• Title/Summary/Keyword: malicious web pages

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Classifying Malicious Web Pages by Using an Adaptive Support Vector Machine

  • Hwang, Young Sup;Kwon, Jin Baek;Moon, Jae Chan;Cho, Seong Je
    • Journal of Information Processing Systems
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    • v.9 no.3
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    • pp.395-404
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    • 2013
  • In order to classify a web page as being benign or malicious, we designed 14 basic and 16 extended features. The basic features that we implemented were selected to represent the essential characteristics of a web page. The system heuristically combines two basic features into one extended feature in order to effectively distinguish benign and malicious pages. The support vector machine can be trained to successfully classify pages by using these features. Because more and more malicious web pages are appearing, and they change so rapidly, classifiers that are trained by old data may misclassify some new pages. To overcome this problem, we selected an adaptive support vector machine (aSVM) as a classifier. The aSVM can learn training data and can quickly learn additional training data based on the support vectors it obtained during its previous learning session. Experimental results verified that the aSVM can classify malicious web pages adaptively.

Classification of Malicious Web Pages by Using SVM (SVM을 활용한 악성 웹 페이지 분류)

  • Hwang, Young-Sup;Moon, Jae-Chan;Cho, Seong-Je
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.3
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    • pp.77-83
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    • 2012
  • As web pages provide various services, the distribution of malware via the web pages is being also increased. Malware can make personal information leak, system mal-function and system be zombie. To protect this damages, we should block the malicious web pages. Because the malicious codes embedded in web pages are obfuscated or transformed, it is difficult to detect them using signature-based approaches which are used by current anti-virus software. To overcome this problem, we extracted features to classify malicious web pages and benign ones by analyzing web pages. And we propose a classification method using SVM which is widely used in machine learning. Experimental results show that the proposed method is better than other methods. The proposed method could classify malicious web pages correctly and be helpful to block the distribution of malicious codes.

JsSandbox: A Framework for Analyzing the Behavior of Malicious JavaScript Code using Internal Function Hooking

  • Kim, Hyoung-Chun;Choi, Young-Han;Lee, Dong-Hoon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.2
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    • pp.766-783
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    • 2012
  • Recently, many malicious users have attacked web browsers using JavaScript code that can execute dynamic actions within the browsers. By forcing the browser to execute malicious JavaScript code, the attackers can steal personal information stored in the system, allow malware program downloads in the client's system, and so on. In order to reduce damage, malicious web pages must be located prior to general users accessing the infected pages. In this paper, a novel framework (JsSandbox) that can monitor and analyze the behavior of malicious JavaScript code using internal function hooking (IFH) is proposed. IFH is defined as the hooking of all functions in the modules using the debug information and extracting the parameter values. The use of IFH enables the monitoring of functions that API hooking cannot. JsSandbox was implemented based on a debugger engine, and some features were applied to detect and analyze malicious JavaScript code: detection of obfuscation, deobfuscation of the obfuscated string, detection of URLs related to redirection, and detection of exploit codes. Then, the proposed framework was analyzed for specific features, and the results demonstrate that JsSandbox can be applied to the analysis of the behavior of malicious web pages.

An Implementation of System for Detecting and Filtering Malicious URLs (악성 URL 탐지 및 필터링 시스템 구현)

  • Chang, Hye-Young;Kim, Min-Jae;Kim, Dong-Jin;Lee, Jin-Young;Kim, Hong-Kun;Cho, Seong-Je
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.4
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    • pp.405-414
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    • 2010
  • According to the statistics of SecurityFocus in 2008, client-side attacks through the Microsoft Internet Explorer have increased by more than 50%. In this paper, we have implemented a behavior-based malicious web page detection system and a blacklist-based malicious web page filtering system. To do this, we first efficiently collected the target URLs by constructing a crawling system. The malicious URL detection system, run on a specific server, visits and renders actively the collected web pages under virtual machine environment. To detect whether each web page is malicious or not, the system state changes of the virtual machine are checked after rendering the page. If abnormal state changes are detected, we conclude the rendered web page is malicious, and insert it into the blacklist of malicious web pages. The malicious URL filtering system, run on the web client machine, filters malicious web pages based on the blacklist when a user visits web sites. We have enhanced system performance by automatically handling message boxes at the time of ULR analysis on the detection system. Experimental results show that the game sites contain up to three times more malicious pages than the other sites, and many attacks incur a file creation and a registry key modification.

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.

Execution-based System and Its Performance Analysis for Detecting Malicious Web Pages using High Interaction Client Honeypot (고 상호작용 클라이언트 허니팟을 이용한 실행 기반의 악성 웹 페이지 탐지 시스템 및 성능 분석)

  • Kim, Min-Jae;Chang, Hye-Young;Cho, Seong-Je
    • 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.

Security Check Scheduling for Detecting Malicious Web Sites (악성사이트 검출을 위한 안전진단 스케줄링)

  • Choi, Jae Yeong;Kim, Sung Ki;Min, Byoung Joon
    • KIPS Transactions on Computer and Communication Systems
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    • v.2 no.9
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    • pp.405-412
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    • 2013
  • Current web has evolved to a mashed-up format according to the change of the implementation and usage patterns. Web services and user experiences have improved, however, security threats are also increased as the web contents that are not yet verified combine together. To mitigate the threats incurred as an adverse effect of the web development, we need to check security on the combined web contents. In this paper, we propose a scheduling method to detect malicious web pages not only inside but also outside through extended links for secure operation of a web site. The scheduling method considers several aspects of each page including connection popularity, suspiciousness, and check elapse time to make a decision on the order for security check on numerous web pages connected with links. We verified the effectiveness of the security check complying with the scheduling method that uses the priority given to each page.

Implementation of Web Searching Robot for Detecting of Phishing and Pharming in Homepage (홈페이지에 삽입된 악성코드 및 피싱과 파밍 탐지를 위한 웹 로봇의 설계 및 구현)

  • Kim, Dae-Yu;Kim, Jung-Tae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.11
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    • pp.1993-1998
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    • 2008
  • Web robot engine for searching web sever vulnerability and malicious code is proposed in this paper. The main web robot function is based on searching technology which is derived from analyses of private information threat. We implemented the detecting method for phishing, pharming and malicious code on homepage under vulnerable surroundings. We proposed a novel approachm which is independent of any specific phishing implementation. Our idea is to examine the anomalies in web pages.

Detect H1TP Tunnels Using Support Vector Machines (SVM을 이용한 HTTP 터널링 검출)

  • He, Dengke;Nyang, Dae-Hun;Lee, Kyung-Hee
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.21 no.3
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    • pp.45-56
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    • 2011
  • Hyper Text Transfer Protocol(HTTP) is widely used in nearly every network when people access web pages, therefore HTTP traffic is usually allowed by local security policies to pass though firewalls and other gateway security devices without examination. However this characteristic can be used by malicious people. With the help of HTTP tunnel applications, malicious people can transmit data within HTTP in order to circumvent local security policies. Thus it is quite important to distinguish between regular HTTP traffic and tunneled HTTP traffic. Our work of HTTP tunnel detection is based on Support Vector Machines. The experimental results show the high accuracy of HTTP tunnel detection. Moreover, being trained once, our work of HTTP tunnel detection can be applied to other places without training any more.

Research on Countermeasure of SQL Injection Attack (SQL Injection 공격을 효율적으로 방어하는 대응책 연구)

  • Hong, Sunghyuck
    • Journal of the Korea Convergence Society
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    • v.10 no.10
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    • pp.21-26
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    • 2019
  • At present, it is indispensable to utilize data as an information society. Therefore, the database is used to manage large amounts of data. In real life, most of the data in a database is the personal information of a group of members. Because personal information is sensitive data, the role of the database administrator who manages personal information is important. However, there is a growing number of attacks on databases to use this personal information in a malicious way. SQL Injection is one of the most known and old hacking techniques. SQL Injection attacks are known as an easy technique, but countermeasures are easy, but a lot of efforts are made to avoid SQL attacks on web pages that require a lot of logins, but some sites are still vulnerable to SQL attacks. Therefore, this study suggests effective defense measures through analysis of SQL hacking technology cases and contributes to preventing web hacking and providing a secure information communication environment.