EXPERT SYSTEM FOR REAL-TIME MOBILE AGENT NETWORK BASED ON COMMUNICATION SYSTEM
1TARUN DHAR DIWAN, 2 BHOOPENDRA DHAR DIWAN, and 3JAHANGEER MOHIUDIN LONE
1, 3 Department of Engineering, 2 Department of Basic Science, Dr. C. V. Raman University, Bilaspur (C.G), India
Email ID: email@example.com, firstname.lastname@example.org, email@example.com
In this paper Many researchers have investigated the development of protection mechanisms in a mobile agent platform. However, the protection mechanisms provided focused on protecting host resources from malicious agents. In these works suspicious cooperating agents have to include protection mechanisms at the application level, which makes the programming of agents a difficult task. In this paper, we proposed the use of semantics for agents to define protection policies using an Interface Definition Language that we have defined. Consequently, the agent application code and the definition of protection policies can be done separately, thus enhancing modularity, and easing programming task. The authentication of agents and the enforcement of their access control policies are done in a transparent way to the agents' applications by our messaging system. as signatures continue to play an important role in financial, commercial and legal transactions, truly secured authentication becomes more and more crucial. to perform verification or identification of a signature, several steps must be performed. Online signature verification has been shown to achieve much higher verification rate than offline verification this paper proposes a novel framework for online signature verification. Different from previous methods, our approach makes use of online handwriting instead of handwritten images for registration. The online registrations enable robust recovery of the writing trajectory from an input online signature and thus allow effective shape matching between registration and verification signatures. In addition, the online registrations enable robust recovery of the writing trajectory from an input online signature and thus allow effective shape matching between registration and verification signatures. in addition, the features have been calculated using 16 bits fixed-point arithmetic and tested with different classifiers, such as hidden markov models, support vector machines, and Euclidean distance classifier. We propose several new techniques to improve the performance of the new signature verification rate system.
Keywords: Verification Rate, markov models, hand writing recognition, training data, testing data. Registration,
International eJournal of Mathematics and Engineering
Volume 4, Issue 3, Pages: 2201 - 2207