Application of Hybrid Machine Learning to Detect and Remove Malware
Journal Title: Transactions on Machine Learning and Artificial Intelligence - Year 2015, Vol 3, Issue 4
Abstract
Anti-malware software traditionally employ methods of signature-based and heuristic-based detection. These detection systems need to be manually updated with new behaviors to detect new, unknown, or adapted malware. Our goal is to create a new malware detection solution that will serve three purposes: to automatically identify and classify unknown files on a spectrum of malware severity; to introduce a hybrid machine learning approach to detect modified malware traces; and to increase the accuracy of detection results. Our solution is accomplished through the use of data mining and machine learning concepts and algorithms. We perform two types of data mining on samples, extracting n-grams and PE features that are used for our machine learning environment. We also introduce a new hybrid learning approach that utilizes both supervised and unsupervised machine learning in a two-layer protocol. A supervised algorithm is applied to classify if a file is considered malware or benign. The files classified as malware will then be categorized and then assigned on a severity spectrum using the SOFM unsupervised algorithm.
Authors and Affiliations
Richard R. Yang, Victor Kang, Sami Albouq, Mohamed Zohdy
Keywords
Related Articles
- EP ID EP278831
- DOI 10.14738/tmlai.34.1436
- Views 58
- Downloads 0
Learning Style Classification Based on Student's Behavior in Moodle Learning Management System
In learning field, each student has his own learning style that affects his way of get, process, understand and percept information. Determining the learning style of students enhances the performance of learning process...
Detection of the Onset of Diabetes Mellitus by Bayesian Classifier Based Medical Expert System
Expert systems play an important role in medical diagnosis research. Researches are still being conducted for building expert systems capable of diagnosing different diseases. Diabetes mellitus is one of the diseases tha...
Implementation of Yorùbá Language Multimedia Learning System
The use of multimedia learning system has been widely accepted as a useful and effective tool in the field of human language. Many students and researchers have examined multimedia learning�s effectiveness from a number...
A Novel Approach to Compute Confusion Matrix for Classification of n-Class Attributes with Feature Selection
Confusion matrix is a useful tool to measure the performance of classifiers in their ability to classify multi-classed objects. Computation of classification accuracy for 2-classed attributes using confusion matrix is ra...
Hello Message Scheme Enhancement in MANET based on Neighbor Mobility
The key idea behind the routing protocols based in multi hope is to find the required path from the source node to the destination. Since those protocols does not consider the node mobility in their mechanism, we propose...