Centrifuge Systems Overview
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Centrifuge Systems Overview

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CSI overview presentation covering our visual data analytics and link analysis solutions.

CSI overview presentation covering our visual data analytics and link analysis solutions.

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  • Centrifuge beganby addressing the needs of the Intelligence CommunityLarge volumes of seemingly unrelated dataJoin together disparate sources quickly and without regard to the original formatExtreme time sensitivityLooking for activities or relationships that were actively trying to avoid detection
  • We’ve now been embraced across both national and local governmental organizations, as well as within the commercial sector.
  • We’ve now been embraced across both national and local governmental organizations, as well as within the commercial sector.
  • BYOD: Bring Your Own Data
  • BYOD: Bring Your Own Data
  • BYOD: Bring Your Own Data
  • BYOD: Bring Your Own Data
  • BYOD: Bring Your Own Data
  • In this simple example of a two-variable relationship graph involving warranty claims data, we display the relationships or connections between customers (green) and warranty claims (blue). As is typically the case, the vast majority of relationships are “normal”, in this case meaning a one-to-one relationship between claims and owners. These types of data connection are often referred to as “noise” in the term “signal to noise ratio”. Most data is pedestrian and useful to an analyst for nothing, other than masking, through layers of “routine activity” noise, those activities that are truly novel.One relationship of interest in this data set is the magnified one in the top left that shows 3 customers, two of which have an unusually large amount of claims associated to them, and who both share a single claim with each other and a third customer. This would certainly warrant closer inspection.
  • Now we jump to a more complex graph. This is based on a use case for a health insurance company what wanted to analyze the relationship between doctors, pharmacies and consumers to identify anything out of the ordinary – doctor-shopping, excessive prescriptions etc.Size can be used to visually represent the node based on any metric - either native data or derived - Opacity – individual icons for nodes can be brighter or lighter based on any metric – simplest metric to use is the number of neighbors.Also, the entire graph can be adjusted in layers so that either nodes, labels are emphasized.

Transcript

  • 1. CENTRIFUGE SYSTEMSOVERVIEWCopyright 2012 Centrifuge Systems, Inc. All Rights reserved. 1See Clearly NowA Powerful, Flexible Lens for Data Discovery
  • 2. Centrifuge Corporate Overview Visual data analysis pioneer since 2007 Genesis in US National Intelligence Sector Funded by Novak Biddle Venture Partners Used by thousands of analysts in both publicsector and commercial organizations Headquartered in McLean, VACopyright 2012 Centrifuge Systems, Inc. All Rights reserved. 2
  • 3. Copyright 2012 Centrifuge Systems, Inc. All Rights reserved. 3 Social Network Analysis (SNA) Sentiment Analysis Claims Fraud Telephony / Text Messaging Gang Activity Evidence Discovery Analysis Financial Money Laundering Serial Crimes Cyber & Computer Network AnalysisAnalyzing large volumes of diverse dataTargets trying to avoid detection
  • 4. Copyright 2012 Centrifuge Systems, Inc. All Rights reserved.Commercial ExamplesProblem: Criminal networks arrange procurement of medication throughlow-cost government contracts, then sell on open market for high profit.Problem: Sophisticated fraud rings of patients, providers and pharmaciesconspire to circumvent law . Difficult to detect with via traditional analytics.Drug ProfiteeringPrescription Fraud4BIG “Pharma”Healthcare
  • 5. Copyright 2012 Centrifuge Systems, Inc. All Rights reserved.Third Party Recognition5Honored as a 2012 FinTech Innovation Lab participantfor Wall Street-focused startup companiesRecently chosen by Gartner as a 2013“Cool Vendor” for Security Intelligence
  • 6. Centrifuge SystemsCopyright 2012 Centrifuge Systems, Inc. All Rights reserved. 6 Data Remains at the Source• No need for redundant storage silos or client-side resources Client Access via Lightweight Browser• Browser-based clients promotes both collaboration and security Easy and Secure Collaboration• Collaboration performed at server• Data does not transfer ownership during analysis Modern Server-based Java Architecture• No feature lock-in, Interact with other best-in-class applications• Highly scalable with no client-side resource requirements
  • 7. Copyright 2012 Centrifuge Systems, Inc. All Rights reserved. 7No Data Preprocessing or Redundant Data Storage• Avoid the time & cost of preprocessing / prepositioning target data sets andthe resulting storage management overhead (hardware, security, backup, etc.)• Data remains on its original server and native format allowing quick accessto newly discovered or updated data;• Templates can created and saved for ease of future analysis.
  • 8. Copyright 2012 Centrifuge Systems, Inc. All Rights reserved. 8 Client Access through Lightweight Browser• Browser-based clients can connect from anywhere, promotead hoc collaboration• Client issues eliminated, extreme server scalability• (RAM, storage, conflicts, etc.)• No data touches the client, greatly reducing privacy concerns
  • 9. Copyright 2012 Centrifuge Systems, Inc. All Rights reserved. 9 Collaboration constraints removed• Collaboration occurs on a secure server, NO data touches a client• Data is not in jeopardy if client is “compromised”• Collaborators can share data without transfer of ownership, greatly reducingsecurity and privacy concerns• Two ways to share• Static PDF image• Fully functional Centrifuge Dataview, each collaborator can contributeStatic, or Liveand Interactive
  • 10. Copyright 2012 Centrifuge Systems, Inc. All Rights reserved. 10 Leverage other best-in-class capabilities via standards-basedJava/JavaScript and REST APIs, plus the included Solution Factory• Early adopter of Ozone Widget Framework (OWF)• Our focus is visual data analytics, not user lock-in• We readily interface with best-in-class partners as determined by your needsUnstructured dataEntity extractionFuzzy matchingWeb harvestingGeo-taggingStatistical AlgorithmsNLPEmbedded
  • 11. Copyright 2012 Centrifuge Systems, Inc. All Rights reserved.VISUAL DATA ANALYTICSSee Clearly Now May 6, 201311A Powerful Lens for Data Discovery
  • 12. NoiseSignalSeparate the Signal from the Noise
  • 13. Copyright 2012 Centrifuge Systems Inc 13Scenario: Health care insurance provider looking for prescription fraudDataset: Claims data relating drug, pharmacy, prescribing doctor and consumerInitial Graph Using OpacityUsing SizeApplying iterativefiltering
  • 14. Copyright 2012 Centrifuge Systems IncHighlight Paths and Degrees of Separation14Scenario: Cyber Security – investigating network traffic and identifying potential threatsDataset: NetFlow data with originating and destination IP addresses and users/orgs1. Identify all pathsVisually highlight all paths that connect subjects of interest2. Identify & isolate path ofinterest3. Iteratively explore suspicious elements1. Start with suspects 2. Reveal nodes associatedwith suspect organizations3. Reveal where traffic isbeing directed4. Reveal users associatedwith suspect traffic (targets)
  • 15. Copyright 2012 Centrifuge Systems IncChoose Link Layouts & Placement15Force-DirectedRadialCircularAlgorithmic layouts allow placement of nodes to be based on different criteria allowingnatural patterns to emergeHierarchical
  • 16. Graphically Select or FilterSelect and filter from one visual to anotherNarrow results, highlight subsets
  • 17. Query Build OutAs “link-ups” are run, the new “associates” are brought into the picture – building outour relationship graph based on added connections. “Link ups” can be added for asmany associates as desired.
  • 18. Copyright 2012 Centrifuge Systems, Inc. All Rights reserved. 18Contact us for more informationRuss HolmesCentrifuge Systems, Inc.7926 Jones Branch Dr., Suite 210McLean, VA 22102(571) 830-1300www.centrifugesystems.com