Rumour is a vital problem for modern techniques of communication. A piece of unauthenticated information travels around the social network creating chaos. In this study, based upon an integrated window prototype model network, N number of nodes are generated. In the study first, the time-varying networks are reduced to a series of static networks by introducing a time-integrating window. Second, instead of inspecting every individual, a reverse dissemination traversal algorithm is used to specify a set of suspects in the source. Third, to determine the real source from the suspects, a novel microscopic rumour spreading model is used to calculate the data counts for each suspect. The one who gets the largest count estimate is considered as to the real source. The proposed work develops a built-in dataset other than the cases, if a user sends existing information in the network it will not allow it to pass on and the fault information creator will block in the network and won't be allowed to send more information. Thus, the approaches help in building reliability in the system. © 2020 IEEE.