A topology based flow model for computing domain reputation

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Abstract

The Domain Name System (DNS) is an essential component of the internet infrastructure that translates domain names into IP addresses. Recent incidents verify the enormous damage of malicious activities utilizing DNS such as bots that use DNS to locate their command & control servers. Detecting malicious domains using the DNS network is therefore a key challenge. We project the famous expression Tell me who your friends are and I will tell you who you are, motivating many social trust models, on the internet domains world. A domain that is related to malicious domains is more likely to be malicious as well. In this paper, our goal is to assign reputation values to domains and IPs indicating the extent to which we consider them malicious. We start with a list of domains known to be malicious or benign and assign them reputation scores accordingly. We then construct a DNS based graph in which nodes represent domains and IPs. Our new approach for computing domain reputation applies a flow algorithm on the DNS graph to obtain the reputation of domains and identify potentially malicious ones. The experimental evaluation of the flow algorithm demonstrates its success in predicting malicious domains.

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APA

Mishsky, I., Gal-Oz, N., & Gudes, E. (2015). A topology based flow model for computing domain reputation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9149, pp. 277–292). Springer Verlag. https://doi.org/10.1007/978-3-319-20810-7_20

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