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  • 1
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    American Association for the Advancement of Science (AAAS)
    Publication Date: 2015-04-11
    Description: 〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉de Montjoye, Yves-Alexandre -- Pentland, Alex Sandy -- New York, N.Y. -- Science. 2015 Apr 10;348(6231):195. doi: 10.1126/science.348.6231.195-a.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. yvesalexandre@demontjoye.com. ; Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25859038" target="_blank"〉PubMed〈/a〉
    Keywords: *Commerce ; *Data Collection ; Female ; Humans ; *Information Dissemination ; Male ; *Privacy
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 2
    Publication Date: 2015-01-31
    Description: Large-scale data sets of human behavior have the potential to fundamentally transform the way we fight diseases, design cities, or perform research. Metadata, however, contain sensitive information. Understanding the privacy of these data sets is key to their broad use and, ultimately, their impact. We study 3 months of credit card records for 1.1 million people and show that four spatiotemporal points are enough to uniquely reidentify 90% of individuals. We show that knowing the price of a transaction increases the risk of reidentification by 22%, on average. Finally, we show that even data sets that provide coarse information at any or all of the dimensions provide little anonymity and that women are more reidentifiable than men in credit card metadata.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉de Montjoye, Yves-Alexandre -- Radaelli, Laura -- Singh, Vivek Kumar -- Pentland, Alex Sandy -- New York, N.Y. -- Science. 2015 Jan 30;347(6221):536-9. doi: 10.1126/science.1256297.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Media Lab, Massachusetts Institute of Technology (MIT), 20 Amherst Street, Cambridge, MA 02139, USA. yvesalexandre@demontjoye.com. ; Department of Computer Science, Aarhus University, Aabogade 34, Aarhus, 8200, Denmark. ; Media Lab, Massachusetts Institute of Technology (MIT), 20 Amherst Street, Cambridge, MA 02139, USA. School of Communication and Information, Rutgers University, 4 Huntington Street, New Brunswick, NJ 08901, USA. ; Media Lab, Massachusetts Institute of Technology (MIT), 20 Amherst Street, Cambridge, MA 02139, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25635097" target="_blank"〉PubMed〈/a〉
    Keywords: *Commerce ; *Data Collection ; Female ; Humans ; Income ; *Information Dissemination ; Male ; *Privacy ; Sex Characteristics
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 3
    Publication Date: 2016-03-19
    Description: Sanchez et al.'s textbook k-anonymization example does not prove, or even suggest, that location and other big-data data sets can be anonymized and of general use. The synthetic data set that they "successfully anonymize" bears no resemblance to modern high-dimensional data sets on which their methods fail. Moving forward, deidentification should not be considered a useful basis for policy.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉de Montjoye, Yves-Alexandre -- Pentland, Alex Sandy -- New York, N.Y. -- Science. 2016 Mar 18;351(6279):1274. doi: 10.1126/science.aaf1578.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Harvard University, Institute for Quantitative Social Science, Cambridge, MA 02138, USA. yvesalexandre@demontjoye.com. ; Massachusetts Institute of Technology, Cambridge, MA 02139, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26989244" target="_blank"〉PubMed〈/a〉
    Keywords: *Commerce ; *Data Collection ; Female ; Humans ; *Information Dissemination ; Male ; *Privacy
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 4
    Publication Date: 2016-08-31
    Description: Most theories of motivation have highlighted that human behavior is guided by the hedonic principle, according to which our choices of daily activities aim to minimize negative affect and maximize positive affect. However, it is not clear how to reconcile this idea with the fact that people routinely engage in...
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
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