Secure Data Distribution and Access in Large Sensor Networks

Louisiana State University, Baton Rouge LA

Investigators

Abstract

Sensor networks, with their massive information acquisition potential, represent a mechanism by which Information Technology can be used to mitigate the vulnerabilities of society with regard to natural and manmade catastrophic events. Two critical components of information management in sensor networks are: (a) secure data distribution i.e., identifying secure in-network sensor data storage sites and determining their specific data contents in order to maximize overall data security and minimize routing overhead to these sites, and (b) data access via maximally secure energy-constrained query reporting between data nodes. These problems cannot be solved in a stand-alone manner, since optimal solutions in one area may lead to sub-optimal solutions in others. This work proposes the development of a unified analytical framework using game-theoretic techniques. The proposed holistic information management framework will enable the successful acquisition and efficient utilization of sensornet data by identifying storage repositories, data contents, and secure query reporting schemes that are optimally suited to each other. Efficient algorithms for the above problems will be derived using a new Data Security Index metric which explicitly accounts for the actions of intelligent opponents and models sensors as intelligent agents cooperating to achieve network objectives, such as maximal data security and data access.