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Joyatee Datta - Detecting VPN Traffic: Techniques and Insights from Traffic Analysis

Abstract

In an increasingly restrictive internet landscape, Virtual Private Networks (VPNs) play an important role in ensuring secure and unrestricted access to the web, however, at the same time, detecting VPN traffic has become a significantly crucial focus for organizations. In my talk, I will explore various methods usually used to identify VPN traffic, such as deep packet inspection (DPI) and traffic flow analysis. Based on my research, I will provide a brief overview of traffic analysis and censorship systems, offering some insights into the evolving techniques used to detect and block VPNs.

Biography

I’m Joyatee Datta, currently a Master’s student specializing in Cybersecurity at Radboud University with a Bachelor’s in Computer Science and Engineering from India. My research interests span computer networks, wireless technologies, and web application security. I have actively contributed to various research projects, including work on secure code analysis, web application security, and network security. My passion lies in working on digital security and tackling real-world challenges. I have published several papers in the field of cybersecurity, including research on autonomous driving, real-time threat detection using unsupervised learning, and technologies used to combat COVID-19. Outside of my studies, I enjoy exploring new countries, playing chess and badminton, and I’m also a classical dancer.

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Directe link naar video indien video niet of niet volledig werkt (b.v. geen audio): Joyatee Datta - Detecting VPN Traffic: Techniques and Insights from Traffic Analysis