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Hybrid Framework for Integrated Malware Analysis to Detect Advanced Persistent Threat
http://hdl.handle.net/20.500.12678/0000004663
http://hdl.handle.net/20.500.12678/0000004663f676f876-0d72-4899-8182-6ddb4223185c
ae5ff1f5-9958-4233-91cd-4c71370bbbb1
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201643.pdf (132 Kb)
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Article | ||||||
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Title | ||||||
Title | Hybrid Framework for Integrated Malware Analysis to Detect Advanced Persistent Threat | |||||
Language | en | |||||
Publication date | 2016-02-25 | |||||
Authors | ||||||
Thwin, Thein Than | ||||||
Thwin, Mie Mie Su | ||||||
Description | ||||||
The term Advanced Persistent Threat (APT)is used as a replacement term for cyber warfareand malware has developed into the majorvehicle for APT. Malware analysis and detectionis a major resource in maintaining anorganization’s antivirus preparedness andresponsiveness by contributing to the well-beingof its IT health, and consequently to that of theeconomy as a whole. There is a need to developan automatic malware detection andclassification system to identify the variants ofmalware, in order to guide analysts in theselection of samples that require the mostattention. In this paper, we introduce HybridFramework for our ongoing research, IntegratedMalware Analysis to Detect Advanced PersistentThreat (APT). In our framework we integratedthe static and dynamic malware analysis as wellas K-mean clustering and Bayesianclassification approaches. | ||||||
Keywords | ||||||
Malware Analysis, Malware, Malware Classification, Malware Clustering | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/318 | |||||
Journal articles | ||||||
Fourteenth International Conference On Computer Applications (ICCA 2016) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |