Visualizing malware programs as images and feeding them into artificial intelligence helps to find patterns in computer malware that might have taken years for humans to identify, according to an article published by two University of North Georgia (UNG) computer science faculty members and a recent graduate.
Dr. Sara Sartoli, an assistant professor, and Dr. Yong Wei, a professor, published the article with recent UNG graduate Shane Hampton. They will present the paper virtually at the IEEE International Conference on Machine Learning and Applications, set for Dec. 14-17.
"Recent industry reports show organizations are increasing their investments in artificial-intelligence-based solutions to fight cyber-attacks," Sartoli said. "And they agree that one of the biggest benefits is to process the large amount of data points quickly."
Wei said artificial intelligence can learn and recognize the deep characteristics of threats "lightning fast" with unprecedented precision. Through this process, the malware software is converted to images that are used to determine patterns.
Sartoli and Wei noted the technology will not replace the people doing the work but will provide a useful tool for them.
Sartoli and Wei appreciate the importance of involving undergraduate students in research.
"Doing research energizes and enriches the classes we teach," Wei said.
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October 28, 2020 at 09:47PM
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Faculty and graduate publish article on machine learning - News at UNG
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