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Artificial intelligence and deep learning have transformed computer vision and image analysis, especially in critical areas like defence, safety, and security. However, the increasing prevalence of adversarial AI attacks, such as gradient attacks, poses significant challenges to the robustness and reliability of these technologies. This project aims to explore both the techniques used for adversarial attacks in object detection and innovative methods to detect and counteract these threats. Specifically, we will focus on investigating methods to identify unusual patterns or anomalies that may indicate adversarial attacks, as well as developing techniques to enhance the robustness of AI algorithms, making them more resistant to such attacks.
This project is part of ongoing research at TNO, where you will be fully integrated into our research group. You will start by reviewing recent literature to identify current methods for adversarial attacks for object detection and technologies to detect and counter these attacks. We have relevant datasets of military vehicles, including annotated images and videos, available for this project. You will use these datasets to perform various adversarial attacks and evaluate different detection and countermeasure techniques, with a specific focus on anomaly/novelty detection approaches.
Depending on your interests and the time available for your thesis project, we will also explore methods to train AI technology to be robust against adversarial attacks, potentially reducing the need for detection and countermeasures. We encourage your initiative and welcome suggestions for new research directions related to this topic.
The project will conclude with a written report of your findings and recommendations, with the possibility of conference or journal publication. You will also present your results and propose future research directions.
We are looking for a highly motivated MSc student with interest in computer vision, image analysis, and artificial intelligence technology. Ideally, you have a technical background and are, e.g., studying computer sciences, artificial intelligence, mathematics, physics, (bio)medical engineering, or a related field. Prior experience with computer vision, image analysis, programming (Python), artificial intelligence / deep learning is appreciated.
Your supervision team will consist of two experienced TNO-colleagues who are actively involved in ongoing research projects at TNO. They have experience both in state-of-the-art computer vision, image analysis, and artificial intelligence research, as well as supervising BSc/MSc/PhD students in internships and graduate projects.
Please include the following practical information in your cover letter:
You want an internship opportunity on the precursor of your career; an internship 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:
At TNO, we innovate for a healthier, safer and more sustainable life. And for a strong economy. Since 1932, we have been making knowledge and technology available for the common good. We find each other in wonder and ingenuity. We are driven to push boundaries. There is all the space and support for your talent and ambition. You work with people who will challenge you: who inspire you and want to learn from you. Our state-of-the-art facilities are there to realize your vision. What you do at TNO matters: impact makes the difference. Because with every innovation you contribute to tomorrow’s world.
At TNO we encourage an inclusive work environment, where you can be yourself. Whatever your story and whatever unique qualities you bring to the table. It is by combining our unique strengths and perspectives that we are able to develop innovations that make a real difference in society.
Innovation with purpose: that is what TNO stands for. We develop knowledge not for its own sake, but for practical application. TNO connects people and knowledge to create innovations that boost the competitive strength of industry and the well-being of society in a sustainable way.
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