Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/2994539.2994541acmconferencesArticle/Chapter ViewAbstractPublication PagesccsConference Proceedingsconference-collections
research-article
Public Access

Privacy Risk in Cybersecurity Data Sharing

Published: 24 October 2016 Publication History

Abstract

As information systems become increasingly interdependent, there is an increased need to share cybersecurity data across government agencies and companies, and within and across industrial sectors. This sharing includes threat, vulnerability and incident reporting data, among other data. For cyberattacks that include sociotechnical vectors, such as phishing or watering hole attacks, this increased sharing could expose customer and employee personal data to increased privacy risk. In the US, privacy risk arises when the government voluntarily receives data from companies without meaningful consent from individuals, or without a lawful procedure that protects an individual's right to due process. In this paper, we describe a study to examine the trade-off between the need for potentially sensitive data, which we call incident data usage, and the perceived privacy risk of sharing that data with the government. The study is comprised of two parts: a data usage estimate built from a survey of 76 security professionals with mean eight years' experience; and a privacy risk estimate that measures privacy risk using an ordinal likelihood scale and nominal data types in factorial vignettes. The privacy risk estimate also factors in data purposes with different levels of societal benefit, including terrorism, imminent threat of death, economic harm, and loss of intellectual property. The results show which data types are high-usage, low-risk versus those that are low-usage, high-risk. We discuss the implications of these results and recommend future work to improve privacy when data must be shared despite the increased risk to privacy.

References

[1]
D. W. Jorgenson, M. S. Ho, and K. J. Stiroh, Productivity, Volume 3: Information Technology and the American Growth Resurgence, Postwar U.S. Economic Growth. MIT Press, 2005.
[2]
FBI, "2015 Internet Crime Report," 2016.
[3]
Symantec, "Internet Security Threat Report 2016," April, p. 81, 2016.
[4]
D. Shackleford, "Combatting cyber risks in the supply chain," SANS.org, 2015.
[5]
O. of the W. H. P. Secretary, "Fact Sheet: Administration Cybersecurity Efforts 2015," 2015.
[6]
PWC, "The Global State of Information Security® Survey 2016: Turnaround and transformation in cybersecurity," 2016.
[7]
R. A. Bauer, "Consumer behavior as risk taking," in Risk Taking and Information Handling in Consumer Behavior, 1960, pp. 389--398.
[8]
C. Starr, "Social benefit versus technological risk.," Science (80-. )., vol. 165, no. 3899, p. 1232, Sep. 1969.
[9]
B. Fischhoff, P. Slovic, S. Lichtenstein, S. Read, and B. Combs, "How safe is safe enough? A psychometric study of attitudes towards technological risks and benefits," Policy Sci., vol. 9, no. 2, pp. 127--152, Apr. 1978.
[10]
P. Slovic, The perception of risk. 2000.
[11]
F. Knight, "Risk, Uncertainty, and Profit," Hart Schaffner Marx Prize essays, vol. XXXI, pp. 1--173, 1921.
[12]
J. Freudiger, S. Rane, A. E. Brito, and E. Uzun, "Privacy Preserving Data Quality Assessment for High-Fidelity Data Sharing," WISCS '14 Proc. 2014 ACM Work. Inf. Shar. Collab. Secur., pp. 21--29, 2014.
[13]
D. Khader, "Attribute Based Search in Encrypted Data," Proc. 2014 ACM Work. Inf. Shar. Collab. Secur. - WISCS '14, pp. 31--40, 2014.
[14]
L. Xu, C. Jiang, Y. Chen, Y. Ren, and K. J. R. Liu, "Privacy or utility in data collection? A contract theoretic approach," IEEE J. Sel. Top. Signal Process., vol. 9, no. 7, pp. 1256--1269, Oct. 2015.
[15]
P. Cichonski, T. Millar, T. Grance, and K. Scarfone, "Computer Security Incident Handling Guide: Recommendations of the National Institute of Standards and Technology, 800--61. Revision 2," NIST Spec. Publ., vol. 800-61, p. 79, 2012.
[16]
J. C. Baird and E. Noma, Fundamentals of scaling and psychophysics. John Wiley & Sons, Inc., 1978.
[17]
K. Auspurg and T. Hinz, Factorial Survey Experiments. 2014.
[18]
J. Bhatia, T. D. Breaux, J. R. Reidenberg, T. B. Norton, "A Theory of Vagueness and Privacy Risk Perception," IEEE 24th International Requirements Engineering Conference (RE'16), 2016.
[19]
H. Nissenbaum, Privacy in context: Technology, policy, and the integrity of social life. Stanford Law Books, 2009.
[20]
C. Wakslak and Y. Trope, "The effect of construal level on subjective probability estimates," Psychol. Sci., vol. 20, no. 1, pp. 52--58, Jan. 2009.
[21]
J. T. Kulas and A. A. Stachowski, "Respondent rationale for neither agreeing nor disagreeing: Person and item contributors to middle category endorsement intent on Likert personality indicators," J. Res. Pers., vol. 47, no. 4, pp. 254--262, Aug. 2013.
[22]
A. Gelman and J. Hill, "Data analysis using regression and multilevel/hierarchical models," Policy Anal., pp. 1--651, 2007.
[23]
H. Hibshi, T. D. Breaux, and S. B. Broomell, "Assessment of risk perception in security requirements composition," 2015 IEEE 23rd Int. Requir. Eng. Conf. (RE), pp. 146--155, 2015.
[24]
F. Faul, E. Erdfelder, A.-G. Lang, and A. Buchner, "G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences.," Behav. Res. Methods, vol. 39, no. 2, pp. 175--91, May 2007.
[25]
J. Creswell, "Research design?: qualitative, quantitative, and mixed methods approaches," 2014, p. 273.
[26]
T. D. Breaux, H. Hibshi, and A. Rao, "Eddy, a formal language for specifying and analyzing data flow specifications for conflicting privacy requirements," Requir. Eng., vol. 19, no. 3, pp. 281--307, Sep. 2014.
[27]
T. D. Breaux, D. Smullen, and H. Hibshi, "Detecting repurposing and over-collection in multi-party privacy requirements specifications," 2015 IEEE 23rd Int'l Req'ts Engr. Conf. (RE), 2015, pp. 166--175.

Cited By

View all
  • (2024)Impact of gain-loss framing on online scam susceptibility: the role of scam frames, warning frames, and risk perceptionBehaviour & Information Technology10.1080/0144929X.2024.2378883(1-14)Online publication date: 23-Jul-2024
  • (2022)A Two-Fold Study to Investigate Users’ Perception of IoT Information Sensitivity Levels and Their Willingness to Share the InformationEmerging Information Security and Applications10.1007/978-3-030-93956-4_6(87-107)Online publication date: 12-Jan-2022
  • (2021)What’s in a Cyber Threat Intelligence sharing platform?Proceedings of the 37th Annual Computer Security Applications Conference10.1145/3485832.3488030(385-398)Online publication date: 6-Dec-2021
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
WISCS '16: Proceedings of the 2016 ACM on Workshop on Information Sharing and Collaborative Security
October 2016
88 pages
ISBN:9781450345651
DOI:10.1145/2994539
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 October 2016

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. cybersecurity data sharing
  2. data usage
  3. personal privacy
  4. risk perception

Qualifiers

  • Research-article

Funding Sources

Conference

CCS'16
Sponsor:

Acceptance Rates

WISCS '16 Paper Acceptance Rate 8 of 24 submissions, 33%;
Overall Acceptance Rate 23 of 58 submissions, 40%

Upcoming Conference

CCS '25

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)550
  • Downloads (Last 6 weeks)58
Reflects downloads up to 22 Dec 2024

Other Metrics

Citations

Cited By

View all
  • (2024)Impact of gain-loss framing on online scam susceptibility: the role of scam frames, warning frames, and risk perceptionBehaviour & Information Technology10.1080/0144929X.2024.2378883(1-14)Online publication date: 23-Jul-2024
  • (2022)A Two-Fold Study to Investigate Users’ Perception of IoT Information Sensitivity Levels and Their Willingness to Share the InformationEmerging Information Security and Applications10.1007/978-3-030-93956-4_6(87-107)Online publication date: 12-Jan-2022
  • (2021)What’s in a Cyber Threat Intelligence sharing platform?Proceedings of the 37th Annual Computer Security Applications Conference10.1145/3485832.3488030(385-398)Online publication date: 6-Dec-2021
  • (2021)PHIN: A Privacy Protected Heterogeneous IoT NetworkResearch Challenges in Information Science10.1007/978-3-030-75018-3_8(124-141)Online publication date: 8-May-2021
  • (2020)Managing Big Data for Addressing Research Questions in a Collaborative Project on Automated Driving Impact AssessmentSensors10.3390/s2023677320:23(6773)Online publication date: 27-Nov-2020
  • (2020)Privacy Adversarial NetworkProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/33698163:4(1-18)Online publication date: 14-Sep-2020
  • (2020)BHDA - A Blockchain-Based Hierarchical Data Access Model for Financial Services2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)10.1109/TrustCom50675.2020.00077(530-538)Online publication date: Dec-2020
  • (2020)Approach to Mitigate the Cyber-Environment Risks of a Technology Platform2020 3rd International Conference on Information and Computer Technologies (ICICT)10.1109/ICICT50521.2020.00069(390-396)Online publication date: Mar-2020
  • (2019)Prototype to Mitigate the Risks of the Integrity of Cyberattack Information in Electoral Processes in Latin AmericaProceedings of the 2019 2nd International Conference on Education Technology Management10.1145/3375900.3375915(111-118)Online publication date: 18-Dec-2019
  • (2019)GDPR Compliance in Cybersecurity SoftwareProceedings of the 14th International Conference on Availability, Reliability and Security10.1145/3339252.3340516(1-8)Online publication date: 26-Aug-2019
  • Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Login options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media