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Showing 1–12 of 12 results
Advanced filters: Author: Yves-Alexandre de Montjoye Clear advanced filters

  • Advanced machine learning techniques have demonstrated the identifiability of human traces online, however, assessment of their potential risks is usually done with small-scale datasets. The authors propose a physics-based approach to evaluate the effectiveness of identification techniques from reported measurements.

    • Luc Rocher
    • Julien M. Hendrickx
    • Yves-Alexandre de Montjoye
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-11

  • Large language models learn from, and often memorize, training data. Here, authors show they memorize far more than previously thought, by stitching together pieces of text like a mosaic. This makes it difficult to control and challenges widely used practices for benchmarking and protecting privacy.

    • Igor Shilov
    • Matthieu Meeus
    • Yves-Alexandre de Montjoye
    ResearchOpen Access
    Nature Communications
    Volume: 17, P: 1-21

  • Anonymization has been the main means of addressing privacy concerns in sharing medical and socio-demographic data. Here, the authors estimate the likelihood that a specific person can be re-identified in heavily incomplete datasets, casting doubt on the adequacy of current anonymization practices.

    • Luc Rocher
    • Julien M. Hendrickx
    • Yves-Alexandre de Montjoye
    ResearchOpen Access
    Nature Communications
    Volume: 10, P: 1-9

  • Large amounts of interaction data are collected by messaging apps, mobile phone carriers, and social media. Creţu et al. propose a behavioral profiling attack model and show that the stability of people’s interaction networks over time can allow individuals to be re-identified in interaction datasets.

    • Ana-Maria Creţu
    • Federico Monti
    • Yves-Alexandre de Montjoye
    ResearchOpen Access
    Nature Communications
    Volume: 13, P: 1-11

  • Online commerce is increasingly relying on pricing algorithms. Using a network-based approach inspired by adversarial machine learning, a firm can learn the strategy of its competitors and use it to unilaterally increase all firms’ profits. This approach, termed as ‘adversarial collusion’, calls for new regulatory measures.

    • Luc Rocher
    • Arnaud J. Tournier
    • Yves-Alexandre de Montjoye
    Research
    Nature Machine Intelligence
    Volume: 5, P: 497-504

  • The breadcrumbs we leave behind when using our mobile phones—who somebody calls, for how long, and from where—contain unprecedented insights about us and our societies. Researchers have compared the recent availability of large-scale behavioral datasets, such as the ones generated by mobile phones, to the invention of the microscope, giving rise to the new field of computational social science.

    • Yves-Alexandre de Montjoye
    • Sébastien Gambs
    • Linus Bengtsson
    Comments & OpinionOpen Access
    Scientific Data
    Volume: 5, P: 1-6