Charlie Obimbo

Dr. Charlie Obimbo is a Professor at the University of Guelph specializing in Computer Systems Security. His research focuses on Intrusion Detection & Prevention Systems, leveraging advanced AI methods like

• Support Vector Machines
• Deep Learning
• k-nearest Neighbors

for network payload classification. He also investigates Data Encryption, Cryptanalysis, and Differential Privacy to address modern cybersecurity challenges involving mobile device security and privacy preservation in large datasets.

Recent research trends highlight his work in

• Enhancing classifier accuracy-interpretability trade-offs
• Developing privacy-preserving algorithms for medical data
• Securing web applications against XSS attacks

His publications span top conferences like IEEE Canada International Humanitarian Technology Conference and journals such as International Journal of Advanced Computer Science and Applications.

Dr. Obimbo's work bridges critical cybersecurity issues including:

• Malicious payload detection
• Backdoor prevention
• Statistical privacy mechanisms
• Economic impacts of cyber threats