A fast malware feature selection approach using a hybrid of multi-linear and stepwise binary logistic regression

Shamsul Huda; Jemal Abawajy; Mali Abdollahian; MD Rafiqul Islam; John Yearwood

doi:10.1002/cpe.3912

A fast malware feature selection approach using a hybrid of multi-linear and stepwise binary logistic regression

Shamsul Huda, Jemal Abawajy, Mali Abdollahian, MD Rafiqul Islam, John Yearwood

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

8 Downloads (Pure)

Original language	English
Article number	e3912
Pages (from-to)	1-18
Number of pages	18
Journal	Concurrency and Computation: Practice and Experience
Volume	29
Issue number	23
Early online date	10 Aug 2016
DOIs	https://doi.org/10.1002/cpe.3912
Publication status	Published - 10 Dec 2017

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10.1002/cpe.3912

Cite this

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title = "A fast malware feature selection approach using a hybrid of multi-linear and stepwise binary logistic regression",

keywords = "Malware detection, Binary logistic regression, Stepwise regression, API call statistics, AIC criteria, Chi-square",

author = "Shamsul Huda and Jemal Abawajy and Mali Abdollahian and Islam, {MD Rafiqul} and John Yearwood",

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AU - Abdollahian, Mali

AU - Islam, MD Rafiqul

AU - Yearwood, John

N1 - Includes bibliographical references.

PY - 2017/12/10

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KW - Malware detection

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KW - Stepwise regression

KW - API call statistics

KW - AIC criteria

KW - Chi-square

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M3 - Article

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M1 - e3912

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