SLIP Technology
Browser: Index Page
Latest
tutorials and programs in zipped file.
The Event Knowledge Base
Stochastic and Fractal Theory, an Outline for Future Work, January 30,
2002
Proposals to Industry on Incident Management
Incident Management and Intrusion Detection System
Proposal to Industry, January 2, 2002
Thematic Analysis in Text Collections.
Verb map Analysis using SLIP, Tutorial and Design
Document December 31, 2001
Noun, Verb co-occurrence Analysis using SLIP, Tutorial
and Design Document, December 29th, 2001
Determining Functional Load
using SLIP, December 28th, 2001
Development Notes on Thematic Analysis With Tutorial and
Design Document; December 26th, 2001
Concept of double articulation in lingusitics
On the Nature of Stratification: December 24th, 2001
.
Event Chemistry.
Development Note" December 18th, 2001
First Report on eventChemistry (TM) ,
December 17th, 2001
Creating and Visualizing a Citation Index: Exercise I
December 17, 2001
Event Browser Exercise I, December 14th, 2001
A theory of
state transition and behavioral analysis is available and is to be applied (by
OSI) to creating templated profiles of opposition activity and intentions.
Human analysis
based on the viewing of event chemistry will be predictive in three ways
1) the human will have a cognitive aid for thinking about and
talking with peers about the events and event types
2) a top down expectancy is provided for pattern completion of
partially developed event chemistry
3) coherency testing separates viewpoints into distinct graphic
pictures and this provides informational transparency with a selective
attention directed by user voice commands.
Technical Note on Links and Atoms, December 10th, 2001
Exercise on Importing an Arbitrary Event Log, December
7th, 2001
The Root_KOS and SLIP Enterprise, December 9th, 2001
Although the
SLIP-RIB technology was developed for Computer Emergency Response Team (CERT) use
the small deployable software browsers will take ANY event log, allow the user
to define any link analysis relationship, produce clustered visualization of
the linkage over a small of large dataset, produce two layers of event
chemistry in correspondence to event atoms and event compounds.
Early SLIP Papers (developed for Incident
Management).
SLIP Data Structures and Algorithms, November 1th, 2001
Experiment with SLIP Analytic Conjectures, November 2th,
2001
SLIP Exercise I, November 11th, 2001
SLIP Exercise II, November 12th, 2001
SLIP Exercise III, November 19th, 2001
Research Note I, November 27th, 2001
SLIP Warehouse Exercise I, December 3th, 2001
Technical Note I, December 3th, 2001
OSI Summary of Possibilities, December 4th, 2001
.
Sensor Link analysis, Iterated scatter-gather
and Parcelation (SLIP).
A data mining technology
based on link analysis, emergent computing and category theory has been
developed as an application to modeling distributed in location and time
computer hacker/cracker incident events. The technology is fully prototyped and
available for demonstration.
The data mining
technology is called Sensor Link analysis, Iterated scatter-gather and
Parcelation (or SLIP). The term "Sensor" replaced the term
"Shallow" on December 10th, 2001.
Link
relationship is definable by the user using a Browser interface. The Browser is
less then 400K in size and has no install procedure. Patterns in the user
defined link relationships are used to define location and time distributed
"events" and these events are visualized as clusters and then as
pictures that appear like chemical compounds - where the atoms are data
invariance and the linkage is the used defined link analysis. Automated
conversion of the event chemistry to finite state transition models (colored
Petri nets) is possible.
Any one of
several enterprise knowledge sharing systems are readily deployable along with
the SLIP-RIB technology. OSI and a partner will deploy the chosen knowledge
sharing system and the SLIP-RIB technology using a deployment compliance model
under development. A process model for any such deployment has been under
development. The process model is simpler than the SW-CMM model for software
procurement, and reflects modern Knowledge Management practices, developed at
George Washington University and by several leading process theorists.
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