This paper introduces a new reservoir computing approach, called Conceptor-Driven Network (ConDN), for the detection of chaos in time-series. Two known parametrizable systems exhibiting chaotic and non-chaotic behaviours have been analysed. By only observing the selected output results (trace matrix) after training the ConDN, the systems can be classified as chaotic or non-chaotic. In addition, the robustness of this method against white noise is also investigated. Index Terms-reservoir computing (RC), Conceptor-Driven RC, complex dynamics, detection of chaos, noise robustness.