Dynamic signature verification for secure retrieval of classified information

With the growth of web enabled services and e-commerce, tremendous amount of information is now readily available on the Internet. A large proportion of this is classified information, which has to be protected against unauthorized access. Password or PIN can be used in conjunction with digital signature, for verification of the identity of users. This paper proposes a dynamic handwritten signature verification based access control system that can be employed in the legal, banking and commercial domains for designing secure information retrieval systems. The dynamic handwritten signature in this system is captured by using a digital tablet or PDA (Personal Digital Assistant) with contact sensitive acquisition system. After preprocessing, the signature data is compared with the templates of authorized signatures by employing an innovative neuro-fuzzy pattern recognition system based on sensing the pressure variable and total time required for executing the signature for uniquely identifying the potential user. The error in matching is used to arrive at the decision regarding permission or denial of access to the classified document. The neuro-fuzzy technique applied in the dynamic signature system is based on evolving fuzzy neural network. This technique has been tested on signatures drawn from signature verification competition database obtained from the internet. Encouraging results show that this technique is a good candidate for the development of practical applications.