@misc{cogprints6711,
          volume = {4},
          number = {2},
           month = {September},
          author = {Manoj Kumar  Singh},
           title = {Password Based a Generalize Robust Security System Design Using Neural Network},
       publisher = {International Journal of Computer Science Issues, IJCSI},
         journal = {M. K. Singh, "Password Based a Generalize Robust Security System Design Using Neural Network", International Journal of Computer Science Issues, IJCSI, Volume 4, Issue 2, pp1-9, September 2009},
            year = {2009},
        keywords = {artificial neural network, security, authentication, intrusion detection},
             url = {http://cogprints.org/6711/},
        abstract = {Among the various means of available resource protection including biometrics, password based system is most simple, user friendly, cost effective and commonly used. But this method having high sensitivity with attacks. Most of the advanced methods for authentication based on password encrypt the contents of password before storing or transmitting in physical domain. But all conventional cryptographic based encryption methods are having its own limitations, generally either in terms of complexity or in terms of efficiency. Multi-application usability of password today forcing users to have a proper memory aids. Which itself degrades the level of security. In this paper a method to exploit the artificial neural network to develop the more secure means of authentication, which is more efficient in providing the authentication, at the same time simple in design, has given. Apart from protection, a step toward perfect security has taken by adding the feature of intruder detection along with the protection system. This is possible by analysis of several logical parameters associated with the user activities. A new method of designing the security system centrally based on neural network with intrusion detection capability to handles the challenges available with present solutions, for any kind of resource has presented.}
}

<script src="//archive-bar.soton.ac.uk/archive-bar.js"></script>