Quotation Vamosi, Stefan, Platzer, Michael, Reutterer, Thomas. 2022. AI-based Re-identification of Behavioral Clickstream Data.


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Abstract

AI-based face recognition, i.e., the re-identification of individuals within images, is an already well established technology for video surveillance, for user authentication, for tagging photos of friends, etc. This paper demonstrates that similar techniques can be applied to successfully re-identify individuals purely based on their behavioral patterns. In contrast to de-anonymization attacks based on record linkage, these methods do not require any overlap in data points between a released dataset and an identified auxiliary dataset. The mere resemblance of behavioral patterns between records is sufficient to correctly attribute behavioral data to identified individuals. Further, we can demonstrate that data perturbation does not provide protection, unless a significant share of data utility is being destroyed. These findings call for sincere cautions when sharing actual behavioral data with third parties, as modern-day privacy regulations, like the GDPR, define their scope based on the ability to re-identify. This has also strong implications for the Marketing domain, when dealing with potentially re-identify-able data sources like shopping behavior, clickstream data or cockies. We also demonstrate how synthetic data can offer a viable alternative, that is shown to be resilient against our introduced AI-based re-identification attacks.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Working/discussion paper, preprint
Language English
Title AI-based Re-identification of Behavioral Clickstream Data
Year 2022
URL https://arxiv.org/pdf/2201.10351.pdf

Associations

People
Vamosi, Stefan (Former researcher)
Platzer, Michael (Former researcher)
Reutterer, Thomas (Details)
Organization
Institute for Marketing and Customer Analytics IN (Details)
Research Institute for Computational Methods FI (Details)
Research Institute for Cryptoeconomics FI (Details)
Research areas (Ă–STAT Classification 'Statistik Austria')
5301 Distributive trades (Details)
5307 Business and management economics (Details)
5315 Commercial science (Details)
5320 Marketing (Details)
5321 Market research (Details)
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