Carnegie Mellon University
Browse

The Effect of Social Influence on Security Sensitivity

Download (827.99 kB)
journal contribution
posted on 2014-07-01, 00:00 authored by Sauvik Das, Tiffany Hyun-Jin Kim, Laura DabbishLaura Dabbish, Jason I. Hong

Despite an impressive effort at raising the general populace’s security sensitivity—the awareness of, motivation to use, and knowledge of how to use security and privacy tools—much security advice is ignored and many security tools remain underutilized. Part of the problem may be that we do not yet understand the social processes underlying people’s decisions to (1) disseminate information about security and privacy and (2) actually modify their security behaviors (e.g., adopt a new security tool or practice). To that end, we report on a retrospective interview study examining the role of social influence—or, our ability to affect the behaviors and perceptions of others with our own words and actions—in people’s decisions to change their security behaviors, as well as the nature of and reasons for their discussions about security. We found that social processes played a major role in a large number of privacy and security-related behavior changes reported by our sample, probably because these processes were effective at raising security sensitivity. We also found that conversations about security were most often driven by the desire to warn or protect others from immediate novel threats observed or experienced, or to gather information about solving an experienced problem. Furthermore, the observability of security feature usage was a key enabler of socially triggered behavior change—both in encouraging the spread of positive behaviors and in discouraging negative behaviors.

History

Publisher Statement

Copyright is held by the author/owner. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee.

Date

2014-07-01

Usage metrics

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC