000			01881naa a2200169uu 4500
001			5121310171310
003			OSt
005			20190211160323.0
008			051213s2005 xx ||||gr |0|| 0 eng d
100	1		_aSEIFERT, Jeffrey W _99761
245	1	0	_aData mining and the search for security : _bchallenges for connecting the dots and databases
260			_aOrlando : _bElsevier, _c2004
520	3		_aData mining is emerging as one of the key features of many homeland security initiatives. Often used as a means for detecting fraud, assessing risk, and product retailing, data mining involves the use of data analysis tools to discover previously unknown, valid patterns and relationships in large data sets. In the context of homeland security, data mining is often viewed as a potential means to identify terrorist activities, such as money transfers and communications, and to identify and track individual terrorists themselves, such as through travel and immigration records. However, compared to earlier uses of data mining by government, some of the homeland security data mining applications represent a significant expansion in the quantity and scope of data to be analyzed. Three of the higher profile initiatives include the now defunct Terrorism Information Awareness (TIA) project, the recently canceled Computer-Assisted Passenger Prescreening System II (CAPPS II), and the Multistate Anti-Terrorism Information Exchange (MATRIX) pilot project. This article examines the evolving nature of data mining for homeland security purposes, the limitations of data mining, and some of the issues raised by its expanding use, including data quality, interoperability, mission creep, and privacy
773	0	8	_tGovernment Information Quarterly _g21, 4, p. 461-480 _dOrlando : Elsevier, 2004 _xISSN 0740-624X _w
942			_cS
998			_a20051213 _b1017^b _cTiago
999			_aConvertido do Formato PHL _bPHL2MARC21 1.1 _c14236 _d14236
041			_aeng