Making ML attack resilient
Machine Learning are not robust against adversarial attacks. We conducted approaches to improve that.
About expert
A Machine Learning at Fraunhofer.
Peter applied their knowledge of Development in AI on the following markets: Germany.
Peter built products like Adversarial Machine Learning using the variety of tools.
Similar cases
Setting up efficient customer support
Organized pre-launch product UX testing, regular users research and new features backlog prioritization
Organized the company's participation in high-profile contests, resulting in Nimb becoming a winner of Smart City Expo worldwide Congress’s call for solution in the “Safe Cities” category and a finalist of Xprize Women’s Safety competition
Set up efficient client support
Enhancing Analytical Infrastructure and Reducing Fraudulent Activities
Led the shift of analytical infrastructure, enhancing data resources and decreasing update errors by 90%. Increased identifiable traffic sources from 60% to 95%. Played a crucial role in reducing fraudulent responses from 28% to 1-4% by strengthening moderation and creating a fraud analytics direction. Contributed to a project reducing the cost of applications from groups by 70% and reducing vacancies in central Moscow from 20% to 6%.
