• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.453-462
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• 2009

Studies on software plagiarism detection, prevention and judgement have become widespread due to the growing of interest and importance for the protection and authentication of software intellectual property. Many previous studies focused on comparing all pairs of submitted codes by using attribute counting, token pattern, program parse tree, and similarity measuring algorithm. It is important to provide a clear-cut model for distinguishing plagiarism and collaboration. This paper proposes a source code clustering algorithm using a probability model on extreme value distribution. First, we propose an asymmetric distance measure pdist($P_a$, $P_b$) to measure the similarity of $P_a$ and $P_b$ Then, we construct the Plagiarism Direction Graph (PDG) for a given program set using pdist($P_a$, $P_b$) as edge weights. And, we transform the PDG into a Gumbel Distance Graph (GDG) model, since we found that the pdist($P_a$, $P_b$) score distribution is similar to a well-known Gumbel distribution. Second, we newly define pseudo-plagiarism which is a sort of virtual plagiarism forced by a very strong functional requirement in the specification. We conducted experiments with 18 groups of programs (more than 700 source codes) collected from the ICPC (International Collegiate Programming Contest) and KOI (Korean Olympiad for Informatics) programming contests. The experiments showed that most plagiarized codes could be detected with high sensitivity and that our algorithm successfully separated real plagiarism from pseudo plagiarism.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.2
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• pp.357-367
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• 2018

As information technology of modern society develops, various malicious codes with the purpose of seizing or destroying important system information are developing together. Among them, ransomware is a typical malicious code that prevents access to user's resources. Although researches on detecting ransomware performing encryption have been conducted a lot in recent years, no additional methods have been proposed to recover damaged files after an attack. Also, because the similarity comparison technique was used without considering the repeated encryption, it is highly likely to be recognized as a normal behavior. Therefore, this paper implements a filter driver to control the file system and performs a similarity comparison method that is verified based on the analysis of the encryption pattern of the ransomware. We propose a system to detect the malicious process of the accessed process and recover the damaged file based on the cloud storage.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.751-753
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• 2005

지문을 5가지 클래스로 나누는 헨리시스템을 기반으로 신경망이나 SVM(Support Vector Machines) 등과 같은 다양한 패턴분류 기법들이 지문분류에 많이 사용되고 있다. 특히 최근에는 높은 분류 성능을 보이는 SVM 분류기의 결합을 이용한 연구가 활발히 진행되고 있다. 지문은 클래스 구분이 모호한 영상이 많아서 단일결합모델로는 분류에 한계가 있다. 이를 위해 본 논문에서는 새로운 분류기 결합모델인 다중결정템플릿(Multiple Decision Templates, MuDTs)을 제안한다. 이 방법은 하나의 지문클래스로부터 서로 다른 특성을 갖는 클러스터들을 추출하여 각 클러스터에 적합한 결합모델을 생성한다. NIST-database4 데이터로부터 추출한 핑거코드에 대해 실험한 결과. 5클래스와 4클래스 분류문제에 대하여 각각 $90.4\%$와 $94.9\%$의 분류성능(거부율 $1.8\%$)을 획득하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05b
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• pp.955-958
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• 2003

최근에는 웹 환경에 적합한 개방형과 컴포넌트들을 효율적으로 분류하고 추출하는 방법이 진행되고 있다. 본 논문에서는 인터넷환경 하에서 생성되는 산출물을 컴포넌트 객체 형태로 통합 관리하고, 데이터베이스와 연결하여 객체들을 효율적으로 관리해 주는 웹기반 인덱스순서관계정보모델을 설계한다. 이 제안의 장점은 "인덱스 순서관계정보"로 클래스(class)들 사이의 관련된 여러 관계정보를 UML 설계방법에 적응할 수 있는 구조로 변형함으로서 개발자가 관계정보를 쉽게 파악하여 모델링 선계언어인 UML 선계방법에 쉽게 적응할 수 있게 한다. 이 모델로 기존의 시스템을 재사용하고 급변하는 소프트웨어 산업에 능동적으로 대체와 소프트웨어 개발에 시간을 단축함으로써 현존하는 다양한 데이터베이스 군들을 최소한의 코드 수정을 통하여 구동할 수 있게 함으로써 소프트웨어 개발 경제성을 높이는 데 있다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.06a
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• pp.175-177
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• 2011

본 논문의 Live Site 개념을 도입한 웹사이트 저작도구의 실시간 자동화 모델에 관한 연구에서는 MVC(Model-View-Controller) 패턴의 시스템으로 사용자가 요구 사항을 전달하면 jsp에서 jsp 간의 호출을 통해 서버로 변경 사항을 넘기고 그 결과물을 다시 사용자에게 보여주는 형식으로 진행된다. 본 시스템 개발에 사용한 Jquery는 자바스크립트와 HTML 사이의 상호작용을 강조하는 경량화된 web application framework로 일반적 웹 스크립팅에 폭넓게 사용 될 수 있는 추상적 계층을 제공하여 스크립팅에서 필요로 하는 거의 모든 상황에 사용 할 수 있다. 본 논문에서는 추상화된 데이터를 제공하여 일상적인 작업들을 일반화 하고 코드의 크기를 줄이며 극도로 단순하게 개발이 가능한 jquery를 사용하여 거의 모든 브라우저에 호환이 가능한, 사용자 각 개인의 경향에 맞춘 웹사이트 저작 도구를 개발하였다. 본 논문에서는 추상화된 데이터를 제공하므로 일상적인 작업들을 일반화 하고 코드의 크기를 줄이며 극도로 단순하게 개발이 가능한 jquery를 사용하여 거의 모든 브라우저에 호환이 가능한, 사용자 각 개인의 경향에 맞춘 웹 저작 도구를 연구하였다. 전 세계적으로 웹 시장이 대두 되는 이 시점에 본 프로그램은 다양한 웹 제작 공급에 대한 새로운 시장을 형성해 주며, 새로운 콘텐츠 제작 방식의 도입으로 인한 활발한 인터넷 시장이 형성 되리라 기대한다. 현재 일부 생소한 Live Site 개념 즉, '사용자가 직접 보고 느끼며 원하는 대로 만드는 웹' 이란 개념의 가지고 고객 만족 커뮤니티라는 목적에 중점을 둔 본 프로그램 개발은 최근 웹 경향에 따른 이상적인 시스템이라 할 수 있다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.3
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• pp.555-564
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• 2022

Recently, cyberattacks are using hacking techniques utilizing intelligent and advanced malicious codes for non-face-to-face environments such as telecommuting, telemedicine, and automatic industrial facilities, and the damage is increasing. Traditional information protection systems, such as anti-virus, are a method of detecting known malicious URLs based on signature patterns, so unknown malicious URLs cannot be detected. In addition, the conventional static analysis-based malicious URL detection method is vulnerable to dynamic loading and cryptographic attacks. This study proposes a technique for efficiently detecting malicious URLs by dynamically learning malicious URL data. In the proposed detection technique, malicious codes are classified using machine learning-based feature selection algorithms, and the accuracy is improved by removing obfuscation elements after preprocessing using Weighted Euclidean Distance(WED). According to the experimental results, the proposed machine learning-based malicious URL detection technique shows an accuracy of 89.17%, which is improved by 2.82% compared to the conventional method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.301-308
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• 2017

With the popularization of smart phones and the development of the Internet, many people use smart phones to conduct identity verification procedures. smart phones are easier and faster to authenticate than personal desktop computers. However, as Internet hacking technology and malicious code distribution technology rapidly evolve and attack types become more diverse, authentication methods suitable for mobile environment are required. As authentication methods, there are methods such as possessive-based authentication, knowledge-based authentication, biometric-based authentication, pattern-based authentication, and multi-element authentication. In this paper, we propose a user authentication mechanism that uses collected information as authentication factor using smart phone. Using the proposed authentication mechanism, it is possible to use the smart phone information and environment information of the user as a hidden authentication factor, so that the authentication process can be performed without being exposed to others. We implemented the user authentication system using the proposed authentication mechanism and evaluated the effectiveness based on applicability, convenience, and security.

• Journal of IKEEE
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• v.22 no.1
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• pp.156-161
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• 2018

Recently, as the population rapidly increases, food shortages and waste are emerging serious problem. In order to solve this problem, various countries and enterprises are trying research and product development such as a study of consumers' purchasing patterns of food and a development of smart refrigerator using IoT technology. However, the smart refrigerators which currently sold have high price issue and another waste due to malfunction and breakage by complicated configurations. In this paper, we proposed a low-cost smart refrigerator system based on IoT for solving the problem and efficient management of ingredients. The system recognizes and registers ingredients through QR code, image recognition, and speech recognition, and can provide various services of the smart refrigerator. In order to improve an accuracy of image recognition, we used a model using a deep learning algorithm and proved that it is possible to register ingredients accurately.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.46-56
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• 2017

Recently, the spread of IoT technology has been spreading, and it has been applied to all industrial fields such as home / home appliance / medical care. Due to the low specification, low power consumption characteristic and communication data characteristic of IoT, implementation of existing algorithm is difficult thing. From this reason, we have proposed for the first time that encryption and decryption can be proceeded by introducing a kind of variable length bit XOR operation method which changes a variable the bit length value by using carry up and carry down method. We confirmed the practicality of encrypting short message data frequently processed by IoT device / QR code / RFID / NFC without changing the size of data before and after encryption.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.3
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• pp.35-46
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• 2016

Social network services (SNS) that help to build relationship network and share a particular interest or activity freely according to their interests by posting comments, photos, videos,${\ldots}$ on online communities such as blogs have adopted and developed widely as a social phenomenon. Several researches have been done to explore the pattern and valuable information in social networks data via text mining such as opinion mining and semantic analysis. For improving the efficiency of text mining, keyword-based approach have been applied but most of researchers argued the limitations of the rules of Korean orthography. This research aims to construct a database of non-standard Korean words which are difficulty in data mining such abbreviations, slangs, strange expressions, emoticons in order to improve the limitations in keyword-based text mining techniques. Based on the study of subjective opinions about specific topics on blogs, this research extracted non-standard words that were found useful in text mining process.