In order to offer backward and forward secrecy for multicast applications (i.e., a new member cannot decrypt the multicast data sent before its joining and a former member cannot decrypt the data sent after its leaving), the data encryption key has to be changed whenever a user joins or leaves the system. Such a change has to be made known to all the current users. The bandwidth used for such re-key messaging can be high when the user pool is large. We propose a distributed servers approach to minimize the overall system bandwidth (and complexity) by splitting the user pool into multiple groups each served by a (logical) server. After presenting an analytic model for the system based on a hierarchical key tree, we show that there is an optimal number of servers to achieve minimum system bandwidth. As the underlying user traffic fluctuates, we propose a simple dynamic scheme with low overhead where a physical server adaptively splits and merges its traffic into multiple groups each served by a logical server so as to minimize its total bandwidth. Our results show that a distributed servers approach is able to substantially reduce the total bandwidth required as compared with the traditional single-server approach, especially for those applications with a large user pool, short holding time, and relatively low bandwidth of a data stream, as in the Internet stock quote applications.

Multicast is an efficient technique for delivering data to a large group of users. For some applications, offering multicast security is an important issue. In such a system, a new member should not be able to decrypt the multicast data sent before its joining and a former member should not be able to decrypt the multicast data sent after its leaving. Traditional approaches generally focus on reducing the re-key messages for a single server. However, these approaches still lead to large exchange overhead when the group is large. We consider a distributed server network in which the user pool is split into multiple groups and served by multiple servers. Given the user traffic, there is a trade-off between the amount of re-key messaging and the total data bandwidth needed. We present a simple model for the system and study how the total bandwidth (including the re-key messaging and data traffic) can be minimized by optimizing the number of servers in the network. As the underlying user traffic is dynamic, a server should be able to split and merge user groups to minimize its total bandwidth. We propose a scheme for such a purpose. We show that a distributed server network is able to reduce substantively the total bandwidth required in the system as compared to the traditional scheme.