SWARM INTELLIGENCE APPROACH OF LEAKER IDENTIFICATION IN SECURE MULTICAST

Secure multicasting is used in a wide range of multicast applications such as commercial pay-per-view video multicast and pay-per view digital library. The multicast protocol used must be secure with copyright protection to prevent the users from leaking the information. This paper focuses on the problem of leaker identification using a swarm intelligence (Ant Colony Optimization) based approach. Termed Ant Colony Optimized Leaker Identification algorithm (ACOLIA), the novel technique serves to efficiently identify the leaker while overcoming the drawbacks of the existing sequential search method, for leaker identification. Simulation results are shown to prove that the number of comparisons made by the ACOLIA is less when compared to the sequential search method for leaker identification.