In recent times, the development sensors wirelessly have been an essential requirement for cutting-edge areas like environment surveillance and intelligent cities. En-route filtering systems are mainly focused on energy efficiency by preventing fraudulent report injection attacks. However, the lifetime of networks is typically neglected. They also have fixed path routing as well as fixed responses to attacks. Additionally, the hot-spot issue is regarded as one of the biggest problems in the extension of network life. In this paper, we propose an algorithmic basis for a fuzzy genetic optimized re-clustering technique to overcome these restrictions and thus reduce the impact of the hot-spot issue. This fuzzy algorithm is employed to analyze the network conditions. In re-clustering key issue is when to conduct the subsequent clustering. To determine the exact time of the next clustering (i.e. the energy draining from the nodes to zero) as well as the fuzzy member functions are optimized by using a the genetic algorithm. Simulation tests verify the proposed algorithm. It has shown that the network's lifetime can be extended by up to 3.64 times while maintaining the detection capability and energy efficiency.