Rizka Widyarini Purwanto
Rizka 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.
Her 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 miniaturised satellite constellations, and space object characterisation using lightcurve data with deep learning.
Rizka received the bachelor’s degree in electrical engineering from Institut Teknologi Bandung (ITB), Indonesia, in 2013, and the master’s degree from the University of New South Wales (UNSW) in 2018, concentrating on artificial intelligence and internetworking. She completed her PhD in 2022, from the School of Computer Science and Engineering at UNSW. Her PhD was funded by the University International Postgraduate Award (UIPA) and Cyber Security Cooperative Research Centre scholarships.
More information
Selected Policy Publications
Deep Learning based Space Object Identification using Light Curve Data.
Rizka Purwanto, Christopher Capon, Komal Gupta, Melrose Brown, Australian Space Research Conference (ASRC) 2022 Formation Flying and Change Detection for the UNSW Canberra Space ‘M2’ Low Earth Orbit Formation Flying CubeSat Mission, https://www.nssa.com.au/20asrc/resources/20ASRC-A5-program-190922.pdf
Formation Flying and Change Detection for the UNSW Canberra Space ‘M2’ Low Earth Orbit Formation Flying CubeSat Mission.
Melrose Brown, Russell Boyce, Andrew Lambert, Edwin G. W. Peters, Steve Gehly, Samuel Boland, Ryan Jefferson, Anthony Kremor, Timothy Bateman, Chris Capon, Brenton Smith, George Bowden, Lauren Glina, Lily Qiao, Sudantha Balage, Komal Gupta, Rizka Purwanto, Travis Bessell, Tom Reddell, James Bennett, Michael Lachut, Tim McLaughlin, Advanced Maui Optical and Space Surveillance Technologies Conference (AMOS) 2022 https://amostech.com/TechnicalPapers/2022/Space-Based-Assets/Brown.pdf
PhishSim: Aiding Phishing Website Detection with a Feature-Free Tool, Rizka Purwanto, Arindam Pal, Alan Blair, Sanjay Jha, IEEE Transactions on Information Forensics & Security 2022, https://ieeexplore.ieee.org/document/9745933/
Man versus Machine: AutoML and Human Experts' Role in Phishing Detection, Rizka Purwanto, Arindam Pal, Alan Blair, Sanjay Jha, arXiv preprint arXiv:2108.12193, 2021, https://arxiv.org/abs/2108.12193
PhishZip: A New Compression-based Algorithm for Detecting Phishing Websites, Rizka Purwanto, Arindam Pal, Alan Blair, Sanjay Jha, IEEE Conference on Communications and Network Security 2020
https://ieeexplore.ieee.org/document/9162211, Doing and Feeling: Relationships Between Moods, Productivity and Task-switching, Muhammad Johan Alibasa, Rizka Purwanto, Kalina Yacef, Nick Glozier, Rafael Calvo, IEEE Transactions on Affective Computing 2020, https://ieeexplore.ieee.org/document/9216577
Check Rizka Purwanto’s other publications and research output here and Google Scholar.
Teaching:
- ITI5003 Software Security
- ITI5163 Information and Computer Security
- ITI9130 System Analysis and Design
Research:
- AI for space
- Phishing detection
- Social engineering
- Three Monash AI Researchers named finalists for the Women in AI Awards 2023 APAC – Monash University
- 2023 Women in AI awards finalists revealed – Digital Nation
- Women in AI finalists announced – Technology Decisions
- Women in AI APAC 2023 finalists announced – Manufacturers’ Monthly
- Women of the Australian Space Community - Space Australia
- This new phishing detection system can decode fraudsters - Data61 Algorithm
- PhishZip: A New Compression-based Algorithm for Detecting Phishing Websites - CSIRO
- Detecting phishing websites via compression-based algorithms - APNIC
- Data61 touts new way to automatically spot phishing attempts - ITNews
- PhishZip was listed in Global Australia’s AI case studies:
- “CSIRO and the University of New South Wales designed PhishZip, an algorithm that uses file compression to systematically assess and exclude harmful phishing websites.”
- Winner of the AI in Space - WAI (Women in AI) Award 2023 Asia Pacific, 2023
- University International Postgraduate Award Recipient, University of New South Wales, 2018