Please view the posters presented at the 18th Annual CityTech Faculty and Student Research Poster Session below. You can click on each poster to enlarge it and view the PDF version under the poster abstract.
We thank all presenters for sharing their innovative and informative research with the CityTech community and beyond!
12. Comparing Performance of Malware Classification onAutomated Stacking
Stacking in machine learning allows multiple classification or regression algorithms to work together with a goal to enhance performance. To understand the risky properties of malware contamination in a system, it is important to accurately classify malware type first. Malware classification is the procedure of labeling the families of malware. In this work, we automate stacking with 7 machine learning algorithms and 3 boosting algorithms. The experimental results show a 99.2% accuracy is achieved from a multilayer perceptron network with AdaBoost classifier, which outperforms other models on the malware API call dataset. View or download a PDF version of this poster.
