SPS Webinar: PhishSim: Aiding Phishing Website Detection With a Feature-Free Tool
Date: 16 October 2024
Time: 9:30 AM ET (New York Time)
Presenter(s): Dr. Rizka Widyarini Purwanto
Based on the IEEE Xplore® article:
PhishSim: Aiding Phishing Website Detection With a Feature-Free Tool, published in the IEEE Transactions on Information Forensics and Security, April 2022.
Download article: Original article is open access, and publicly available to all for download.
Abstract
In this presentation, the presenter will explore PhishSim, a cutting-edge tool designed to enhance phishing detection by utilizing a feature-free method. Traditional phishing detection methods often rely on specific website features, which can become outdated as phishing techniques evolve. PhishSim addresses this challenge by employing the Normalized Compression Distance (NCD), a parameter-free similarity measure that eliminates the need for feature extraction. The tool examines the HTML content of webpages, comparing them to known phishing sites to accurately classify new threats. Additionally, they will discuss the implementation of an incremental learning algorithm, allowing PhishSim to continuously adapt to new phishing strategies without the need to re-extract features. This presentation will highlight PhishSim’s effectiveness, demonstrated by its high accuracy and low false positive rate, making it a robust solution for real-world deployment in information security. Attendees will gain insights into how this innovative approach can be integrated into existing security frameworks to better protect against evolving phishing threats.
Biography
Dr. Rizka Widyarini Purwanto received the B.S. degree in electrical engineering from Institut Teknologi Bandung, Indonesia, in 2013, the M.S. degree, concentrating on artificial intelligence and internetworking, and the Ph.D. degree from the School of Computer Science and Engineering, both at the University of New South Wales (UNSW) in 2018 and 2022 respectively. Her Ph.D. was funded by the University International Postgraduate Award (UIPA) and Cyber Security Cooperative Research Centre scholarships.
She is currently an Assistant Professor to the Master of Cybersecurity with Monash University, Indonesia and Adjunct Associate Lecturer at University of New South Wales. Prior to this role, she was a postdoctoral researcher at UNSW Canberra Space, with past experiences working as a software engineer in Australia and Indonesia.
Dr. Purwanto research interests are mainly in the application of artificial intelligence in various areas. Her current research interests include scams and phishing attacks, specifically on improving cybersecurity awareness, and developing AI based methods that could automatically help detect phishing attacks and scams. Besides AI for cybersecurity, she is also currently working in the area of AI for space, particularly on the use of federated learning on miniaturized satellite constellations, and space object characterization.
