Disruptive network scenarios with ad hoc, intermittent connectivity and mobility create unique challenges to supporting distributed applications. In this paper, we propose Distributed Dataset Synchronization over disruptive Networks (DDSN), a protocol which provides resilient multi-party communication in adverse communication environments. DDSN is designed to work on top of the Named-Data Networking protocol and utilizes semantically named, and secured, packets to achieve distributed dataset synchronization through an asynchronous communication model. A unique design feature of DDSN is letting individual entities exchange their dataset states directly, instead of using some compressed form of the states. We have implemented a DDSN prototype and evaluated its performance through simulation experimentation under various packet loss rates. Our results show that, compared to an epidemic routing based data dissemination solution, DDSN achieves 33-56% lower data retrieval delays and 40-44% lower overheads, with up to 20% packet losses. When compared to the existing NDN dataset synchronization protocols, DDSN can lower the state and data synchronization delays from one-third to two-third, and lower the protocol overhead by up to one-third, with the performance difference becoming more pronounced as network loss rates go up.