• Communications of the Korean Institute of Information Scientists and Engineers
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• v.28 no.11
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• pp.112-116
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• 2010

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.422-435
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• 2016

Despite the convenience brought by the advances in web and Internet technology, users are increasingly being exposed to the danger of various types of cyber attacks. In particular, recent studies have shown that today's cyber attacks usually occur on the web via malware distribution and the stealing of personal information. A drive-by download is a kind of web-based attack for malware distribution. Researchers have proposed various methods for detecting a drive-by download attack effectively. However, existing methods have limitations against recent evasion techniques, including JavaScript obfuscation, hiding, and dynamic code evaluation. In this paper, we propose an emulation-based malicious webpage detection method. Based on our study on the limitations of the existing methods and the state-of-the-art evasion techniques, we will introduce four features that can detect malware distribution networks and we applied them to the proposed method. Our performance evaluation using a URL scan engine provided by VirusTotal shows that the proposed method detects malicious webpages more precisely than existing solutions.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1121-1129
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• 2013

Recent malware distribution causes severe and nation-wide problems such as 3 20 cyber attack in Korea. In particular, Drive-by download attack, which is one of attack types to distribute malware through the web, becomes the most prevalent and serious threat. To prevent Drive-by download attacks, it is necessary to analyze MDN(Malware Distribution Networks) of Drive-by download attacks. Effective analysis of MDN requires a detection of obfuscated and/or encapsulated JavaScript in a web page. In this paper, we propose the scheme called Multi-level emulation to analyze the process of malware distribution. The proposed scheme analyzes web links used for malware distribution to support the efficient analysis of MDN.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1290-1295
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• 2016

Recently, as mobile internet usage has been increasing rapidly, malware attacks through user's web browsers has been spreading in a way of social engineering or drive-by downloading. Existing defense mechanism against drive-by download attack mainly focused on final download sites and distribution paths. However, detection and prevention of injection sites to inject malicious code into the comprised websites have not been fully investigated. In this paper, for the purpose of improving defense mechanisms against these malware downloads attacks, we focus on detecting the injection site which is the key source of malware downloads spreading. As a result, in addition to the current URL blacklist techniques, we proposed the enhanced method which adds features of detecting the injection site to prevent the malware spreading. We empirically show that the proposed method can effectively minimize malware infections by blocking the source of the infection spreading, compared to other approaches of the URL blacklisting that directly uses the drive-by browser exploits.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.1003-1007
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• 2009

Client-side attacks including drive-by download target vulnerabilities in client applications that interact with a malicious server or process malicious data. A typical client-side attack is web-based one related to a malicious web page exploiting specific browser vulnerability that can execute mal ware on the client system (PC) or give complete control of it to the malicious server. To defend those attacks, this paper has constructed high interaction client honeypot system using Capture-HPC that adopts execution-based detection in virtual machine. We have detected and classified malicious web pages using the system. We have also analyzed the system's performance in terms of the number of virtual machine images and the number of browsers executed simultaneously in each virtual machine. Experimental results show that the system with one virtual machine image obtains better performance with less reverting overhead. The system also shows good performance when the number of browsers executed simultaneously in a virtual machine is 50.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.93-103
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• 2019

Recently, malicious code distribution of ransomware through a web site based on a drive-by-download attack has resulted in service disruptions to the web site and damage to PC files for end users. Therefore, analyzing the characteristics of the target web site industry, distribution time, application type, and type of malicious code that is being exploited can predict and respond to the attacker's attack activities by analyzing the status and trend of malicious code sites. In this paper, we will examine the distribution of malicious codes to 3.43 million websites in Korea to draw out the characteristics of each detected landing site, exploit site, and distribution site, and discuss countermeasures.

• Convergence Security Journal
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• v.14 no.4
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• pp.61-71
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• 2014

In recent years, malwares in Android smartphones are becoming increased explosively. Since a great deal of appsare deployed day after day, detecting the malwares requires commercial anti-virus companies to spend much time and resources. Such a situation causes malwares to be detected after they have become already spread. We propose a scheme called TAU that dynamically tracks application behaviors to specify apps with potential security risks. TAU keeps track of how a user's interactions to smartphones incurs the app installation, the route of app spread, and the behavior of app execution. This tracking specifies apps that have the possibility of attacking the smartphones using the drive-by download and update attack schemes. Moreover, the tracked behaviors are used to decide whether apps are repackaged or not. Therefore, TAU allows anti-virus companies to detect malwares efficiently and rapidly by guiding to preferentially analyze apps with potential security risks.

• Convergence Security Journal
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• v.18 no.3
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• pp.37-44
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• 2018

Today we live in a flood of web sites and access numerous websites through the Internet to obtain various information. However, unless the security of the Web site is secured, Web site security can not be secured from various malicious attacks. Hacking attacks, which exploit Web site security vulnerabilities for various reasons, such as financial and political purposes, are increasing. Various attack techniques such as SQL-injection, Cross-Site Scripting(XSS), and Drive-By-Download are being used, and the technology is also evolving. In order to defend against these various hacking attacks, it is necessary to remove the vulnerabilities from the development stage of the website, but it is not possible due to various problems such as time and cost. In order to compensate for this, it is important to identify vulnerabilities in Web sites through web vulnerability checking and take action. In this paper, we investigate web vulnerabilities and diagnostic techniques and try to understand the priorities of vulnerabilities in the development stage according to the actual status of each case through cases of actual web vulnerability diagnosis.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.100-115
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• 2019

Malicious code distribution on the Internet is one of the most critical Internet-based threats and distribution technology has evolved to bypass detection systems. As a new defense against the detection bypass technology of malicious attackers, this study proposes the automated tracing of malicious websites in a malware distribution network (MDN). The proposed technology extracts automated links and classifies websites into malicious and normal websites based on link structure. Even if attackers use a new distribution technology, website classification is possible as long as the connections are established through automated links. The use of a real web-browser and proxy server enables an adequate response to attackers' perception of analysis environments and evasion technology and prevents analysis environments from being infected by malicious code. The validity and accuracy of the proposed method for classification are verified using 20,000 links, 10,000 each from normal and malicious websites.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.79-80
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• 2014

악성코드 유포를 위해 가장 많이 사용되는 Drive-by-download 공격에는 주로 자바스크립트가 사용되며, 공격자는 탐지 시스템의 우회하고 행위 분석을 어렵게 하기 위해 공격에 사용되는 스크립트를 난독화 한다. 난독화 된 자바스크립트를 탐지하기 위한 여러 기존의 연구들이 있었지만 최소한의 코드가 난독화 되어 있거나 정상 코드와 혼재할 경우 난독화 여부를 판단하기 어려운 한계가 있다. 본 논문에서는 난독화 된 자바 스크립트를 효과적으로 탐지하기 위해 전체 스크립트를 실행 단위 코드로 나눠 분석에 필요한 특징을 효과적으로 추출하는 방법을 제안한다.