CT-ER: Security and Privacy Solutions for Data-Centric Sensor Networks

Proposal Number: NSF-0627382

TITLE: Security and Privacy Solutions for Data-Centric Sensor Networks

PI: Sencun Zhu ([email protected]), Co-PI: Guohong Cao ([email protected])

As sensor networks scale in size, so will the amount of sensing

data generated. The large volume of data coupled with the fact

that the data are spread across the entire network creates a

demand for efficient data dissemination/access techniques to find

the relevant data from within the network. This demand has led to

the development of data centric sensor (DCS) networks, where

sensor data rather than sensor nodes are named based on attributes

such as event type or geographic location. However, saving data in

the network also creates critical security problems, which have

not been addressed by previous work.

The objective of this research is to design secure DCS systems

which provide two fundamental security services: data

confidentiality and location privacy. Three types of attack models

with increasing attacker capabilities are considered, including

local passive attacks, sensor-assisted passive attacks, and

compromise-based active attacks. Techniques based on the principle

of least privilege, dummy traffic and filtering, location privacy

and query optimization are designed to defend against the attacks.

The success of this research will have a much broader impact on

making sensor networks more affordable and amenable to commercial,

civilian, and military applications. It has the potential to

foster new research in the privacy perspective of sensor networks.

The results from this research will be disseminated widely through

high quality publications and talks. The proposed research will

also be integrated with the education curricula at Penn State.