Elephant Herd Optimization with Weighted Extreme Learning Machine based PDF Malware Detection and Classification Model

Elephant Herd Optimization with Weighted Extreme Learning Machine based PDF Malware Detection and Classification Model

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© 2022 by IJETT Journal
Volume-70 Issue-8
Year of Publication : 2022
Authors : P. Pandi Chandran, Hema Rajini. N, M. Jeyakarthic
DOI : 10.14445/22315381/IJETT-V70I8P222

How to Cite?

P. Pandi Chandran, Hema Rajini. N, M. Jeyakarthic, "Elephant Herd Optimization with Weighted Extreme Learning Machine based PDF Malware Detection and Classification Model," International Journal of Engineering Trends and Technology, vol. 70, no. 8, pp. 216-223, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I8P222

Abstract
Portable Document Format (PDF) is widely utilized for document exchange and distribution because of its high portability and universal usage. Benign users and attackers leverage the format's adaptable and flexible nature to utilize different vulnerabilities, overcome security limitations, and then convert the PDF format into one of the foremost malicious code spread vectors. Investigation of the content in the malicious PDF for extracting major features plays a vital role in the automated identification of new attacks. This study develops an Elephant Herd Optimization with Weighted Extreme Learning Machine (EHO-WELM) based PDF malware detection and classification model. The presented EHO-WELM model mainly aims to determine the existence of PDF malware. For attaining this, the EHO-WELM model pre-processes in two ways: categorical encoding and null value removal. In addition, the pre-processed data are passed into the WELM model to identify and classify PDF Malware. For determining the weight values of the WELM model, the EHO algorithm is applied to improve the classifier efficacy, showing the work's novelty. The simulation analysis of the EHO-WELM model on the benchmark dataset implied superior outcomes over the existing approaches.

Keywords
Malware detection, Weighted extreme learning machine, PDF Malware, Elephant herd optimization, Parameter tuning.

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