Finding malware on a web scale

1Citations
Citations of this article
10Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In recent years, attacks that exploit vulnerabilities in browsers and their associated plugins have increased significantly. These attacks are often written in JavaScript and millions of URLs contain such malicious content. Over the last several years, we have created a series of techniques designed to detect and prevent malicious software or malware. These techniques focus on detecting malware that infects web pages. Much of this research has been done in close collaboration with a major search engine, Bing, which is interested in making sure it does not present malicious results to its users, independently of the user's browser, location, or operating system. As such, detection needs to be as general and wide-reaching as possible. While some of the techniques summarized below can be deployed within a web browser, our primary deployment model involves crawling the web in an effort to find and blacklist malicious pages. In the rest of this paper, we will summarize three related projects: Nozzle, Zozzle, and Rozzle. Nozzle is a runtime malware detector. Zozzle is a a mostly static malware detector. Finally, Rozzle is a de-cloacking technique that amplifies both. © 2012 Springer-Verlag Berlin Heidelberg.

Cite

CITATION STYLE

APA

Livshits, B. (2012). Finding malware on a web scale. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7531 LNCS, pp. 1–2). Springer Verlag. https://doi.org/10.1007/978-3-642-33704-8_1

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free