Secure Barcode Authentication using Genetic Algorithm

Abstract

Genetic Algorithm (GA) is an invaluable tool for solving optimization problems due to its robustness. It does not break even in the presence of a reasonable noise or even if the inputs are changed slightly. GA offers significant benefits over other optimization techniques in searching a large state space or n-dimensional surface. In todays information age information transfer and sharing has increased exponentially. With the popularization of Internet and exponential increase in e-commerce transactions security has become an inevitable and an integral part of any e-commerce application. Data integrity, confidentiality, authenticity, nonrepudiation have gained tremendous importance and have become important components of information security. In this paper we have made an attempt to exploit the randomness involved in crossover and mutation processes of GA for generating a barcode for authentication process. The number of crossover points and number of mutation points is fixed and cannot be altered by the user. In the current work we have employed a single crossover point and two mutation points. We have used Code-39 and Code-128 encoding techniques for generating a barcode. The barcode data comprises of 12 randomly generated decimal digits. Each decimal digit is represented using 4 bits. Hence the length of the barcode data is 36 bits. The randomly generated data is transformed into encoded form by applying crossover, mutation and XOR operations before generating a bar code. The randomness together with encoding makes the password robust and hard to track. Finally, the algorithm is implemented in Java and applied for authentication of employee data in a hypothetical organization. The methodology is general and can be applied to any task where authentication is required.