Searched for: subject%3A%22malware%255C+detection%22
(1 - 4 of 4)
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Park, Sung kyung (author)
Identifying novel malware and their behaviour enables security engineers to prevent and protect users with devices on the network from attackers. MalPaCA is an algorithm that helps to understand the behaviours of the network traffic by clustering uni-directional network connections which can be analyzed further to interpret which label suites...
bachelor thesis 2021
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Garack, Jonathan (author)
MalPaCa is an unsupervised clustering tool, which the main purpose is to cluster unidirectional network connections based on network behavior. The clustering is only based on non-intrusive (private) packet features such as transport and network header fields, and thus it has a strong potential use-case. This paper focuses on feature extraction...
bachelor thesis 2021
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Verwer, S.E. (author), Nadeem, A. (author), Hammerschmidt, C.A. (author), Bliek, L. (author), Al-Dujaili, Abdullah (author), O’Reilly, Una-May (author)
Training classifiers that are robust against adversarially modified examples is becoming increasingly important in practice. In the field of malware detection, adversaries modify malicious binary files to seem benign while preserving their malicious behavior. We report on the results of a recently held robust malware detection challenge. There...
conference paper 2020
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Wijnands, K.J. (author)
In the last years the impact of malware has become a huge problem. Each year, more and more new malware samples are discovered [2]. And the malware is becoming more sophisticated, for example ransomware. Ransomware encrypts personal documents, such as photos and word documents, and asks money to be able to decrypt these files, hence the name....
master thesis 2015
Searched for: subject%3A%22malware%255C+detection%22
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