An AACO Based Optimized SWiFi Network To Reduce Overheads

Nowadays the internet is Janus-faced with several challenges. Verifying data integrity and authentication are essential security services in order to secure data transmission process. Maintaining the security of your computer, network and private/sensitive data against unauthorized access and a wide variety of security threats without compromising the efficiency of the network can be challenging. The existing scheme enhance the data integrity, authentication and privacy depending on encryption/decryption methods by combining PGP, SWiFi and HMAC Systems in WiFi network but the efficiency of the system is reduced due to the overheads like delay, load etc. encountered during transmission. This research proposed a security technique to reduce the security risk across networks using PGP, sWiFi and HMAC systems with an efficient adaptive ant colony optimization (AACO) algorithm with uniform mutation operator using self-adaptive approach. Here mutation operator is used for enhancing the algorithm escape from local optima. The algorithm converges to the optimal final solution, by gathering the most effective sub-solutions where the probability of delay, load, retransmission attempts is very low and throughput is high. The proposed scheme gives better results than existing scheme as presented in results. The proposed technique is very complex for attackers to decode, and it is applicable to client-server architecture. The proposed system is expected to present, protect, and enhance the data integrity, authentication and privacy. Also, it improves the performance of the system. From the current study it may be concluded that the proposed system is more efficient than that of existing scheme. ________________________________________________________________________________________________________