Belma has been working at TNO for less than a year and there is already a key network function of TNO’s own 5G test environment named after her: the ‘Belma UPF’. It’s a compliment from her colleagues for her contribution to developing it.
Network technologies of the future
‘I’m a junior scientist innovator in the Networks research group, where we experiment with the network technologies of the future. Programmable networks are my specialism, especially 5G.’
‘My first project was to improve the performance of the 5G core network of our Hi-5 platform. This is our own mobile test bed, which we use for our experiments. We wanted to improve the user plane function (UPF) and we were successful, making it some 30 to 60 times faster.
The UPF is now called the Belma UPF – a real honour, particularly as other organisations will also be able to use it. That’s the great thing about TNO: what we develop here is really put to use. A lot of scientific research is futuristic. It’s clever stuff and it needs to be done, but the question is often whether this or that innovation will actually be applied.’
‘I wanted to know how the internet works and after studying Electrical Engineering, I went to work for a telecom company, but I was soon bored there. Once I’d understood how the technology worked, there wasn’t much more to learn. So, I went back to do a PhD and that’s why I’m now working for TNO. Here, everything is new every day and everything you do is a challenge.’
‘I’ve been working here for less than a year and I’ve already done so many projects. Including in areas that are still unknown territory for me, such as cloud computing. Colleagues who have more experience of this subject are very helpful. I learn a lot from pair programming with colleagues and from just trying things out. TNO employees really take the time if they want to show you something new. They have patience and understanding. They always like to show what they’re working on.’
Using AI to detect malware
‘A great example is how, together, we found ways of detecting malware in networks with the help of AI. Experimenting with this in our research cloud was tricky, because of course you don’t want to jeopardise other research projects that make use of it.
We found a solution with an automated approach that ensures only approved communication can leave the test network, with several levels of security to block unplanned malware communication. In this way, we can test our malware detection with a single click, without running the risk of infecting the whole TNO network.’
‘I really enjoy working in Networks and I think it’s still too early to consider my next step. As long as I can learn new things every day and really work on research, this is the place for me. I’ll soon be hearing whether a project that I’m very keen on will get the go-ahead. Then a new adventure will begin.’