Optimization of Security Framework Mechanism Based on Local Knowledge Discovery Process for WSN

Network security is a prime concern along with energy management in wireless sensor networks. Many application of wireless sensor network such as monitoring, tracking and priority processing of security are always dependent on available resources and available security measures. This research provides security framework with aggregation adaptive framework for network filtering process with add on feature of pattern matching process with frequent correlation with packet sequence. We have used free bit information in header for frequent correlated match of any malicious activity so that there is no need to go for the pattern matching with knowledge base of the network for the same type of events occurred in the network. Variation of security level has been considered with variation of attacker time. Our proposed framework provides 2 % less security level hitting values when tested with 300 collected periods and provides 5 % less security level hitting values when tested with 300 collected periods with variation of frequency of attack when compared to adaptive security framework. Proposed work provides less resource consumption and higher security level in aggregated view of context with stable authentication process.