Research
In my research, I tend to employ machine learning (ML) and evolutionary algorithms (EA) for cloud monitoring and anomaly detection in IaaS.
Specifically, I conduct research in the following topics:
- Computer Systems Security
- Anomaly and Malware Detection
- Cloud Computing Security and Monitoring
- Applied Machine Learning
- Cyber Physical Systems
Publications
Please visit my scholar profile at:
Google Scholar
Conference Papers
- Mahmoud Abdelsalam, Ram Krishnan, and Ravi Sandhu, "Online Malware Detection in Cloud Auto-Scaling Systems Using Shallow Convolutional Neural Networks" In Proceedings 31st Annual IFIP WG 11.3 Working Conference on Data and Applications Security and Privacy (DBSec), Charleston, SC, July 15-17, 2019. Presentation (pdf)
- Mahmoud Abdelsalam, Ram Krishnan, Yufei Huang and Ravi Sandhu, "Malware Detection in Cloud Infrastructures using Convolutional Neural Networks" In Proceedings 11th IEEE International Conference on Cloud Computing (CLOUD), San Francisco, CA, USA, July 2-7, 2018, 8 pages. Presentation (pdf)
- Mahmoud Abdelsalam, Ram Krishnan and Ravi Sandhu, "Clustering-Based IaaS Cloud Monitoring" In Proceedings 10th IEEE International Conference on Cloud Computing (CLOUD), Honolulu, Hawaii, USA, June 25-30, 2017, 8 pages. Presentation (pdf)
Ph.D. Thesis
Mahmoud Abdelsalam, "Online Malware Detection in Cloud Auto-Scaling Systems using Performance Metrics", PhD dissertation, department of Computer Science, University of Texas at San Antonio. 2018.
Research Projects
CloudEye
An open-source security monitoring system for anomaly detection in the cloud.
CloudEye is a cloud monitoring service for VMs using machine learning. It uses OpenStack Ceilometer as a data poller.
http-traffic-gen
An open-source HTTP traffic generator that can generate poisson and on/off pareto traffic.