Content access control aims at ensuring that, in a system with several resources, users can only access resources they are authorized to. Resources are encrypted using cryptographic keys. Generating, distributing and renewing these keys are the challenges faced by key management schemes. While most of the existing key management schemes are typically evaluated by simulation. We propose, for the first time, to use Markovian processes for this purpose. Markovian processes give more accurate evaluation. The key tables-based key management scheme for linear hierarchies (KTLH) is a particularly interesting key management scheme; it was initially proposed for securing group communications, but could easily be adapted to other application such as wireless sensor networks. KTLH requires each user to maintain a set of keys. The keys and size of the key set change dynamically, making the evaluation of the overheads of KTLH a challenging task. Our contribution is threefold, we have (1) modeled KTLH using Markov processes, (2) evaluated KTLH according to its storage, computation and bandwidth overheads and compared it to existing key management schemes and (3) shown how our approach could be generalized to other key management schemes.
Content access control within hierarchies is an ubiquitous problem. It occurs in any context where users have different access rights to a set of resources. Resources are encrypted using cryptographic keys and key management schemes are used to generate, distribute and renew them.We propose a new key management model and build an efficient key management scheme on top of it. We start by introducing the content access control problem and review the most important works on key management for content access control from both multicast and information technology communities. The main contribution of this paper is twofold: first, we propose a key management model that takes advantage of the implicit relations between resources to optimize the number of keys in the hierarchy; second, we propose a key management scheme our model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.