Internship | Mitigation of inversion attacks in Federated Learning
4 weken geleden
About this position
Federated learning (FL) is a hot research topic enabling training on databases of multiple organizations while preserving the privacy of people whose personal data is stored in the databases. FL supports sharing of deep learning (DL) models between the different organizations during the training process without sharing personal data. Training the DL models in a federated way can significantly boost the performance since you indirectly have access to more data. Initially, it was assumed that it is safe to share DL models between multiple organizations, but research has shown that the original data used for training can be recovered from them, which is called an inversion attack. The aim of the project is to explore the vulnerabilities of the current state-of-the-art algorithms for FL in terms of inversion attacks.
What will be your role?
Your role will be to enhance privacy by exploring vulnerabilities related to inversion attacks and – when possible – mitigate these vulnerabilities. The activities include performing a literature study to understand the current state-of-the-art, finding the weaknesses of current solutions, proposing a new solution, implementing the solution, performing experiments to show that the solution is better than the current state-of-the-art, writing a master thesis, and optionally a scientific paper.
You will perform this assignment within TNO’s Intelligent Imaging department. The Intelligent Imaging department is a passionate, creative, and dedicated team of professionals (50 people) specialized in developing groundbreaking applications in the field of computer vision. Our team members have diverse backgrounds, ranging from physics to artificial intelligence. Intelligent Imaging is a young and growing department which has built up a lot of expertise over the past years in AI and deep learning.
Keywords for this project include: Artificial Intelligence, Privacy, Deep Learning, Federated Learning.
What we expect from you
You are in the final stages of your master's in artificial intelligence, computer science, physics, mathematics, electrical engineering, or a similar field. You have some experience in computer vision, artificial intelligence, deep learning and Python programming.
The duration of the graduation project or internship is 6 to 9 months. Please mention in your application whether you are looking for an internship or a graduation project, the preferred duration of your project and your desired starting date.
What you'll get in return
You want to work on the precursor of your career; a work placement gives you an opportunity to take a good look at your prospective future employer. TNO goes a step further. It’s not just looking that interests us; you and your knowledge are essential to our innovation. That’s why we attach a great deal of value to your personal and professional development. You will, of course, be properly supervised during your work placement and be given the scope for you to get the best out of yourself. Furthermore, we provide:
A highly professional, innovative working environment, with top experts as colleagues. A suitable internship allowance ( euro for wo- and hbo-students, euro for mbo-students, for a full-time internship). Eight hours of leave per internship month (for a full-time internship). A free membership of , where you can meet TNO-colleagues and join , such as sports activities, (work-related) courses or the yearly ski-trip. Use of a laptop. An allowance for travel expenses in case you don’t receive an OV-card.-
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