What's in the community cookie jar?

Aaron Cahn; Scott Alfeld; Paul Barford; S. Muthukrishnan

doi:10.1109/ASONAM.2016.7752292

What's in the community cookie jar?

Aaron Cahn, Scott Alfeld, Paul Barford, S. Muthukrishnan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Third party tracking of user behavior via web cookies represents a privacy threat. In this paper we assess this threat through an analysis of anonymized, crowdsourced cookie data provided by Cookiepedia.co.uk. We find that nearly 45% of the cookies in the corpus are from Facebook and of the remaining cookies 25% come from 10 distinct domains. Over 65% are Maximal Permission cookies (i.e., 3rd party, non-secure, persistent, root-level). Cookiepedia's anonymization of user data presents challenges with respect to modeling site traffic. We further elucidate the privacy issue by conducting targeted crawling campaigns to supplement the Cookiepedia data. We find that the amount of traffic obscured by Cookiepedia's anonymizing procedure varies dramatically from site to site - sometimes obscuring as much as 80% of traffic. We use the crawls to infer the inverse function of the anonymizing procedure, allowing us to enhance the crowdsourced dataset while maintaining user anonymity.

Original language	English (US)
Title of host publication	Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
Editors	Ravi Kumar, James Caverlee, Hanghang Tong
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	567-570
Number of pages	4
ISBN (Electronic)	9781509028467
DOIs	https://doi.org/10.1109/ASONAM.2016.7752292
State	Published - Nov 21 2016
Event	2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 - San Francisco, United States Duration: Aug 18 2016 → Aug 21 2016

Publication series

Name	Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016

Conference

Conference	2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
Country/Territory	United States
City	San Francisco
Period	8/18/16 → 8/21/16

ASJC Scopus subject areas

Computer Networks and Communications
Sociology and Political Science
Communication

Access to Document

10.1109/ASONAM.2016.7752292

Cite this

Cahn, A., Alfeld, S., Barford, P., & Muthukrishnan, S. (2016). What's in the community cookie jar? In R. Kumar, J. Caverlee, & H. Tong (Eds.), Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 (pp. 567-570). Article 7752292 (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASONAM.2016.7752292

What's in the community cookie jar? / Cahn, Aaron; Alfeld, Scott; Barford, Paul et al.
Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016. ed. / Ravi Kumar; James Caverlee; Hanghang Tong. Institute of Electrical and Electronics Engineers Inc., 2016. p. 567-570 7752292 (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Cahn, A, Alfeld, S, Barford, P & Muthukrishnan, S 2016, What's in the community cookie jar? in R Kumar, J Caverlee & H Tong (eds), Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016., 7752292, Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016, Institute of Electrical and Electronics Engineers Inc., pp. 567-570, 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016, San Francisco, United States, 8/18/16. https://doi.org/10.1109/ASONAM.2016.7752292

Cahn A, Alfeld S, Barford P, Muthukrishnan S. What's in the community cookie jar? In Kumar R, Caverlee J, Tong H, editors, Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 567-570. 7752292. (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016). doi: 10.1109/ASONAM.2016.7752292

Cahn, Aaron ; Alfeld, Scott ; Barford, Paul et al. / What's in the community cookie jar?. Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016. editor / Ravi Kumar ; James Caverlee ; Hanghang Tong. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 567-570 (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016).

@inproceedings{d95edfbe6f114c32825bd14bef33e7ec,

title = "What's in the community cookie jar?",

abstract = "Third party tracking of user behavior via web cookies represents a privacy threat. In this paper we assess this threat through an analysis of anonymized, crowdsourced cookie data provided by Cookiepedia.co.uk. We find that nearly 45% of the cookies in the corpus are from Facebook and of the remaining cookies 25% come from 10 distinct domains. Over 65% are Maximal Permission cookies (i.e., 3rd party, non-secure, persistent, root-level). Cookiepedia's anonymization of user data presents challenges with respect to modeling site traffic. We further elucidate the privacy issue by conducting targeted crawling campaigns to supplement the Cookiepedia data. We find that the amount of traffic obscured by Cookiepedia's anonymizing procedure varies dramatically from site to site - sometimes obscuring as much as 80% of traffic. We use the crawls to infer the inverse function of the anonymizing procedure, allowing us to enhance the crowdsourced dataset while maintaining user anonymity.",

author = "Aaron Cahn and Scott Alfeld and Paul Barford and S. Muthukrishnan",

note = "Funding Information: The authors would like to thank Cookiepedia for supplying the data used in this study. This material is based upon work supported by the DHS grant BAA 11-01 and AFRL grant FA8750-12-2-0328. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not reflect the views of the DHS or AFRL Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 ; Conference date: 18-08-2016 Through 21-08-2016",

year = "2016",

month = nov,

day = "21",

doi = "10.1109/ASONAM.2016.7752292",

language = "English (US)",

series = "Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "567--570",

editor = "Ravi Kumar and James Caverlee and Hanghang Tong",

booktitle = "Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016",