Knowledge Discovery for Counterterrorism and Law Enforcement by David Skillicorn

By David Skillicorn

Most of the study aimed toward counterterrorism, fraud detection, or different forensic purposes assumes that this can be a really expert program area for mainstream wisdom discovery. regrettably, wisdom discovery alterations thoroughly whilst the datasets getting used were manipulated so one can hide a few underlying job. Knowledge Discovery for Counterterrorism and legislations Enforcement operates from the basis that detection algorithms has to be rethought to be powerful during this area, and offers a brand new strategy in line with state-of-the-art research to be used in hostile settings.

Reveals How Criminals cover Information

 

This quantity makes a speciality of 4 major kinds of wisdom discovery: prediction, clustering, dating discovery, and textual research. for every of those program parts, the writer discusses possibilities for concealment which are on hand to criminals and divulges a number of the strategies that may reduction in detecting them. He studies what's recognized in regards to the various applied sciences for every sector and evaluates their effectiveness. The e-book additionally offers a preview of applied sciences presently less than improvement and describes how they'll slot in to latest methods to wisdom discovery.

Provides Proactive formulation for Staying One Step prior to Adversaries

 

While all knowledge-discovery structures are at risk of manipulation, designers and clients of algorithmic structures who're armed with the data of those subversive strategies are greater in a position to create structures to prevent those vulnerabilities. This e-book delineates an efficient procedure for integrating knowledge-discovery instruments, presents a special realizing of the boundaries of the know-how, and incorporates a transparent presentation of the upsides and pitfalls of knowledge assortment. it's a strong weapon within the arsenal of somebody confronting the more and more subtle strategies hired through lawbreakers and different unsavory individuals.

 

 

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Extra resources for Knowledge Discovery for Counterterrorism and Law Enforcement (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Sample text

Low-level data can often be directly analyzed by humans, provided it can be made to match our normal modes of sensing. Humans can usually recognize what objects are in an image, a task that is still difficult to do algorithmically. However, while humans are good at dealing with a single record of this form, they perform less well when there are many records. For example, humans watching banks of closed-circuit television feeds soon start to miss potentially important activities that are plainly visible.

However, error rates in controlled situations are dropping to usable levels. Exploring relationships and connections, starting from an object or person of interest. Relationship data expresses the links or connections between people, and between people and objects such as addresses, telephone numbers, bank accounts, cars, flights, and so on. Such data arises from surveillance, from interrogation, and indirectly from other forms of data such as call billing records. In such data, almost all knowledge discovery is done by starting from a known person or object and exploring the neighborhood of that starting point.

The city of London collects a congestion charge for vehicles that enter the center of the city each day, using cameras to read licence-plate numbers for the purpose of identifying the vehicles5 . This data can be used, say as part of a criminal investigation, to show that a particular car passed a particular point at a particular time, but the data was collected anyway, regardless of whether information about that car was asked for. In contrast, if a particular car is involved in a hit-and-run accident at a particular place and time, police officers will try to find someone who saw the car there at the right time.

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