标题：Data Mining and Homeland Security—An Overview
      作者：Jeffrey W. Seifert
      时间：20070118
      语言：English
      摘要：Data mining has become 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 can be 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.
While data mining represents a significant advance in the type of analytical tools
currently available, there are limitations to its capability. One limitation is that
although data mining can help reveal patterns and relationships, it does not tell the
user the value or significance of these patterns. These types of determinations must
be made by the user. A second limitation is that while data mining can identify
connections between behaviors and/or variables, it does not necessarily identify a
causal relationship. Successful data mining still requires skilled technical and
analytical specialists who can structure the analysis and interpret the output.
Data mining is becoming increasingly common in both the private and public
sectors. Industries such as banking, insurance, medicine, and retailing commonly use
data mining to reduce costs, enhance research, and increase sales. In the public
sector, data mining applications initially were used as a means to detect fraud and
waste, but have grown to also be used for purposes such as measuring and improving
program performance. However, some of the homeland security data mining
applications represent a significant expansion in the quantity and scope of data to be
analyzed. Some efforts that have attracted a higher level of congressional interest
include the Terrorism Information Awareness (TIA) project (now-discontinued) and
the Computer-Assisted Passenger Prescreening System II (CAPPS II) project (nowcanceled
and replaced by Secure Flight). Other initiatives that have been the subject
of congressional interest include the Multi-State Anti-Terrorism Information
Exchange (MATRIX), the Able Danger program, the Automated Targeting System
(ATS), and data collection and analysis projects being conducted by the National
Security Agency (NSA).
As with other aspects of data mining, while technological capabilities are
important, there are other implementation and oversight issues that can influence the
success of a project’s outcome. One issue is data quality, which refers to the
accuracy and completeness of the data being analyzed. A second issue is the
interoperability of the data mining software and databases being used by different
agencies. A third issue is mission creep, or the use of data for purposes other than
for which the data were originally collected. A fourth issue is privacy. Questions
that may be considered include the degree to which government agencies should use
and mix commercial data with government data, whether data sources are being used
for purposes other than those for which they were originally designed, and possible
application of the Privacy Act to these initiatives. It is anticipated that congressional
oversight of data mining projects will grow as data mining efforts continue to evolve.
This report will be updated as events warrant.
目录：What Is Data Mining? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Limitations of Data Mining as a Terrorist Detection Tool . . . . . . . . . . . . . . . . . . 3
Data Mining Uses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Terrorism Information Awareness (TIA) Program . . . . . . . . . . . . . . . . . . . . 5
Computer-Assisted Passenger Prescreening System (CAPPS II) . . . . . . . . . 8
Secure Flight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Multistate Anti-Terrorism Information Exchange (MATRIX) Pilot
Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Other Data Mining Initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Able Danger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Automated Targeting System (ATS) . . . . . . . . . . . . . . . . . . . . . . . . . . 17
National Security Agency (NSA) and the Terrorist Surveillance
Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Novel Intelligence from Massive Data (NIDM) Program . . . . . . . . . . 20
Data Mining Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Data Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Interoperability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Mission Creep . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Privacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Legislation in the 108th Congress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Legislation in the 109th Congress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Legislation in the 110th Congress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
For Further Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29