Enhanced Password Based Security System Based on User Behavior using Neural Networks

There are multiple numbers of security systems are available to protect your computer/resources. Among them, password based systems are the most commonly used system due to its simplicity, applicability and cost effectiveness But these types of systems have higher sensitivity to cyber-attack. Most of the advanced methods for authentication based on password security encrypt the contents of password before storing or transmitting in the physical domain. But all conventional encryption methods are having its own limitations, generally either in terms of complexity or in terms of efficiency. In this paper an enhanced password based security system has been proposed based on user typing behavior, which will attempt to identify authenticity of any user failing to login in first few attempts by analyzing the basic user behaviors/activities and finally training them through neural network and classifying them as genuine or intruder.