In large scale sensor networks contain various applications and domains. The data composed from wireless sensor network are used under making decisions in critical infrastructures. Data’s are generated from multiple sources those are transmitted through intermediate processing nodes. The aggregation function should be performed by the intermediate nodes. An attacker compromise those type of intermediate nodes by introducing additional attacking nodes in the network or compromising the existing nodes in the network. So achieving the high data trustworthiness is critical for correct decision-making. The provenance management challenges in sensor networks are consumption of low energy and low bandwidth consumption. This survey introduces a new lightweight scheme in order to securely transmit sensor data with provenance. The in-packet Bloom filters techniques used to encode provenance with the sensor data. This mechanism initially performs provenance at the source then perform restoration of the data at the destination. The provenance scheme functionality used to detect packet drop attacks organized by malicious intermediate data forwarding nodes. This survey describes the effectiveness and efficiency of the Light weight secure provenance scheme in detecting packet forgery and packet loss attacks through In Network Aggregation scheme. This scheme reduces the energy cost of processing in wireless sensor networks also there is no currently solution providing both integrity and confidentiality. Moreover, existing solutions allow only limited data transfer from 15MB to 25MB.So they have limited applicability to certain types of application. Recently, research has focused on secure exact in-network aggregation. Secure Exact In Network Aggregation use multi path approach. Secure Exact In Network Aggregation increase the data rate of data transfer up to 2GB from 25 MB based on the tree based approach .This approach perform aggregation by constructing an multipath, which could be a minimum spanning tree, rooted at sink and source nodes are considered as leaves. Each node has a parent node to forward its data. Flow of data starts from leaves nodes up to the sink and therein the aggregation done by multi path start from failed nodes rather at source node.