Wireless sensor networks (WSNs) are distributed collection of small sensor nodes that gather security-sensitive data and control security-critical operations in a wide range of industrial, home, and business applications. Their numerous applications, including those that concern the nation?s security, the health care system, and monitoring and protecting natural landscapes, clearly put the robust operation of WSNs at the core of technologies that are vital to our society. Using advanced tools from the theory of random graphs, this project develops methods for designing WSNs that are i) secure; ii) reliable against sensor and link failures; and iii) resilient against adversarial attacks. The research program is supported by several education and outreach activities including development of new courses, K-12 outreach, and dissemination of research results to academic and industrial audience.
In order to ensure a secure, reliable, and resilient WSN operation, investigators consider WSNs that employ a randomized key predistribution scheme and develop conditions so that the network i) is k-connected; and ii) is resilient against node capture attacks in the sense of unassailability and unsplittability. This is done by developing realistic models of secure WSNs constructed by intersecting two random graphs: a cryptographic graph induced by the random key predistribution scheme and a communication graph induced by the wireless communication media and random deployment of sensors. For several classical random key predistribution schemes and wireless communication models, investigators develop (i) zero-one laws for k-connectivity; (ii) Poisson approximation results to obtain the asymptotic probability of k-connectivity; and (iii) conditions on network parameters (e.g., number of nodes, link failure probability, number of keys per node, key pool size) that ensure the unassailability and unsplittability of the network.
