CRM: a new dynamic cross-layer reputation computation model in wireless networks
Lin, H; Hu, J; Ma, J; et al.Xu, L; Yang, L
Date: 1 April 2015
Journal
Computer Journal
Publisher
Oxford University Press (OUP)
Publisher DOI
Abstract
Multi-hop wireless networks (MWNs) have been widely accepted as an indispensable
component of next-generation communication systems due to their broad applications and easy
deployment without relying on any infrastructure. Although showing huge benefits, MWNs face many
security problems, especially the internal multi-layer security ...
Multi-hop wireless networks (MWNs) have been widely accepted as an indispensable
component of next-generation communication systems due to their broad applications and easy
deployment without relying on any infrastructure. Although showing huge benefits, MWNs face many
security problems, especially the internal multi-layer security threats being one of the most challenging
issues. Since most security mechanisms require the cooperation of nodes, characterizing and learning
actions of neighboring nodes and the evolution of these actions over time is vital to construct an
efficient and robust solution for security-sensitive applications such as social networking, mobile
banking, and teleconferencing. In this paper, we propose a new dynamic cross-layer reputation
computation model named CRM to dynamically characterize and quantify actions of nodes. CRM
couples uncertainty based conventional layered reputation computation model with cross-layer design
and multi-level security technology to identify malicious nodes and preserve security against internal
multi-layer threats. Simulation results and performance analyses demonstrate that CRM can provide
rapid and accurate malicious node identification and management, and implement the security
preservation against the internal multi-layer and bad mouthing attacks more effectively and efficiently
than existing models.
Computer Science
Faculty of Environment, Science and Economy
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