 어디서나 무선 인터넷을 사용하여 모바일 뱅킹, 결재, 증권거래 등 원하는 서비스를 이용할 수 있게 해주었다. 사용자들은 이를 이용하여 다양한 정보들을 검색, 저장, 이용한다. 그러나 무선 인터넷의 순기능과는 반대로 최근 모바일 기기의 보안취약점을 이용한 악성애플리케이션 및 각종 공격으로 사용자 개인정보탈취의 위협이 증가하고 있다. 사회공학공격의 일종인 피싱(Phishing)은 신뢰받는 기관을 사칭하여 만들어놓은 가짜사이트에 사용자로부터 자신의 개인정보 및 금융정보를 입력하게끔 유도하여 사용자정보를 탈취하는 방법으로 최근 SMS를 이용하여 정부 및 금융기관을 사칭한 문자를 보내 피싱사이트로 접속을 유도하는 피해사례가 증가하고 있다. 본 논문에서는 국내 피싱사이트의 유형을 분석하고 피싱사이트로 접근을 유도하는 방법 중 하나인 SMS를 이용한 피싱을 방지 할 수 있는 시스템을 고안한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.4
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• pp.406-411
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• 2010

A honeynet is a closely monitored computing resource that we want to be probed, attacked or compromised. More precisely, a honeypot is "an information system resource whose value lies in unauthorized or illicit use of that resource The value of honeynet is weighed by the information that can be obtained from it. but It's very difficult to deploy Honeynet in Real World, So I focused on Virtual Honeynet. The strength of virtual honeynet is scalability and ease of maintenance. It is inexpensive to deploy and accessible to almost everyone. Compared with physical honeypots, this approach is more lightweight. Instead of deploying a physical computer system that acts as a honeypot, we can also deploy one physical computer that hosts several virtual machines that act as honeypots.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.837-840
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• 2017

각종 사이버 범죄가 증가함에 따라 실시간 모니터링을 통한 사전 탐지 기술뿐만 아니라, 사후 원인 분석을 통한 사고 재발 방지 기술의 중요성이 증가하고 있다. 사후 분석은 시스템에서 생산된 다양한 유형의 대용량 로그를 기반으로 분석가가 보안 위협 과정을 규명하는 것으로 이를 지원하는 다양한 상용 및 오픈 소스 SW 존재하나, 대부분 단일 분석가 PC에서 운용되는 파일 기반 SW로 대용량 데이터에 대한 분석 성능 저하, 다수 분석가 간의 데이터 공유 불가, 통계 연관 분석 한계 및 대화형 점진적 내용 분석 불가 등의 문제점을 해결하지 못하고 있다. 이러한 문제점을 해결하기 위하여 고성능 인메모리 관계형 데이터베이스 시스템을 로그 스토리지로 활용하는 대용량 로그 분석 SW 개발하였다. 특히, 기 확보된 공격자 프로파일을 활용하여 공격의 유무를 확인하는 텍스트 패턴 매칭 연산은 전통적인 관계형 데이터베이스 시스템의 FTS(Full-Text Search) 기능 활용이 가능하나, 대용량 전용 색인 생성에 따른 비현실적인 DB 구축 소요 시간과 최소 3배 이상의 DB 용량 증가로 인한 시스템 리소스 추가 요구 등의 단점이 있다. 본 논문에서는 인메모리 관계형 데이터베이스 시스템 기반 효율적인 텍스트 패턴 매칭 연산을 위하여, 고성능의 대용량 로그 DB 적재 방법과 새로운 유형의 패턴 매칭 방법을 제안하였다.