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Distributed and collaborative malware analysis with MASS

: Rump, F.; Behner, T.; Ernst, R.


Tölle, J. ; Institute of Electrical and Electronics Engineers -IEEE-; IEEE Computer Society; IEEE Computer Society, Technical Committee on Computer Communications:
IEEE 42nd Conference on Local Computer Networks, LCN 2017. Proceedings : 9-12 October 2017, Singapore
Piscataway, NJ: IEEE, 2017
ISBN: 978-1-5090-6523-3
ISBN: 978-1-5090-6522-6
ISBN: 978-1-5090-6524-0
Conference on Local Computer Networks (LCN) <42, 2017, Singapore>
Conference Paper
Fraunhofer FKIE ()

Malicious software poses a great risk to critical infrastructure. Researchers have proposed numerous ways to analyze malware behavior in order to understand and respond to this threat. However, only little attention has been paid to the organization of the malware analysis process itself. In this paper we present the Malware Analysis and Storage System (MASS), a novel framework for malware analysis. MASS is designed as a distributed and scalable system and aims to empower cooperation between malware researchers. We will describe the central aspects of the framework and explain the malware analysis process flow. Furthermore, we will present a performance evaluation to demonstrate the suitability of the framework for typical malware analysis tasks.