research-article

Public Information Exposure Detection: Helping Users Understand Their Web Footprints

Authors:

Grace Hui Yang,

Andrew Hian-Cheong,

Sicong ZhangAuthors Info & Claims

ASONAM '15: Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015

Pages 153 - 161

https://doi.org/10.1145/2808797.2809280

Published: 25 August 2015 Publication History

Abstract

To help users better understand the potential risks associated with publishing data publicly, as well as the quantity and sensitivity of information that can be obtained by combining data from various online sources, we introduce a novel information exposure detection framework that generates and analyzes the web footprints users leave across the social web. Web footprints are the traces of one's online social activities represented by a set of attributes that are known or can be inferred with a high probability by an adversary who has basic information about a user from his/her public profiles. Our framework employs new probabilistic operators, novel pattern-based attribute extraction from text, and a population-based inference engine to generate web footprints. Using a web footprint, the framework then quantifies a user's level of information exposure relative to others with similar traits, as well as with regard to others in the population. Evaluation over public profiles from multiple sites (Google+, LinkeIn, FourSquare, and Twitter) shows that the proposed framework effectively detects and quantifies information exposure using a small amount of initial knowledge.

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Cited By

Singh LGresenz C(2023)Social Media Data for Firearms Research: Promise and PerilsThe ANNALS of the American Academy of Political and Social Science10.1177/00027162231174320704:1(267-291)Online publication date: 20-Jun-2023
https://doi.org/10.1177/00027162231174320
Liu SSingh LTian K(2020)Information Exposure From Relational Background Knowledge on Social Media2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA)10.1109/DSAA49011.2020.00041(282-291)Online publication date: Oct-2020
https://doi.org/10.1109/DSAA49011.2020.00041
Weinshel BWei MMondal MChoi EShan SDolin CMazurek MUr BCavallaro LKinder JWang XKatz J(2019)Oh, the Places You've Been! User Reactions to Longitudinal Transparency About Third-Party Web Tracking and InferencingProceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security10.1145/3319535.3363200(149-166)Online publication date: 6-Nov-2019
https://dl.acm.org/doi/10.1145/3319535.3363200
Show More Cited By

Public Information Exposure Detection: Helping Users Understand Their Web Footprints
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
2. Information systems
  1. Information systems applications

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cover image ACM Conferences

ASONAM '15: Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015

August 2015

835 pages

ISBN:9781450338547

DOI:10.1145/2808797

Copyright © 2015 ACM.

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]

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Published: 25 August 2015

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ASONAM '15: Advances in Social Networks Analysis and Mining 2015

August 25 - 28, 2015

Paris, France

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Overall Acceptance Rate 116 of 549 submissions, 21%

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Cited By

Singh LGresenz C(2023)Social Media Data for Firearms Research: Promise and PerilsThe ANNALS of the American Academy of Political and Social Science10.1177/00027162231174320704:1(267-291)Online publication date: 20-Jun-2023
https://doi.org/10.1177/00027162231174320
Liu SSingh LTian K(2020)Information Exposure From Relational Background Knowledge on Social Media2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA)10.1109/DSAA49011.2020.00041(282-291)Online publication date: Oct-2020
https://doi.org/10.1109/DSAA49011.2020.00041
Weinshel BWei MMondal MChoi EShan SDolin CMazurek MUr BCavallaro LKinder JWang XKatz J(2019)Oh, the Places You've Been! User Reactions to Longitudinal Transparency About Third-Party Web Tracking and InferencingProceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security10.1145/3319535.3363200(149-166)Online publication date: 6-Nov-2019
https://dl.acm.org/doi/10.1145/3319535.3363200
Tadic BRohde MWulf V(2018)CyberActivist: Tool for Raising Awareness on Privacy and Security of Social Media Use for ActivistsSocial Computing and Social Media. User Experience and Behavior10.1007/978-3-319-91521-0_36(498-510)Online publication date: 31-May-2018
https://doi.org/10.1007/978-3-319-91521-0_36
Yang HSoboroff IXiong LClarke CGarfinkel SPerego RSebastiani FAslam JRuthven IZobel J(2016)Privacy-Preserving IR 2016Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval10.1145/2911451.2917763(1247-1248)Online publication date: 7-Jul-2016
https://dl.acm.org/doi/10.1145/2911451.2917763
Singh L(2016)Data Ethics—Attaining Personal Privacy on the WebEthical Reasoning in Big Data10.1007/978-3-319-28422-4_7(81-90)Online publication date: 23-Apr-2016
https://doi.org/10.1007/978-3-319-28422-4_7

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