• Proceedings of the Korean Information Science Society Conference
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• 2006.10c
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• pp.511-514
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• 2006

비정상행위 탐지를 위한 프로파일 기술은 침임탐지시스템의 성능 향상을 위한 핵심기술로서, 높은 공격 탐지율과 침입탐지시스템의 수행 시간 단축을 위해 반드시 요구되는 기술이다. 최근 인터넷의 보급과 활성화로 웹 어플리케이션 보안을 위한 연구가 활발히 진행되고 있으나, 웹 애플리케이션의 개발 언어와 공격 특성을 반영하지 못해 그 효율성이 저하되고 있다. 본 논문에서는 웹 공격 탐지를 위해 연구 되었던 서열정렬 알고리즘을 이용한 웹 공격 탐지의 성능 개선을 위하여 웹 애플리케이션 개발에 주로 사용되는 스크립트파일을 기반으로 한 프로파일 방법을 제안하고 실험 결과를 기술하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.259-263
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• 2015

The vulnerabilities related to Flash player which is widely used in internet browsers and office programs are gradually increased. To detect Flash malwares, previous work focuses on predefined features of ActionScript. However above work cannot detect new/mutated Flash malwares, since predefined features could not cover the new patterns of new/mutated Flash mawares. To solve this problem, we propose a Flash malware detection method that uses machine learning to learn Flash Tag patterns and classify Flash by using machine learning.

• Journal of Industrial Convergence
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• v.16 no.4
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• pp.47-52
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• 2018

WebShell is a web script file created by a hacker to remotely commands to a web server. The hacker can bypass the security system using the web shell, access the system, control the system such as file modification, copying and deletion, install malicious code in the web source code, attack the user's PC, And so on. There are many types of WebShell attack, but we study about attacks on PHP and JSP based web server which are used as representative ones. And we propose the method of web page management, method of development, and several other methods. By using these countermeasures, it is possible to effectively prevent damage caused by WebShell attacks.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.669-677
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• 2020

As the number of Internet users exploded, attacks on the web increased. In addition, the attack patterns have been diversified to bypass existing defense techniques. Traditional web firewalls are difficult to detect attacks of unknown patterns.Therefore, the method of detecting abnormal behavior by artificial intelligence has been studied as an alternative. Specifically, attempts have been made to apply natural language processing techniques because the type of script or query being exploited consists of text. However, because there are many unknown words in scripts and queries, natural language processing requires a different approach. In this paper, we propose a new classification model which uses byte pair encoding (BPE) technology to learn the embedding vector, that is often used for web attack payloads, and uses an attention mechanism-based Bi-GRU neural network to extract a set of tokens that learn their order and importance. For major web attacks such as SQL injection, cross-site scripting, and command injection attacks, the accuracy of the proposed classification method is about 0.9990 and its accuracy outperforms the model suggested in the previous study.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.5
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• pp.35-45
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• 2005

There has recently been an increase of phishing attacks, attacks which lure users into revealing their personal information to an attacker who in turn exploits this information for economic gain. The conventional methods of fooling the user with similarly modified mail or address are constantly evolving and have diversified to include the forgery of mail or domain addresses. Recently the injury incurred by these attacks has greatly increased as attackers exploit the weaknesses found on a few web browsers and used these to conduct phishing attacks based on URL spoofing. Furthermore we are now witnessing the entrance of highly advanced phishing techniques that no longer simply rely on vulnerabilities, but employ ordinary script, HTML, DNS sniffing, and the list goes on. In this paper we first discuss means of investigating and preventing the advanced URL spoofing techniques used in phishing attacks, and then propose a scheme for fundamentally restricting them altogether.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1129-1135
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• 2016

The NH-NongHyup network and servers were paralyzed in 2011, in the 2013 3.20 cyber attack happened and classified documents of Korea Hydro & Nuclear Power Co. Ltd were leaked on december in 2015. All of them were conducted by a foreign country. These attacks were planned for a long time compared to the script kids attacks and the techniques used were very complex and sophisticated. However, no successful solution has been implemented to defend an APT attacks(Advanced Persistent Threat Attacks) thus far. We will use big data analytics to analyze whether or not APT attacks has occurred. This research is based on the data collected through ISAC monitoring among 3 hierarchical Korean Defense System. First, we will introduce related research about big data analytics and machine learning. Then, we design two big data analytics models to detect an APT attacks. Lastly, we will present an effective response method to address a detected APT attacks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.317-320
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• 2016

The NH-NongHyup network and servers were paralyzed in 2011, in the 2013 3.20 cyber attack happened and Classified documents of Korea Hydro & Nuclear Power Co. Ltd were leaked on December in 2015. All of them were conducted by a foreign country. These attacks were planned for a long time compared to the script kids attacks and the techniques used were very complex and sophisticated. However, no successful solution has been implemented to defend an APT attack thus far. Therefore, we will use big data analytics to analyze whether or not APT attack has occurred in order to defend against the manipulative attackers. This research is based on the data collected through ISAC monitoring among 3 hierarchical Korean defense system. First, we will introduce related research about big data analytics and machine learning. Then, we design two big data analytics models to detect an APT attack and evaluate the models' accuracy and other results. Lastly, we will present an effective response method to address a detected APT attack.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.275-276
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• 2016

기존의 HTML의 경우 미디어 재생, 3D 그래픽 처리, 웹 소켓 통신 등을 위해서는 Silverlight나 Active-X와 같은 비 표준 플러그인을 설치해야만 구현할 수 있었다. 하지만, 차세대 웹 표준인 HTML5에서는 별도의 플러그인 설치 없이 자바스크립트의 신규 기능만으로 미디어 재생 등과 같은 동적인 기능을 구현할 수 있다. 이처럼 HTML5에서 자바스크립트 기능이 강화됨에 따라 이를 악용한 신종 사이버 공격의 위협이 증가 하고 있다. 기존의 악성 코드 공격과는 달리 사용자 단말에 어떠한 감염도 없이, 악성 스크립트를 삽입한 웹 페이지 접속만으로 악성 행위를 유발하기 때문에 기존의 보안기술로는 탐지에 한계가 존재한다. 이에 본 논문에서는 로컬 프록시를 활용하여, 사용자 단말에서 송/수신되는 HTTP 트래픽을 수집하고, 이를 분석하여, 악성 자바스크립트를 탐지 및 차단하고, 나아가서 난독화 된 악성 자바스크립트를 탐지하는 방법을 제안하고자 한다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1105-1114
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• 2021

Due to the recent surge in popularity of cryptocurrency, the threat of cryptojacking, a malicious code for mining cryptocurrencies, is increasing. In particular, web-based cryptojacking is easy to attack because the victim can mine cryptocurrencies using the victim's PC resources just by accessing the website and simply adding mining scripts. The cryptojacking attack causes poor performance and malfunction. It can also cause hardware failure due to overheating and aging caused by mining. Cryptojacking is difficult for victims to recognize the damage, so research is needed to efficiently detect and block cryptojacking. In this work, we take representative distinct symptoms of cryptojacking as an indicator and propose a new architecture. We utilized the K-Nearst Neighbors(KNN) model, which trained computer performance indicators as behavior-based dynamic analysis techniques. In addition, a K-means model, which trained the frequency of malicious script words for script similarity-based static analysis techniques, was utilized. The KNN model had 99.6% accuracy, and the K-means model had a silhouette coefficient of 0.61 for normal clusters.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.4
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• pp.1025-1036
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• 2016

The conversion of the international standard web utilization HTML5 technology is being developed for improvement of the internet environment based on nonstandard technology like ActiveX. Hyper Text Markup Language 5 (HTML5) of basic programming language for creating a web page is designed to consider the security more than HTML4. However, the range of attacks increased and a variety of security threats generated from HTML4 environment inherited by new HTML5 API. In this paper, we focus on the script-based attack such as CSRF (Cross-Site Request Forgery), Cookie Sniffing, and HTML5 API such as CORS (Cross-Origin Resource Sharing), Geolocation API related with the infringement of the personal information. We reproduced the infringement cases actually and embodied a detection module of a Plug-in type diagnosed based on client. The scanner allows it to detect and respond to the vulnerability of HTML5 previously, thereby self-diagnosing the reliability of HTML5-based web applications or web pages. In a case of a new vulnerability, it also easy to enlarge by adding another detection module.