Data security and privacy research at UT Dallas will get a significant boost thanks to two grants totaling almost $1 million from the National Science Foundation.
Collaborators at Purdue University will receive about half that funding, with the balance coming to Dr. Murat Kantarcioglu at UT Dallas.
The larger of the two grants deals with the increasingly common practice of cross-matching datasets to support various activities involving intelligence, counterterrorism, forensics and disease control.
“Because those datasets may contain privacy-sensitive or confidential information, the use of efficient privacy-preserving protocols for cross-matching different datasets is crucial,” said Kantarcioglu, an assistant professor of computer science and director of the University’s Data Security and Privacy Lab.
Techniques known as secure multi-party computation (SMC) protocols are already in place to address such issues, but they have one major drawback: They aren’t scaleable using a reasonable amount of computing resources to the size of the large datasets involved.
This project takes a novel approach to addressing that problem by using what are known as privacy-preserving data sanitization methods, Kantarcioglu said. The goal is to establish a multi-step process using an approach called differential privacy to maximize the accuracy of queries from statistical databases while minimizing the chances of identifying its records.
In other words, the work seeks to derive extremely accurate information while preserving very high levels of privacy.
“The approach developed in this project expands the opportunities and contexts for data use by enabling the cross-match of multiple data archives, possibly owned by different parties, without violating the privacy of the data,” said Kantarcioglu, whose co-investigator at UT Dallas on the project is Dr. Latifur Khan, an associate professor of computer science.
The second grant supports development of a comprehensive approach for data quality in sensor networks. Rather than protecting individual privacy, the goal is to ensure the trustworthiness of the data, which, from a computer scientist’s standpoint, is a related issue.
“This project focuses on cases where there may be a malicious attacks launched to decrease the quality of sensor network data,” Kantarcioglu said. “Consider a sensor network created to monitor a battlefield, for example. An adversary may launch multiple attacks to feed false information through the network. Our goal is to create tools that can help design sensor networks that can provide high-quality data even under malicious attacks.”
The research is also relevant to the use of sensor networks in healthcare, homeland security and other domains, he said.
In addition to leading research under these two grants, Kantarcioglu is an NSF Career Award recipient and the principal investigator for cybersecurity-related grants from the U.S. Air Force, the National Institutes of Health and the Office of Naval Research. These projects and others have contributed not only to papers published in academic journals and presented at technical conferences but also to several tool repositories and open-source software created by UT Dallas professors and students, said Dr. Bhavani Thuraisingham, director of the University’s Cybersecurity Research Center.
One of those tool repositories, an anonymization toolbox that can be used to sanitize privacy-sensitive data before data release, has already been downloaded by more than 300 researchers from around the work, including the U.S., Canada, the United Kingdom, Israel, Germany, Hungary, India, China, France, Turkey, Greece, Ireland and Senegal.