The ELSA Cybersecurity use case team is exited to announce a new challenge!
The “Robust Android Malware Detection Competition, hosted by IEEE SaTML 2025“, aims to evaluate ML-based detectors concerning
- Adversarial Robustness to Feature-space Attacks
- Adversarial Robustness to Problem-space Attacks
- Temporal Robustness to Data Drift
The participants must train their models on the challenge dataset, evaluate them with the provided code, and submit the results. They can access all necessary information and datasets via our benchmarks platform.
Join the Challenge
Here’s how to get started:
- register via the ELSA benchmarks platform
- read the competition rules and instructions
- download the datasets and store them in the
datafolder - implement your detector
- run the provided code
- submit your results
Key Dates:
- now: all competition tracks are open
- March 31st: submission deadline
The Cybersecurity use case is excited for your submissions.
About IEEE SaTML 2025
“The 3rd IEEE Conference on Secure and Trustworthy Machine Learning (IEEE SaTML 2025) will expand on the theoretical and practical understandings of vulnerabilities inherent to machine learning (ML), explore the robustness of learning algorithms and systems, and aid in developing a unified, coherent scientific community which aims to establish trustworthy machine learning. IEEE SaTML will be hosted on the campus of the University of Copenhagen on April 9-11, 2025. The venue for the conference will be the Lundbeckfond Auditorium.” – (source: IEEE SaTML website, February 14th, 2025)
