After overcoming some drawbacks from an improved genetic feedback algorithm based network security policy framework. A motivation was experienced for the need of a strong network security policy framework. In this paper a strong network model for security function is presented. A gene for a network packet is defined through fitness function and a method to calculate fitness function is explained. The basic attacks encountered can be categorized as buffer overflow, array index out of bound, etc. A stress is given on passive attack, active attack, its types and brute force attack. An analysis on recent attacks and security is provided. Finally the best policy using a comparator is found. The main aim of this paper is threat detection, time optimization, performance increase in terms of accuracy and policy automation. For experimenting real data set from the internet and local network is used. Jpcap, winpcap, Colasoft Capsa 7 open source software are used for implementation. 73% efficiency is achieved because we add 3 networking terms such as payload, checksum, and sequence number. A client server environment is made use of. General TermsGenetic algorithm, Network security, Crossover technique.