Straining Attacker's Impact in WSN using Secure Data Aggregation

Wireless sensor networks (WSNs) are significantly found in several purposes, such as volcano and fireplace tracking, metropolitan sensing, and border surveillance. In a large WSN, in-network information aggregation considerably reduces the total amount of connection cost and power consumption. The research community planned a loss-resilient aggregation construction called synopsis diffusion, which uses duplicate-insensitive algorithms on prime of multipath routing schemes to precisely compute aggregates. But, this aggregation construction does not handle the issue of false sub aggregate values led by compromised nodes. That attack might cause large mistakes in the aggregate computed at the beds base station that will be the main node in the aggregation hierarchy. In this paper, we make the synopsis diffusion approach secure against the above mentioned attack presented by compromised nodes. Particularly, we present an algorithm allow the beds base station to solidly compute predicate rely or sum even in the clear presence of this kind of attack. Our attack-resilient computation algorithm computes the true aggregate by filter out the benefits of compromised nodes in the aggregation hierarchy.