Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Physical Sciences and Mathematics
Malware Image Classification Using Machine Learning With Local Binary Pattern, Jhu-Sin Luo, Dan Lo
Malware Image Classification Using Machine Learning With Local Binary Pattern, Jhu-Sin Luo, Dan Lo
Master of Science in Computer Science Theses
Malware classification is a critical part in the cybersecurity.
Traditional methodologies for the malware classification
typically use static analysis and dynamic analysis to identify malware.
In this paper, a malware classification methodology based
on its binary image and extracting local binary pattern (LBP)
features are proposed. First, malware images are reorganized into
3 by 3 grids which is mainly used to extract LBP feature. Second,
the LBP is implemented on the malware images to extract features
in that it is useful in pattern or texture classification. Finally,
Tensorflow, a library for machine learning, is applied to classify
malware images with …
A Multiple Classifier System For Predicting Best-Selling Amazon Products, Michael Kranzlein
A Multiple Classifier System For Predicting Best-Selling Amazon Products, Michael Kranzlein
Master of Science in Computer Science Theses
In this work, I examine a dataset of Amazon product metadata and propose a heterogeneous multiple classifier system for the task of identifying best-selling products in multiple categories. This system of classifiers consumes the product description and the featured product image as input and feeds them through binary classifiers of the following types: Convolutional Neural Network, Na¨ıve Bayes, Random Forest, Ridge Regression, and Support Vector Machine. While each individual model is largely successful in identifying best-selling products from non best-selling products and from worst-selling products, the multiple classifier system is shown to be stronger than any individual model in the …