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Recent advances in wireless sensor networks (WSNs) have led to many new promising applications including habitat monitoring and target tracking. However, data communication between nodes consumes a large portion of the total energy consumption of the WSNs. Consequently, Data Aggregation techniques can greatly help to reduce the energy consumption by eliminating redundant data traveling back to the base station. The security issues such as data integrity, confidentiality, and freshness in data aggregation become crucial when the WSN is deployed in a remote or hostile environment where sensors are prone to node failures and compromises. There is currently research potential in securing data aggregation in the WSN. Data-centric technologies are needed that perform innetwork aggregation of data to yield energy-efficient dissemination. In this paper we model jamming prevention techniques and compare its performance with traditional prevention techniques. In the proposed work sourcedestination placement and communication network density on the energy costs and delay associated with data aggregation. In my proposed work, defense strategies offers significant performance gains across a wide range of operational scenarios. The main goal of defense strategies algorithms is to gather and protect jamming areas in an energy efficient manner so that network lifetime is enhanced.