tailieunhanh - Báo cáo hóa học: "Research Article A Novel Distributed Privacy Paradigm for Visual Sensor Networks Based on Sharing Dynamical Systems"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Novel Distributed Privacy Paradigm for Visual Sensor Networks Based on Sharing Dynamical Systems | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2007 Article ID 21646 17 pages doi 2007 21646 Research Article A Novel Distributed Privacy Paradigm for Visual Sensor Networks Based on Sharing Dynamical Systems William Luh Deepa Kundur and Takis Zourntos Department of Electrical and Computer Engineering 214 Zachry Engineering Center Texas A M University College Station TX 77843-3128 USA Received 5 January 2006 Revised 29 April 2006 Accepted 30 April 2006 Recommended by Chun-Shien Lu Visual sensor networks VSNs provide surveillance images video which must be protected from eavesdropping and tampering en route to the base station. In the spirit of sensor networks we propose a novel paradigm for securing privacy and confidentiality in a distributed manner. Our paradigm is based on the control of dynamical systems which we show is well suited for VSNs due to its low complexity in terms of processing and communication while achieving robustness to both unintentional noise and intentional attacks as long as a small subset of nodes are affected. We also present a low complexity algorithm called TANGRAM to demonstrate the feasibility of applying our novel paradigm to VSNs. We present and discuss simulation results of TANGRAM. Copyright 2007 Hindawi Publishing Corporation. All rights reserved. 1. INTRODUCTION Visual data is an integral part of the interface between humans and their environment. Visual data in the form of images and video can be used to enhance a human operator s ability to reliably make crucial decisions in the face of alerts provided by sensing mechanisms. For example in a combat field a sensor network can be deployed to sense temperature toxins vibrations movement and so forth. To reliably assess whether a change in the sensed phenomena is due to enemy infiltration or natural environmental and fauna causes it is useful to obtain additional side information in the form of an image. As another example in health