Abstract
Every form a user fills out, every click a user makes on a website, every comment or recommendation a user posts about a product creates a new data point that is being used by companies and researchers to better understand and potentially infer human behavior. In this chapter we highlight cases when companies and/or researchers stepped over the boundary of ethically reasonable uses of big data or manipulated individuals online without their expressed consent. We describe tools that members of the American public could use to improve the level of user privacy on the Internet and to gain more control over their data. Yet, recognizing the limits of individual protections, we also argue that the time has come to launch a public discussion about ethical uses of large-scale human behavioral data. We should develop guidelines and regulations that protect users while still allowing companies and researchers the ability to advance knowledge about human behavior in responsible ways.
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References
Angwin, J. (2010). The web’s new gold mine: Your secrets. Retrieved November 01, 2015, from http://www.wsj.com/articles/SB10001424052748703940904575395073512989404.
Bacher, P., Holz, T., Kotter, M., & Wicherski, G. (2008). Know your enemy: Tracking botnets. Retrieved November 01, 2015, from https://www.honeynet.org/papers/bots.
Burstein, A. (2008). Conducting cybersecurity research legally and ethically. In Usenix workshop on large-scale exploits and emergent threats.
Chambers, C. (2014). Facebook fiasco was Cornell’s study of ‘emotional contagion’ an ethics breach? Retrieved November 01, 2015, from http://www.theguardian.com/science/head-quarters/2014/jul/01/facebook-cornell-study-emotional-contagion-ethics-breach.
Duhigg, C. (2012). How companies learn your secrets. Retrieved November 01, 2015, from http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html.
Dwork, C. (2008). Differential privacy: A survey of results. In Theory and applications of models of computation (pp. 1–19). Springer.
EPIC. (2015). Online tracking and behavioral profiling. Retrieved November 01, 2015, from http://epic.org/privacy/consumer/online_tracking_and_behavioral.html.
Fang, L., & LeFevre, K. (2010). Privacy wizards for social networking sites. In ACM world wide web conference (www).
Gorski, D. (2014). Did Facebook and PNAS violate human research protections in an unethical experiment? Retrieved November 01, 2015, from https://www.sciencebasedmedicine.org/did-facebook-and-pnas-violate-human-research-protections-in-an-unethical-experiment/.
Gundecha, P., Barbier, G., & Liu, H. (2011). Exploiting vulnerability to secure user privacy on a social networking site. In Proceedings of the 17 th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 511–519). ACM.
Hill, K. (2012). How target figured out a teen girl was pregnant before her father did. Retrieved November 01, 2015, from http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/.
Irani, D., Webb, S., Li, K., & Pu, C. (2009). Large online social footprints—An emerging threat. In International conference on computational science and engineering.
Jolly, I. (2015). Data protection in united states: Overview. Retrieved November 01, 2015, from http://us.practicallaw.com/6-502-0467.
Kanich, C., Kreibich, C., Levchenko, K., Enright, B., Voelker, G. M., Paxson, V., Savage, S. et al. (2008, October). Spamalytics: An empirical analysis of spam marketing conversion. In Acm conference on computer and communications security (pp. 3–14). Alexandria, Virginia, USA.
Kramer, A., Guillory, J., & Hancock, J. (2014). Experimental evidence of massive-scale emotional contagion through social networks. Proceedings of the National Academy of Science, 111(42), 8788–8790.
Li, N., Li, T., & Venkatasubramanian, S. (2007, April). t-closeness: Privacy beyond k- anonymity and l-diversity. In Proceedings of the International Conference on Data Engineering (ICDE).
Lucas, M.M., & Borisov, N. (2008). FlyByNight: Mitigating the privacy risks of social networking. In Acm Workshop on Privacy in the Electronic Society (WPES).
Luo, W., Xie, Q., & Hengartner, U. (2009). FaceCloak: An architecture for user privacy on social networking sites. In International Conference on Computational Science 13 and Engineering (CSE).
Machanavajjhala, A., Gehrke, J., & Kifer, D. (2007). l-diversity: Privacy beyond k- anonymity. ACM Transactions on Knowledge Discovery from Data, 1(1).
Madden, M. (2014). Public perceptions of privacy and security in the post-snowden era. Retrieved November 01, 2015, from http://www.pewinternet.org/2014/11/12/public-privacy-perceptions/.
McCandlish, S. (2002). EFF’s top 12 ways to protect your online privacy. Retrieved November 01, 2015, from https://www.eff.org/wp/effs-top-12-ways-protect-your-online-privacy/.
Neagu, A. (2014). 11 steps to dramatically improve your online privacy in less than 1 hour. Retrieved November 01, 2015, from https://heimdalsecurity.com/blog/online-privacy-essential-guide/.
Olsen, S. (2002). Nearly undetectable tracking device raises concern. Retrieved November 01, 2015, from http://www.cnet.com/news/nearly-undetectable-tracking-device-raises-concern/.
Paxson, V. (2004). Strategies for sound internet measurement. In Acm Sigcomm Conference on Internet Measurement. New York, USA: ACM.
Real Time Statistics Project. (2015). Internet live statistics. Retrieved November 01, 2015, from http://www.internetlivestats.com/.
SACHRP-HHS. (2013). Considerations and recommendations concerning internet research and human subjects research regulations, with revisions. Retrieved November 01, 2015, from http://www.hhs.gov/ohrp/sachrp/mtgings/2013%20March%20Mtg/internet_research.pdf.
Samarati, P., & Sweeney, L. (1998). Protecting privacy when disclosing information k-anonymity and its enforcement through generalization and suppression. In Proceedings of the IEEE Symposium on Research in Security and Privacy.
Schmitz, D.T. (2013). 5 ways to improve your privacy online. Retrieved November 01, 2015, from http://www.technewsworld.com/story/78590.html.
Siege, E. (2013). Predictive analytics: The power to predict who will click, buy, lie, or die. John Wiley & Sons.
Singh, L., Yang, H., Sherr, M., Hian-Cheong, A., Tian, K., Zhu, J., Zhang, S. et al. (2015). Public information exposure detection: Helping users understand their web footprints. In International Conference on Advances in Social Networks Analysis and Mining (asonam). Paris, France.
Smith, C. (2015). How many people use 950+ of the top social media, apps, and digital services? Retrieved November 01, 2015, from http://expandedramblings.com/index.php/resource-how-many-people-use-the-top-social-media/.
Soper, D. (2012, April). Is human mobility tracking a good idea? Communications of ACM, 55(4), 35–37.
Tompsett, B. (2005). Identity theft in an onlineworld. Computer Law Security Report, 21(2).
Valentino-Devries, J. (2010). How to avoid the prying eyes. Retrieved November 01, 2015, from http://www.wsj.com/articles/SB10001424052748703467304575383203092034876.
Waldman, K. (2014). Facebook’s unethical experiment. Retrieved November 01, 2015, from http://www.slate.com/articles/health_and_science/science/2014/06/facebook_unethical_experiment_it_made_news_feeds_happier_or_sadder_to_manipulate.html.
Zhou, B., Pei, J., & Luk, W. (2008, December). A brief survey on anonymization techniques for privacy preserving publishing of social network data. ACM SIGKDD Explorations Newsletter, 10(2).
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This work was supported by NSF CNS-1223825 and NSF IIS-1522745. The opinions and findings described in this paper are those of the author and do not necessarily reflect the views of the National Science Foundation.
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Singh, L. (2016). Data Ethics—Attaining Personal Privacy on the Web. In: Collmann, J., Matei, S. (eds) Ethical Reasoning in Big Data. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-28422-4_7
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DOI: https://doi.org/10.1007/978-3-319-28422-4_7
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