Network traffic classification is an active research field that acts as an enabler for various applications in network management and cybersecurity. Numerous studies from this field have targeted the case of classifying network traffic into a set of single-activities (e.g., chatting, streaming). However, the proliferation of internet services and devices has led to the emergence of new consuming patterns such as multi-tasking that consists in performing several activities simultaneously. Recognizing the occurrence of such multi-activity situations may help service providers to design quality of service solutions that better fit users’ requirements. In this paper, we propose a framework that is able to recognize multi-activity situations based on network traces. Our experiments showed that our solution is able to achieve promising results despite the complexity of the task that we target. Indeed, the obtained multi-activity detection performance is equivalent or often surpasses state-of-the-art techniques dealing with only a single activity.