On the reverse engineering of the citadel botnet

24Citations
Citations of this article
26Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Citadel is an advanced information stealing malware that targets financial information. This malware poses a real threat against the confidentiality and integrity of personal and business data. Recently, a joint operation has been conducted by FBI and Microsoft Digital Crimes Unit in order to take down Citadel command-and-control servers. The operation caused some disruption in the botnet but has not stopped it completely. Due to the complex structure and advanced anti-reverse engineering techniques, the Citadel malware analysis process is challenging and time-consuming. This allows cyber criminals to carry on with their attacks while the analysis is still in progress. In this paper, we present the results of the Citadel reverse engineering and provide additional insights into the functionality, inner workings, and open source components of the malware. In order to accelerate the reverse engineering process, we propose a clone-based analysis methodology. Citadel is an offspring of a previously analyzed malware called Zeus. Thus, using the former as a reference, we can measure and quantify the similarities and differences of the new variant. Two types of code analysis techniques are provided in the methodology namely assembly to source code matching, and binary clone detection. The methodology can help reduce the number of functions that should be analyzed manually. The analysis results prove that the approach is promising in Citadel malware analysis. Furthermore, the same approach is applicable to similar malware analysis scenarios. © 2014 Springer International Publishing Switzerland.

Cite

CITATION STYLE

APA

Rahimian, A., Ziarati, R., Preda, S., & Debbabi, M. (2014). On the reverse engineering of the citadel botnet. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8352 LNCS, pp. 408–425). Springer Verlag. https://doi.org/10.1007/978-3-319-05302-8_25

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