| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | August 21, 2014 |
| Latest Amendment Date: | May 24, 2017 |
| Award Number: | 1422215 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Dan Cosley
dcosley@nsf.gov (703)292-8832 CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | October 1, 2014 |
| End Date: | September 30, 2018 (Estimated) |
| Total Intended Award Amount: | $279,154.00 |
| Total Awarded Amount to Date: | $295,154.00 |
| Funds Obligated to Date: |
FY 2017 = $16,000.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
201 OLD MAIN UNIVERSITY PARK PA US 16802-1503 (814)865-1372 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
110 Technology Center Building State College PA US 16802-7000 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
Special Projects - CNS, Secure &Trustworthy Cyberspace |
| Primary Program Source: |
01001718DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Online social networks, such as Facebook, Twitter, and Google+, have become extremely popular. They have significantly changed our behaviors for sharing information and socializing, especially among the younger generation. However, the extreme popularity of such online social networks has become a double-edged sword -- while promoting online socialization, these systems also raise privacy issues. To protect user privacy without compromising socialization functions, this project articulates a unifying framework that bridges the gap between the human-oriented and technology-centered perspectives. In particular, this project is developing methods to (1) detect the discrepancies between users' information sharing expectations and actual information disclosure; (2) design a user-centered yet computationally-efficient formal model of user privacy in social networks; and (3) develop a mechanism to effectively enforce privacy policies in the proposed model. The potential long-term social benefits are significant, since such awareness may gradually change people's privacy perceptions and affect their behavior in privacy-centric scenarios.
This project develops a concept of "Social Circles" to model social network access within a Restricted Access and Limited Control framework. Methods are being developed to derive social circles from a variety of types of existing information within the social network; these are used to determine appropriate access control settings. The project is assessing information flow and risk of leakage given such settings, including the issues raised by heterogeneity of systems. In addition to theoretical analysis of potential information flows with respect to a variety of adversary models, the project is conducting user studies to determine if this approach reduces the gap between perceived and actual privacy.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
With the increasing participation in online social networks, it has become critical to preserve users’ privacy, without preventing them from socialization and information sharing. Unfortunately, existing approaches from either human-oriented or technology-centered camp fall short meeting such requirements. Often, findings in human-oriented camp have little concern on computational or implementation-related aspect while those in technology-centered camp use over-simplified privacy model due to lack of understanding of user needs and privacy policy. Toward this dichotomy between two perspectives on user privacy in social networks, over the project period, we have accomplished the following objectives: (1) we proposed a unifying Social Circle framework that bridges the gap between human-oriented and technology-centered privacy perspectives; (2) using the developed social circle model, we have analyzed the privacy protection mechanism in commercial social network platforms; (3) we have developed a personalized, context-aware privacy scoring mechanism to automatically assess the sensitiveness of unstructured text messages in online social platforms such as Twitter; and (4) we have Investigated users' privacy attitudes and leakages to better understand complicated privacy issues better, using Instagram as an example case. Our technical achievements have appeared or will appear in two dozen academic publications at top-tier outlets. Finally, we have also successfully trained a number of graduate students and undergraduate students under REU program, providing in-depth and hands-on research environment.
Last Modified: 02/16/2019
Modified by: Dongwon Lee
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