The integration of distributed energy resources (DERs) into distribution systems greatly increases the system complexity and introduces two-way power flows. Conventional protection schemes are based upon local measurements and simple linear system models, thus they cannot handle the new complexity and power flow patterns in systems with high DERs penetration. In this paper, we propose a data-driven protection framework to address the challenges induced by DERs. Considering the limited available data under fault conditions, we adopt the support vector data description (SVDD) method, a commonly used one-class classifier, for distribution system fault detection. The proposed method is tested under the IEEE 123-node test feeder and simulation results show that our proposed SVDD-based fault detection method significantly improves the robustness and resilience against DERs in comparison with conventional protection systems.