Visualizing Automatically Detected Periodic Network Activity

Malware frequently leaves periodic signals in network logs, but these signals are easily drowned out by non-malicious periodic network activity, such as software updates and other polling activity. This paper describes a novel algorithm based on Discrete Fourier Transforms capable of detecting multi...

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Veröffentlicht in:	IEEE Symposium on Visualization for Cyber Security (VIZSEC) (Online) S. 1 - 8
Hauptverfasser:	Gove, Robert, Deason, Lauren
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.10.2018
Schlagworte:	Data visualization Discrete Fourier transforms Human-centered computing-Visualization-Visualization application domains-Information visualization Human-centered computing-Visualization-Visualization design and evaluation methods Malware Microsoft Windows Security and privacy-Intrusion/anomaly detection and malware mitigation-Malware and its mitigation Time series analysis Time-frequency analysis
ISSN:	2639-4332
Online-Zugang:	Volltext
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