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Detection and analysis of drive-by attacks

Detection and analysis of drive-by attacks

Name: Detection and analysis of drive-by attacks

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Detection and Analysis of Drive-by-Download Attacks and Malicious JavaScript Code. Marco Cova, Christopher Kruegel, and Giovanni Vigna. University of. 26 Apr Detection and analysis of drive-by-download attacks and malicious These attacks usually result in the download of additional malware that  Abstract - Authors - References - Cited By. 19 Dec Download citation | Detection and analys | JavaScript is a browser scripting language that allows developers to create sophisticated.

CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): JavaScript is a browser scripting language that allows developers to create. Drive-by downloads attack has become the primary attack vehicle for One existing method of detecting drive-by download attacks is using static analysis. This paper presents a novel approach to the detection and analysis of malicious JavaScript code. Our approach combines anomaly detection with emulation to.

Detection and Analysis of Drive-by-Download Attacks and Malicious JavaScript Code –Use libAnomaly, a library to develop anomaly detection systems. for real drive-by download attacks found in a real time email spam feed M. Cova, C. Kruegel, and G. Vigna, “Detection and analysis of drive-by-download. Drive-by Download Attack (DBD) is one of the major threats on the web fresh information related to malicious activities to detect and prevent such attacks. 16 Aug Flash drive-by downloads and malvertising continue to be common attack vectors for malware infections. Here's a look at how these attacks can. detection and prevention of drive-by-download attacks. Em- bedded in a web Drive-by downloads, web security, static code analysis, dy- namic code analysis .

Abstract. Malicious web sites perform drive-by download attacks to infect their .. based detection methods, such as [22], might also prove effective in protecting. 31 Dec 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 attacks exploit vulnerabilities in Web browsers, and users are been used in the detection/prediction approaches of drive-by-download attacks . Opcode analysis (dynamic analysis) into our approach-I (static approach). Our method is based on fine-grained analysis of Drive-by-Download attacks based on HTTP Context-Types. We also evaluate a new detection method for.

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