| Title | Enhancing and Evaluating Identity Privacy and Authentication Strength by Utilizing the Identity Ecosystem |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Chang, Kai Chih, Zaeem, Razieh Nokhbeh, Barber, K. Suzanne |
| Conference Name | Proceedings of the 2018 Workshop on Privacy in the Electronic Society |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-5989-4 |
| Keywords | authentication, composability, Human Behavior, identity, Internet of Things, IoT Security 2018, Metrics, privacy, pubcrawl, Resiliency |
| Abstract | This paper presents a novel research model of identity and the use of this model to answer some interesting research questions. Information travels in the cyber world, not only bringing us convenience and prosperity but also jeopardy. Protecting this information has been a commonly discussed issue in recent years. One type of this information is Personally Identifiable Information (PII), often used to perform personal authentication. People often give PIIs to organizations, e.g., when applying for a new job or filling out a new application on a website. While the use of such PII might be necessary for authentication, giving PII increases the risk of its exposure to criminals. We introduce two innovative approaches based on our model of identity to help evaluate and find an optimal set of PIIs that satisfy authentication purposes but minimize risk of exposure. Our model paves the way for more informed selection of PIIs by organizations that collect them as well as by users who offer PIIs to these organizations. |
| URL | http://doi.acm.org/10.1145/3267323.3268964 |
| DOI | 10.1145/3267323.3268964 |
| Citation Key | chang_enhancing_2018 |
Enhancing and Evaluating Identity Privacy and Authentication Strength by Utilizing the Identity Ecosystem