| Autors: Nenov, L., Kassev, K. M., Chanev, D. Title: Investigation of algorithms for virus detection using neural networks and machine learning Keywords: Training, Analytical models, Machine learning algorithms, Ne Abstract: The aim of the project is to study, analyze and research different models of algorithms for neural network training and the application of machine learning. The main goal is to offer a solution that detects malicious files in a large set of data by evaluating each of them. The algorithms are considered Gradient Boosting Classifier, Random Forest Classifier, also, in the proposed appropriate solutions to this problem, neural networks with „deep learning”, as well as techniques from hidden Markov model. They are often a good solution for detecting and classifying malware. References Issue
Copyright IEEE |
Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus
