Privacy and Confidentiality in an e-Commerce World: Data Mining, Data Warehousing, Matching and Disclosure Limitation

The growing expanse of e-commerce and the widespread availability of online databases raise many fears regarding loss of privacy and many statistical challenges. Even with encryption and other nominal forms of protection for individual databases, we still need to protect against the violation of privacy through linkages across multiple databases. These issues parallel those that have arisen and received some attention in the context of homeland security. Following the events of September 11, 2001, there has been heightened attention in the United States and elsewhere to the use of multiple government and private databases for the identification of possible perpetrators of future attacks, as well as an unprecedented expansion of federal government data mining activities, many involving databases containing personal information. We present an overview of some proposals that have surfaced for the search of multiple databases which supposedly do not compromise possible pledges of confidentiality to the individuals whose data are included. We also explore their link to the related literature on privacy-preserving data mining. In particular, we focus on the matching problem across databases and the concept of ``selective revelation'' and their confidentiality implications.Comment: Published at http://dx.doi.org/10.1214/088342306000000240 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Comment: Complex Causal Questions Require Careful Model Formulation: Discussion of Rubin on Experiments with "Censoring" Due to Death

Comment on Complex Causal Questions Require Careful Model Formulation: Discussion of Rubin on Experiments with ``Censoring'' Due to Death [math.ST/0612783]Comment: Published at http://dx.doi.org/10.1214/088342306000000295 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

William Kruskal: My Scholarly and Scientific Model

Discussion of ``The William Kruskal Legacy: 1919--2005'' by Stephen E. Fienberg, Stephen M. Stigler and Judith M. Tanur [arXiv:0710.5063]Comment: Published in at http://dx.doi.org/10.1214/088342306000000376 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Introduction to papers on the modeling and analysis of network data

Introduction to papers on the modeling and analysis of network dataComment: Published in at http://dx.doi.org/10.1214/10-AOAS346 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Editorial: Statistics and forensic science

Forensic science is usually taken to mean the application of a broad spectrum of scientific tools to answer questions of interest to the legal system. Despite such popular television series as CSI: Crime Scene Investigation and its spinoffs--CSI: Miami and CSI: New York--on which the forensic scientists use the latest high-tech scientific tools to identify the perpetrator of a crime and always in under an hour, forensic science is under assault, in the public media, popular magazines [Talbot (2007), Toobin (2007)] and in the scientific literature [Kennedy (2003), Saks and Koehler (2005)]. Ironically, this growing controversy over forensic science has occurred precisely at the time that DNA evidence has become the ``gold standard'' in the courts, leading to the overturning of hundreds of convictions many of which were based on clearly less credible forensic evidence, including eyewitness testimony [Berger (2006)].Comment: Published in at http://dx.doi.org/10.1214/07-AOAS140 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Editorial: Statistics and "The lost tomb of Jesus"

What makes a problem suitable for statistical analysis? Are historical and religious questions addressable using statistical calculations? Such issues have long been debated in the statistical community and statisticians and others have used historical information and texts to analyze such questions as the economics of slavery, the authorship of the Federalist Papers and the question of the existence of God. But what about historical and religious attributions associated with information gathered from archeological finds? In 1980, a construction crew working in the Jerusalem neighborhood of East Talpiot stumbled upon a crypt. Archaeologists from the Israel Antiquities Authority came to the scene and found 10 limestone burial boxes, known as ossuaries, in the crypt. Six of these had inscriptions. The remains found in the ossuaries were reburied, as required by Jewish religious tradition, and the ossuaries were catalogued and stored in a warehouse. The inscriptions on the ossuaries were catalogued and published by Rahmani (1994) and by Kloner (1996) but there reports did not receive widespread public attention. Fast forward to March 2007, when a television ``docudrama'' aired on The Discovery Channel entitled ``The Lost Tomb of Jesus'' touched off a public and religious controversy--one only need think about the title to see why there might be a controversy! The program, and a simultaneously published book [Jacobovici and Pellegrino (2007)], described the ``rediscovery'' of the East Talpiot archeological find and they presented interpretations of the ossuary inscriptions from a number of perspectives. Among these was a statistical calculation attributed to the statistician Andrey Feuerverger: ``that the odds that all six names would appear together in one tomb are 1 in 600, calculated conservatively--or possibly even as much as one in one million.''Comment: Published in at http://dx.doi.org/10.1214/08-AOAS162 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org