• Title/Summary/Keyword: 은닉 URL 탐지

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Detection System of Hidden Javascript URLs in Web Source Codes (웹 소스코드에 은닉된 Javascript URL 점검체계)

  • Park, Hweerang;Cho, Sangil;Park, JungKyu;Cho, Youngho
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.01a
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    • pp.119-122
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    • 2019
  • 최근 웹 변조 공격은 대형 포탈, 은행, 학교 등 접속자가 많은 홈페이지에 악성 URL을 불법 삽입하여 해당 URL을 통해 접속자 PC에 자동으로 악성코드 유포하고 대규모 봇넷(botnet)을 형성한 후 DDoS 공격을 수행하거나 감염 PC들의 정보를 지속적으로 유출하는 형태로 수행된다. 이때, 홈페이지에 삽입되는 악성 URL은 탐지가 어렵도록 Javascript 난독화 기법(obfuscation technique) 등으로 은밀히 삽입된다. 본 논문에서는 웹 소스코드에 은닉된 악성 Javascript URL들에 대한 일괄 점검체계를 제안하며, 구현된 점검체계의 prototype을 활용하여 점검성능에 대한 시험결과를 제시한다.

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A Study on Minimizing Infection of Web-based Malware through Distributed & Dynamic Detection Method of Malicious Websites (악성코드 은닉사이트의 분산적, 동적 탐지를 통한 감염피해 최소화 방안 연구)

  • Shin, Hwa-Su;Moon, Jong-Sub
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.21 no.3
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    • pp.89-100
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    • 2011
  • As the Internet usage with web browser is more increasing, the web-based malware which is distributed in websites is going to more serious problem than ever. The central type malicious website detection method based on crawling has the problem that the cost of detection is increasing geometrically if the crawling level is lowered more. In this paper, we proposed a security tool based on web browser which can detect the malicious web pages dynamically and support user's safe web browsing by stopping navigation to a certain malicious URL injected to those web pages. By applying these tools with many distributed web browser users, all those users get to participate in malicious website detection and feedback. As a result, we can detect the lower link level of websites distributed and dynamically.

An Enhanced method for detecting obfuscated Javascript Malware using automated Deobfuscation (난독화된 자바스크립트의 자동 복호화를 통한 악성코드의 효율적인 탐지 방안 연구)

  • Ji, Sun-Ho;Kim, Huy-Kang
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.22 no.4
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    • pp.869-882
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    • 2012
  • With the growth of Web services and the development of web exploit toolkits, web-based malware has increased dramatically. Using Javascript Obfuscation, recent web-based malware hide a malicious URL and the exploit code. Thus, pattern matching for network intrusion detection systems has difficulty of detecting malware. Though various methods have proposed to detect Javascript malware on a users' web browser, the overall detection is needed to counter advanced attacks such as APTs(Advanced Persistent Treats), aimed at penetration into a certain an organization's intranet. To overcome the limitation of previous pattern matching for network intrusion detection systems, a novel deobfuscating method to handle obfuscated Javascript is needed. In this paper, we propose a framework for effective hidden malware detection through an automated deobfuscation regardless of advanced obfuscation techniques with overriding JavaScript functions and a separate JavaScript interpreter through to improve jsunpack-n.

Research on Malicious code hidden website detection method through WhiteList-based Malicious code Behavior Analysis (WhiteList 기반의 악성코드 행위분석을 통한 악성코드 은닉 웹사이트 탐지 방안 연구)

  • Ha, Jung-Woo;Kim, Huy-Kang;Lim, Jong-In
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.21 no.4
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    • pp.61-75
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    • 2011
  • Recently, there is significant increasing of massive attacks, which try to infect PCs that visit websites containing pre-implanted malicious code. When visiting the websites, these hidden malicious codes can gain monetary profit or can send various cyber attacks such as BOTNET for DDoS attacks, personal information theft and, etc. Also, this kind of malicious activities is continuously increasing, and their evasion techniques become professional and intellectual. So far, the current signature-based detection to detect websites, which contain malicious codes has a limitation to prevent internet users from being exposed to malicious codes. Since, it is impossible to detect with only blacklist when an attacker changes the string in the malicious codes proactively. In this paper, we propose a novel approach that can detect unknown malicious code, which is not well detected by a signature-based detection. Our method can detect new malicious codes even though the codes' signatures are not in the pattern database of Anti-Virus program. Moreover, our method can overcome various obfuscation techniques such as the frequent change of the included redirection URL in the malicious codes. Finally, we confirm that our proposed system shows better detection performance rather than MC-Finder, which adopts pattern matching, Google's crawling based malware site detection, and McAfee.