Distributed and Collaborative Malware Analysis with MASS

Rump, Fabian; Behner, Timm; Ernst, Raphael

doi:10.1109/lcn.2017.95

Cited by 3 publications

(3 citation statements)

References 3 publications

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“…In the future, malware de-obfuscation and steganography analysis must be done in a more systematic and efficient way when the volume of more sophisticated malware increases. Frameworks for distributed and automated malware analysis like MASS [20] could be a suitable approach for handling large volumes of malware samples retrieved from honeynets.…”

Section: The Road Aheadmentioning

confidence: 99%

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The New Threats of Information Hiding: The Road Ahead

et al. 2018

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Compared to cryptography, steganography is a less discussed domain. However, there is a recent trend of exploiting various information hiding techniques to empower malware, for instance to bypass security frameworks of mobile devices or to exfiltrate sensitive data. This is mostly due to the need to counteract increasingly sophisticated security mechanisms, such as code analysis, runtime countermeasures, or real-time traffic inspection tools. In this perspective, this paper presents malware exploiting information hiding in a broad sense, i.e., it does not focus on classical covert channels, but also discusses other camouflage techniques. Differently from other works, this paper solely focuses on real-world threats observed in the 2011 -2017 timeframe. The observation indicates a growing number of malware equipped with some form of data hiding capabilities and a lack of effective and universal countermeasures.

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Section: The Road Aheadmentioning

confidence: 99%

“…Frameworks for distributed and automated malware analysis like MASS [20] could be a suitable approach for handling large volumes of malware samples retrieved from honeynets.…”

Section: The Road Aheadmentioning

confidence: 99%

The New Threats of Information Hiding: The Road Ahead

et al. 2018

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“…In the internet-based collaborative computing [1] mode, there are similarities between the operation and management of collaborative applications and the scheduling of nodes in distributed systems [2]. The performance of applications is affected by the construction and management of system infrastructure.…”

Section: Introductionmentioning

confidence: 99%

A New Collaborative Scheduling Mechanism Based on Grading Mapping for Resource Balance in Distributed Object Cloud Storage System

Chen

et al. 2021

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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An algorithmic mapping of storage locations brings high storage efficiency to the storage system, but the loss of efficient scheduling makes systems prone to crashing at low usage. This paper uses the Ceph storage system as a research sample to analyze these issues and proposes a grading mapping adaptive storage resource collaborative optimization mechanism. This approach grading both the storage device and the storage content, and introduced random factors and influence factors as two-factors to quantify the grading mapping relationship between the two of them. This relation coordinates the storage systems' performance and reliability. In addition, a collaborative storage algorithm is proposed to realize balanced storage efficiency and control data migration. The experimental results show that in comparison with the inherent mechanism in the traditional Ceph system, the proposed cooperative storage adaptation mechanism for data balancing has increased the average system usage by 17% and reduces data migration by 50% compared to the traditional research approach.

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