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Trusted CI Webinar: Data Quality and Security Evaluation Framework Development
In this talk, we are presenting our work on building a data quality and security (DQS) framework, which integrates cybersecurity with other diverse metrics, such as accuracy, reliability, timeliness, and safety into a single methodological and technological framework.

This innovation has a high potential to enable a significant improvement in a wide spectrum of science and technology applications as it will create new opportunities for optimizing data structures, data processing and fusion procedures based on a new quality and security information application. While the developed evaluation techniques may cover a wide range of data sources, the current framework’s implementation concentrates on using an ordinary user’s owned mobile devices and Android-based smartphones in particular.

We believe that DQS evaluation framework will stimulate further improvement of the quality of the whole cyberinfrastructure and, in particular, cybersecurity.

About Trusted CI: Trusted CI is the NSF Cybersecurity Center of Excellence. The mission of Trusted CI is to improve the cybersecurity of NSF computational science and engineering projects, while allowing those projects to focus on their science endeavors. This mission is accomplished through one-on-one engagements with projects to solve their specific problems, broad education, outreach and training to raise the practice-of-security across the community, and looking for opportunities for improvement to bring in research to raise the state-of-practice. ​For more information about what Trusted CI does, how it can help your project, the advances it is making in cybersecurity and resources for cybersecurity professionals, please see our website

*NOTE:* Be sure to check your SPAM/JUNK folder for the registration confirmation email.

Mar 26, 2018 11:00 AM in Indiana (East)

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Leon Reznik
Professor of Computer Science & Computing Security @Rochester Institute of Technology
Leon Reznik is a Professor of Computer Science (primary affiliation) and Computing Security (secondary affiliation) at the Rochester Institute of Technology. His current research concentrates on data quality and security evaluation and assurance; cognitive sensor networks and systems; intelligent intrusion detection and big data analytics.
Igor Khokhlov
Ph.D. Candidate @Rochester Institute of Technology
Igor Khokhlov is a Ph.D. candidate at the Rochester Institute of Technology. He conducts research on data quality and value evaluation for sensor-originated data. Igor’s fields of interest include Android OS, cyber-security, and AI.