10-17, 17:15–17:35 (Europe/Luxembourg), Salle Europe
Crowdsec is building the largest CTI, crowdsourced by an open source security engine solution. With the help of machine learning algorithms, we analyze this data to detect and classify cyber threats in near real time.
Over the past years CTI has evolved from a simple blocklist to a more end-to-end approach.
Learn about the crowdsourced approach to achieving this CTI thanks to using an open-source security engine that detects & blocks more than 150 behaviors across a network of 60k nodes spread all over the globe, ensuring that the CTI system is continually updated with the latest information & can respond quickly to new threats. You will also get insights on the data that builds this next-generation CTI & see examples of DDOS events, CVEs blocked, & a description of malicious actors reported on the Internet.
To conclude you will get insights of machine learning applications to classify IP addresses based on their behavior.
I am passionate about analyzing large datasets to solve complex problems. If data are unique, it’s an even higher source of motivation. I joined CrowdSec in September 2021 to make sense of the datalake and add machine learning to the solution.
My background is mostly applied mathematics and machine learning, which I gained studying in Paris-Dauphine University and Ecole Normale Supérieure de Cachan.
Prior CrowdSec, I experienced 4 years working in a Satellite images company as a Data Scientist, where I contributed to major research projects related to methane emissions mitigation.
Outside working hours you will most likely see me bouldering or hiking outdoor.