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MATRIX AI: Online Malware Detection in Cloud Auto-Scaling Systems

September 18 @ 11:00 am - 12:00 pm CDT

Online Malware Detection in Cloud Auto-Scaling Systems

Ram Krishnan, Ph.D., Department of Electrical and Computer Engineering, UTSA

Friday, September 18, 2020, 11 AM -12 PM CST

Meeting Link: bit.ly/MATRIXFallSeminarSeries

Abstract: Cloud computing is becoming increasingly popular among organizations. The Infrastructure as a Service (IaaS) cloud computing model has become an attractive solution because of its ability to reduce costs and improve resource utilization. Cloud ecosystems have also become attractive targets to attackers because of the massive amount of data residing on the cloud as well as the massive processing power that could be recruited for malicious intent. Thus, security is a critical task in cloud ecosystems and continuous security monitoring in the cloud is imperative for detecting malicious activities.

This talk discusses the problem of online malware detection in cloud systems using machine learning. We find that current malware detection techniques that target VMs lack taking advantage of unique cloud characteristics such as auto-scaling. That is, those techniques could be applied to VMs as well as stand-alone servers with nothing specific about cloud. We explore how cloud characteristics such as auto-scaling could be leveraged for effective malware detection and response. We utilize black-box and white-box metrics of various cloud resources to model benign and malicious cloud behavior. We conclude by exploring how an integrated and automated cyber threat detection, sharing and response could be designed for cloud computing systems.

Web: ai.utsa.edu
Twitter: twitter.com/ai_utsa
YouTube: bit.ly/MATRIXonYouTube
Launch Event Archive: bit.ly/MATRIXLaunch


September 18
11:00 am - 12:00 pm