150 words agree or disagree This week we discussed data mining and the various programs used as well as the goals of various organizations in regard to devoting resources to combing massive amounts of data for the proverbial "needle in the haystack". We learned about several notable examples of programs in use, to include the Signal Detection Theory (SDI), Analytic Framework for Intelligence (AFI), and the Data Analysis and Research for Trade Transparency System (DARTTS). I’ll skip the overview of each, as we have all read the lesson, but it’s safe to say no one underestimates the valuable resources these tools and methods have been to signals and intelligence analysts.  Social Networks and Link Analysis (SNA)  This link analysis has been applied recently after the burgeoning ubiquity of social media in just about every individual’s life. Link analysis is performed by mapping relations between events, and entities (Nissan, 2012). This analysis works by examining the links between events and entities, and categorizing those bonds by strength, in order to draw a picture of how strong the ties linking each event are. This is useful when trying to build a map of a terror cell or organized crime ring, allowing analysts (military, state, or even local police) to begin drawing parallels between occurrences such as types of MO used in a bank robbery, or specific engineering habits used in producing an IED. Nissan’s 2012 article even notes several such programs by name, “Crime Link”, “ORIONInvestigations”, and “Daisy”, all of which are tailored to provide visual representation of the connection between two given things. According to the reading, one of the biggest issues in data mining was applying it to criminal activity (McCue, 2006) in a successful fashion. The framework and foundation of data mining was already there, stretching back nearly a century. The problem, however, was to meet and deal with the various restrictions put in place for law enforcement. There is no court order or legal warrant needed for a company to monitor their employee’s communications, and we all tacitly agree to such monitoring of our online behavior on social media sites and in google, but law enforcement actors, whether they be local or federal, operate under different authority than a private company. I found the Predictive Policing theory or model to be pretty interesting. I recall watching the movie Minority Report with Tom Cruise and being really engrossed with the idea of predicting crimes before they happen. In the movie they used psychics, but we do a kind of similar thing in the real world, where departments are using proactive vs reactive policing techniques in order to curtail crime. I know that even I, a lowly patrolman, have the ability to generate calls for service reports listing type of crime and geographical area of the city, and I can use those reports to tailor my enforcement to catch more bad guys and stop more crime. References McCue, C. (2006.

1. 150 words agree or disagree
This week we discussed data mining and the various programs
used as well as the goals of various organizations in regard to
devoting resources to combing massive amounts of data for the
proverbial "needle in the haystack". We learned about several
notable examples of programs in use, to include the Signal
Detection Theory (SDI), Analytic Framework for Intelligence
(AFI), and the Data Analysis and Research for Trade
Transparency System (DARTTS). I’ll skip the overview of each,
as we have all read the lesson, but it’s safe to say no one
underestimates the valuable resources these tools and methods
have been to signals and intelligence analysts.
Social Networks and Link Analysis (SNA)
This link analysis has been applied recently after the
burgeoning ubiquity of social media in just about every
individual’s life. Link analysis is performed by mapping
relations between events, and entities (Nissan, 2012). This
analysis works by examining the links between events and
entities, and categorizing those bonds by strength, in order to
draw a picture of how strong the ties linking each event are.
This is useful when trying to build a map of a terror cell or
organized crime ring, allowing analysts (military, state, or even
local police) to begin drawing parallels between occurrences
such as types of MO used in a bank robbery, or specific
engineering habits used in producing an IED. Nissan’s 2012
article even notes several such programs by name, “Crime
Link”, “ORIONInvestigations”, and “Daisy”, all of which are
tailored to provide visual representation of the connection
between two given things.
According to the reading, one of the biggest issues in data
mining was applying it to criminal activity (McCue, 2006) in a

2. successful fashion. The framework and foundation of data
mining was already there, stretching back nearly a century. The
problem, however, was to meet and deal with the various
restrictions put in place for law enforcement. There is no court
order or legal warrant needed for a company to monitor their
employee’s communications, and we all tacitly agree to such
monitoring of our online behavior on social media sites and in
google, but law enforcement actors, whether they be local or
federal, operate under different authority than a private
company.
I found the Predictive Policing theory or model to be pretty
interesting. I recall watching the movie Minority Report with
Tom Cruise and being really engrossed with the idea of
predicting crimes before they happen. In the movie they used
psychics, but we do a kind of similar thing in the real world,
where departments are using proactive vs reactive policing
techniques in order to curtail crime. I know that even I, a lowly
patrolman, have the ability to generate calls for service reports
listing type of crime and geographical area of the city, and I can
use those reports to tailor my enforcement to catch more bad
guys and stop more crime.
References
McCue, C. (2006). Data mining and predictive analytics in
public safety and security.
IT Professional Magazine, 8
(4), 12-18. doi:http://dx.doi.org/10.1109/MITP.2006.84
Nissan, E., & Nissan, E. (2012). AN OVERVIEW OF DATA
MINING FOR COMBATING CRIME.
Applied Artificial Intelligence
,
26

3. (8), 760–786.
https://doi.org/10.1080/08839514.2012.713309