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Title: Study of incremental fuzzy clustering for malware analysis
Authors: Li, Xinyi.
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2013
Abstract: Internet is playing a important role in modern lifestyle. On the other hand, it brings the problem of cyber security. Malicious software, also known as Malware, is a major threat to cyber security. One malware may have large amount and various types of variants. It takes human analysts some time to respond using classic static analysis technique. Therefore dynamic malware analysis techniques are proposed to improve the efficiency of identifying new unknown malware and variants of known malware. In this project, three clustering algorithms based on Fuzzy C-means are implemented and applied in malware data analysis. They are proved to be work well on medium size dataset with multi-attributes. For large dataset such as malware datasets, they cannot function as expected. Only two out of three new algorithms implemented can be successfully applied for handling malware datasets.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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