NSF Org:	CNS Division Of Computer and Network Systems
Recipient:	RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK, THE
Initial Amendment Date:	May 17, 2019
Latest Amendment Date:	June 18, 2019
Award Number:	1915828
Award Instrument:	Standard Grant
Program Manager:	Sara Kiesler skiesler@nsf.gov  (703)292-8643 CNS  Division Of Computer and Network Systems CSE  Directorate for Computer and Information Science and Engineering
Start Date:	June 1, 2019
End Date:	December 31, 2019 (Estimated)
Total Intended Award Amount:	$299,997.00
Total Awarded Amount to Date:	$315,997.00
Funds Obligated to Date:	FY 2019 = $0.00
History of Investigator:	Liyue Fan (Principal Investigator) liyue.fan@uncc.edu Lisa Baranik (Co-Principal Investigator)
Recipient Sponsored Research Office:	SUNY at Albany 1400 WASHINGTON AVE ALBANY NY  US  12222-0100 (518)437-4974
Sponsor Congressional District:	20
Primary Place of Performance:	SUNY at Albany 1044 Washington Ave Albany NY  US  12222-0100
Primary Place of Performance Congressional District:	20
Unique Entity Identifier (UEI):	NHH3T1Z96H29
Parent UEI:	NHH3T1Z96H29
NSF Program(s):	Special Projects - CNS, Secure &Trustworthy Cyberspace
Primary Program Source:	01001920DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):	025Z, 065Z, 114Z, 7434, 7916, 9102, 9178, 9251
Program Element Code(s):	171400, 806000
Award Agency Code:	4900
Fund Agency Code:	4900
Assistance Listing Number(s):	47.070

ABSTRACT

Social and behavioral research has a long history of collecting digitized data. With more and more studies incorporating participants' smartphone sensor and usage data, individual privacy has become a serious concern. Although researchers are trained to exercise confidentiality, sensitive information can be inferred from the smartphone data about the participants and their environment (e.g., families and communities). Without a systematic solution to address privacy concerns, participants may withdraw and request removal of their data from studies. This project aims to provide privacy protection to study participants during data collection, thus encouraging research participation. Furthermore, the project demonstrates that meaningful research results can be derived while honoring the participants' privacy preferences.

The project bridges the privacy-enhancing technologies community and social and behavioral research community by focusing on the usefulness and limitations of privacy technologies, collectively. Specifically, the project (1) includes a systematic review of privacy-preserving methods for commonly collected smartphone data types and develops open-source tools compatible with widely adopted research platforms; (2) studies the usefulness of data privacy methods and identifies limitations and open challenges, by incorporating the perspectives of social and behavior researchers; and (3) further studies participant privacy concerns and the utility of privacy-enhanced data through a case study on refugee vocational behavior, which focuses on using survey and mobile behavioral data to predict job-search behaviors.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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