We address the problem of cage-trapping in diffusion through network structures exhibiting dynamic disorder using kinetic Monte Carlo Ising simulations to generate evolving network configurations. Diffusion is studied using blind random walkers (RWs) and we partition the net displacement of the RWs into two terms that represent contributions from transport through neighboring conducting clusters and self-diffusion of the site on which the RW finds itself, respectively. We propose a new scaling analysis for the diffusion cage-trapping time in this system and provide a theoretical analysis for estimating the trap-time scaling exponent that appears to universalize data obtained from computer simulations in both 2d and 3d Ising lattices. (C) 2009 Elsevier B.V. All rights reserved.