Injecting false data attack is a well studied topic in Wireless Sensor Networks. Traditional bandwidth efficient mechanism filters the false data injection with minor extra overheads at the en-route nodes and reduces the energy in the entire network. But bandwidth efficient mechanism fail to prevent early detection of gang injecting false data attack from mobile compromised sensor nodes. An effective strategy for early detection of injected false data is to use data aggregation and data authentication protocol that can sparsely minimize the waste of resources including bandwidth and battery power for confidential data transmission. However, such data transmission framework did not address important factors such as network security and efficiency. In this paper, we present a localized Bandwidth Optimal Group Injected Data Filtering (BO-GIDF) framework that handles group injected false data and improves network security by formulating a neighbor selection mechanism to identify whether the node is injected with false data or not. The BO-GIDF framework includes Group based Collaborative Neighbor Selection and time taken on packet forwarding from one point to another to identify the presence of false data being appended in the framework. With the application of Time-efficient Sink Detection algorithm, the occurrence of time event on packet forwarding helps to improve packet transmission. The proposed framework includes enhancement to security and efficiency by forwarding the node information and performing the verification procedure based on the received packet to filter the false data. We also demonstrate how the proposed framework can be extended to filter group of injected false data in the sensor network using Associative Filtering scheme. Extensive experiments and simulation results indicate that, in terms of bandwidth efficiency (for gang injecting false attack), packet transmission, network security and processing time, BO-GIDF performs favorably compared to existing filtering mechanisms in wireless sensor network. © Research India Publications.