Hamming Distance Approach to Reduce Role Mining Scalability

Role-based Access Control has become the standard of practice for many organizations restricting control on limited resources in complicated infrastructures or systems. The main objective role mining development is to define appropriate roles that can be applied specified security access policies. However, scales this kind setting are extensive and cause a huge load management To resolve above mentioned problems, paper proposes model implements Hamming Distance approach by rearranging existing matrix as input data overcome scalability problem. findings show generated file size all datasets substantially have been reduced compared original It also shown technique successfully reduce scale ranging between 30% 47% produce better candidate roles.