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Privacy in e-Shopping Transactions: Exploring and Addressing the Trade-Offs

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Cyber Security Cryptography and Machine Learning (CSCML 2018)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10879))

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Abstract

The huge growth of e-shopping has brought convenience to customers, increased revenue to merchants and financial entities and evolved to possess a rich set of functionalities and requirements (e.g., regulatory ones). However, enhancing customer privacy remains to be a challenging problem; while it is easy to create a simple system with privacy, this typically causes loss of functions.

In this work, we look into current e-shopping infrastructures and aim at enhancing customer privacy while retaining important features and requiring the system to maintain the topology and transaction flow of established e-shopping systems that are currently operational. Thus, we apply what we call the “utility, privacy, and then utility again” paradigm: we start from the state of the art of e-shopping (utility); then we add privacy enhancing mechanisms, reducing its functionality in order to tighten privacy to the fullest (privacy); and finally, we incorporate tools which add back lost features, carefully relaxing privacy this time (utility again).

We also implemented and tested our design, verifying its reasonable added costs.

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Notes

  1. 1.

    https://www.eugdpr.org/.

  2. 2.

    https://ec.europa.eu/info/law/payment-services-psd-2-directive-eu-2015-2366_en.

  3. 3.

    As well as many proposals in non-academic forums. See, for instance, https://z.cash/ (a modified implementation of Zerocash) and https://cryptonote.org/.

  4. 4.

    Key-privacy security requires that an eavesdropper in possession of a ciphertext not be able to tell which specific key, out of a set of known public keys, is the one under which the ciphertext was created, meaning the receiver is anonymous from the point of view of the adversary.

  5. 5.

    https://en.wikipedia.org/wiki/Address_Verification_System.

  6. 6.

    https://magento.com/sites/default/files/White%20Paper%20-%20Magento%202.0%20Performance%20and%20Scalability%2003.31.16.pdf.

  7. 7.

    https://usa.visa.com/dam/VCOM/global/about-visa/documents/visa-facts-figures-jan-2017.pdf.

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Acknowledgements

The work of Jesus Diaz was done in part while visiting the Network Security Lab at Columbia University. The work of Seung Geol Choi was supported in part by the Office of Naval Research under Grant Number N0001415WX01232. The work of David Arroyo was supported by projects S2013/ICE-3095-CM (CIBERDINE) and MINECO DPI2015-65833-P of the Spanish Government. The work of Francisco B. Rodriguez was supported by projects MINECO TIN2014-54580-R and TIN2017-84452-R of the Spanish Government. The work of Moti Yung was done in part while visiting the Simons Institute for Theory of Computing, UC Berkeley.

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Authors and Affiliations

  1. Blue Indico - BEEVA, Madrid, Spain

    Jesus Diaz

  2. United States Naval Academy, Annapolis, USA

    Seung Geol Choi

  3. Universidad Autónoma de Madrid, Madrid, Spain

    David Arroyo & Francisco B. Rodriguez

  4. Georgia Institute of Technology, Atlanta, USA

    Angelos D. Keromytis

  5. Columbia University, New York, USA

    Moti Yung

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  1. Jesus Diaz
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Correspondence to Jesus Diaz .

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Editors and Affiliations

  1. Ben-Gurion University of the Negev, Beer Sheva, Israel

    Itai Dinur

  2. Ben-Gurion University of the Negev, Beer Sheva, Israel

    Shlomi Dolev

  3. Tata Consultancy Services (India), Chennai, Tamil Nadu, India

    Sachin Lodha

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Diaz, J., Choi, S.G., Arroyo, D., Keromytis, A.D., Rodriguez, F.B., Yung, M. (2018). Privacy in e-Shopping Transactions: Exploring and Addressing the Trade-Offs. In: Dinur, I., Dolev, S., Lodha, S. (eds) Cyber Security Cryptography and Machine Learning. CSCML 2018. Lecture Notes in Computer Science(), vol 10879. Springer, Cham. https://doi.org/10.1007/978-3-319-94147-9_17

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  • DOI: https://doi.org/10.1007/978-3-319-94147-9_17

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