Quantitative Methods in Defense and National SecurityMichael F. McGrathDASN RDT&EFebruary 7, 2007

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Why This ConferenceIs Important

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Outline

• The Post-9/11 Defense Climate • Examples of Needs for Computational Modeling

– GWOT: Counter-IED, Identity Management– Homeland Defense and Maritime Domain Awareness– System Design and Test and Evaluation– Other needs

• Conclusion – how this community can engage

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Strategic EnvironmentQuadrennial Defense Review

Near Peer Competitors

Irregular Warfare Terrorist Threats

Global Maritime Security

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Navy Acquisition Vision

To provide weapons, systems andplatforms for the men and women of theNavy/Marine Corps that support theirmissions and give them a technologicaledge over our adversaries.

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ASN (RDA) Goals

• Expedite GWOT acquisition programs as much as possible without compromising safety.

• Reduce volatility in current acquisition programs.

• Develop an investment/transition strategy for Science and Technology (S&T) to ensure future technological edge.

• Lead the Acquisition Enterprise component of the Naval Enterprise, in collaboration with OPNAV/HQMC and the fleet.

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ASN (RDA) Goals

• Expedite GWOT acquisition programs as much as possible without compromising safety.

• Reduce volatility in current acquisition programs.

• Develop an investment/transition strategy for Science and Technology (S&T) to ensure future technological edge.

• Lead the Acquisition Enterprise component of the Naval Enterprise, in collaboration with OPNAV/HQMC and the fleet.

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S&T Focus Areas DON S&T Strategy (2007)

• Power and Energy• Operational Environments• Asymmetric & Irregular Warfare • Maritime Domain Awareness• Information, Analysis and Communication• Power Projection• Assure Access and Hold at Risk• Distributed Operations• Naval Warrior Performance and Protection• Survivability and Self-Defense• Platform Mobility• Fleet/Force Sustainment• Affordability, Maintainability, Reliability

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IEDs Are Not New…

• The Place and Time– Wall St., New York City– Sept. 16, 1920; 12:01 PM

• The Attack– ~100 lbs of TNT detonated with

~500 lbs of sash weights– Delivered in a horse-drawn

wagon

• The Damage– ~33 dead, ~400 injured– Carnage for blocks around– Windows shattered for 2 miles– NY Stock Exchange closed

• The Attacker: “American Anarchist Fighters”

– Never identified, located or convicted

– Case closed in 1940

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IEDs: An Evolving Threat

Command Wire IEDs Icon Vehicle AttacksVBIEDs

Targeting FirstResponders

Complex Ambushes

Improved Concealment

More AggressiveVehicle Borne IEDs

Radio Controlled IEDs

CORDLESSPHONE

Explosively Formed Penetrator

and Claymore

(Hart/697-5252/050927)

• Evolving

• Learning

• Innovating

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Counter-IED ResearchFocusing “Left of Boom”

BOOM

ObtainFunds

DevelopOrg’n

Gather & Provide Material

Improvise Tactics &Devices

PlanAttacks

Perform Attacks

ConsequenceManagement

Attribution

Example: Social Network AnalysisONR-sponsored research

• Objectives– New techniques and tools to:

• Describe terrorist networks• Anticipate their actions• Predict their targets• Deny their ability to act

• Approach– Use new and established social

theory, computational tools, and data

– Theory-based models of command and control organizations

– Computational analyses of social networks, such as terrorist or espionage networks

TERRORISTNETWORK ANALYSIS

“Creep of the Week”reports to gain better understanding of terror suspects and interconnections among terror groups

COURSE OF ACTION ANALYSIS

What-If forecasts for impact on terror groups of various courses of action (such as using kinetic vice non-kinetic options.)

DYNET TOOL SUITE

Models for effective interventions against mobile or spreading hazards

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Predict Detect Prevent Neutralize Mitigate

ST

AG

ER

ES

EA

RC

H T

HR

US

TS

• Psychology & Sociology of Terrorists

• Information Management

• Pattern Recognition

• Artificial Intelligence

• Explosive Characterization

• Sensor Technologies

• Signal Processing

• Data Fusion

• Pattern Recognition

• Autonomous System Technologies

• RF Communications

• Non- Lethal Weapons

• Information Management

• Artificial Intelligence

• Chemisty/Physics of Explosives

• Energy-based Weapons

• Autonomous System Technologies

• Tagging / Marking

• Protective Structures

• Armor

• Knowledge Management

• Information Technology

Counter-IED Strategic Research ProgramONR/NRL, Universities, industry

Biometrics and Identity Management

• Biometrics– Automated mechanisms to measure physiological and/or

behavioral characteristics– Identify an individual (One:Many)– Verify the identity of an individual (1:1)

• Identity Management– Pre-9/11, this was a “Blue Force” authentication and access issue– Today it is an urgent “Red Force” and “Gray Force” issue

Take away anonymity as a tool of the terrorist

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Biometric Automated Toolset (BAT)

USMC “BAT Cave”, Fallujah

Iris Scan

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Iris Research at USNA

• Develop/expand iris database– Orthogonal-eye looking into camera– non-orthogonal-not looking into camera

• Algorithm Development– 1D recognition algorithm (patent filed)– New segmentation algorithm

• Testing on orthogonal irises

– Segmentation of non-orthogonal irises– Non-orthogonal iris recognition

• Analysis– Non-orthogonal iris recognition analysis– Compression effects on recognition

Biometrics in a System of SystemsCollect, Match/Store, Analyze, Disseminate

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Outline

• The Post-9/11 Defense Climate • Examples of Needs for Computational Modeling

– GWOT: Counter-IED, Identity Management– Homeland Defense and Maritime Domain Awareness– System Design and Test and Evaluation– Other needs

• Conclusion – how this community can engage

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“…the effective understanding of anything associated with the global Maritime Domain that could impact the security, safety, economy, or environment of the United States.”

- NSPD 41 / HSPD 13 21 Dec 04

HomelandDefense

Commercial,Environmental,

SafetyInterests

HomelandSecurity

MaritimeDomain

Awareness

Maritime Homeland Security

(DHS-led: USCG)

Maritime Homeland Defense

(DoD-led: USNORTHCOM)

Maritime Domain Awareness (MDA)

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Merchant Fleets• 121,000+ Ships... 198 Flags• 65-70% OPTEMPO• Containers

– 17 million+...210 million moves/year– Each container used 8.5 times/year

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Maritime Domain Awareness

The Maritime Industry…over 90% of global trade move s by sea

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Global Challenges to Maritime Security

• Piracy• Drug smuggling• Human smuggling and

slavery• Exclusive Economic

Zone (resource) exploitation

• Trade disruption

• Search and Rescue• Illegal weapons

movement/proliferation• Organized crime• Environmental attack• Political and religious

extremism• Terrorism

Nations find their well-being challenged by these common threats to Maritime Security

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THE NATIONAL STRATEGY

FOR MARITIME SECURITY

September 2005

THE NATIONAL STRATEGY

FOR MARITIME SECURITY

September 2005

MDA Objectives & GapsNational Plan to Achieve MDA

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THE NATIONAL STRATEGY

FOR MARITIME SECURITY

September 2005

THE NATIONAL STRATEGY

FOR MARITIME SECURITY

September 2005

Essential Tasks • Persistently monitor in the global

maritime domain:– Vessels and craft– Cargo– Vessel crews & passengers– All identified areas of interest

• Access and maintain data on vessels, facilities, and infrastructure

• Collect, fuse, analyze, and disseminate information to decision makers to facilitate effective understanding

Identified Gaps

• Non Cooperative/Small vessels

• Detecting dangerous cargoes• Criminals/High Risk Persons• Government and Commercial

database access• Data fusion and analysis

capability

MDA Objectives & GapsNational Plan to Achieve MDA

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Data Fusion and Data Mining

• Data Mining – Offline discovery of new patterns– Manual or automated

• Fusion – Automated real-time detection of known patterns– Level 1: Recognize objects; form tracks– Level 2: Recognize situations; discern relationships between

objects– Level 3: Recognize threat; infer intent of enemy

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The Fusion ChallengeRapid, Accurate, Actionable Information from Multiple Sources

Today’s Limitations• Increasing volumes of information

overloading warfighters• Operating pattern data is not

linked to the picture• Integration of national and tactical

sensor data processes are manually established

• Warfighter cannot drill-down to see what data was used to create the track

• Sensor data that doesn’t “add up”to a track is lost

• Tactical user at “pointy end of spear” cannot process data in time to use

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What I need to know

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SIGINT

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Example: USN/USCG Vessel Tracking Project

Multi-INT Fusion

Space

CommercialSources

Lloyd’s InfoInternet/Open Source

NAVAL ASSETS

Autom

ated

Tra

ckin

g

Automated Search

Automated Correlation

NAVAIR: P3, Storyfinder + SEIIUSS: SOSUS/SURTASS

Robust Communication Backbone(Global Grid)

TagsShips/Containers

HyperspectralMNR tags

Chokepoints/Ports

Radar ELINTOptics SEIAcoustics AIS

HFSWR

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Example: Cooperative Maritime Awareness A Joint Concept Technology Demonstration (US/Singapore)

Problem: Limited maritime security forces can interdict and inspect only a small fraction of maritime traffic

Solution: Focus on most probable maritime threats.

– Draw information from multiple sources– Share information with international partners– Correlate multi-source information to maritime

contacts– Identify anomalies

Technologies:• Singapore Open C2

Centre• USPACOM HQ Joint

Operations Center, Data Fusion Center

• ONI and National Systems data centers

• CENTRIXS, APAN• Data Gathering,

Correlation, Fusion, Filtering, Sharing

• Multi-level security guards• Special track sources• Profiling (containers,

personnel, vessels, . . .)• Interfaces to non-

traditional data types

Caspian Trader approaches Long Beach

- 24 crew; Last port of call: Singapore- PACOM track shows large gaps- Query generated to Singapore- Singapore data indicates 20 crew on board- Alert generated

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Example: PALADINApplying Bayesian Networks to Naval Information

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Example: Automated Level 2/3 Fusion ONR FY-07 Future Naval Capability (FNT-07-01)

Automated derivation of object relationships and co mbat intent; supports timely, high confidence decision making

Automated derivation of object relationships and co mbat intent; supports timely, high confidence decision making

� Lots of data, little understanding � Manual capability to manage multiple hypotheses

o Entities, events that may be related

Current Capability

ONR’s Objective�Data from many operational & tactical

sources automatically exploited�Automated capability to manage

hundreds of multiple hypotheses about the meaning of

o Groups of entitieso Events that may potentially be related

�Warfighter-relevant understanding about how entities and events relate

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Example: Research Issues

• Managing Uncertainty and Object Refinement – Spatial clustering, aggregation of tracks, positions of physical entities – Representing complex situations with a tractable set of state variables – Representing higher levels of abstraction and information aggregation– Representing knowledge uncertainty

• Inference Engines and Ontology Development– Inconsistent entity data representation and interpretation– Multi-source exploitation and fusion of data to minimize the uncertainty

of information, while preserving data integrity in the face of various information handling and processing factors that may corrupt the fusion operations, rendering the results incorrect and possibly misleading

– Higher levels of fusion for inferring activities, relationships, and intentions of objects and people

– Data mining techniques to uncover trends in activity, links among objects, and hidden models of behavior

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Outline

• The Post-9/11 Defense Climate • Examples of Needs for Computational Modeling

– GWOT: Counter-IED, Identity Management– Homeland Defense and Maritime Domain Awareness– System Design, Test and Evaluation– Other needs

• Conclusion – how this community can engage

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• Capabilities– Design & Analysis of

Complex Systems – Greater Knowledge Earlier in

Acquisition Process and Improved Understanding of Design Margins

– Statistically Significant Number of Threat Representative High Fidelity Simulations

– Optimize and Increase Understanding from T&E

Role of Computational Modeling

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Example: Test & EvaluationFull Ship Shock Testing

Today“At Sea”, Limited Data

Future M&S“Virtual”, Multiple Tests

Best of Both WorldsExperiment: Full truth, partially exposedSimulation: Partial truth, fully exposed

Sandia

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Example: Ship Self Defense AAWPEO(IWS)

• High degree of commonality in combat systems– LPD 17, LHA6, LCS, DDG 1000, CVN 21

• All must demonstrate Probability of Raid Annihilati on (PRA)• Opportunity for savings through common T&E and simu lation

2. Full Ship Shock Trials (Proposed)

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Navy Enterprise Testbed for P RAVirtual Test Ship, Virtual Range

NAWC Weapons DivisionChina Lake

Naval Research LabWashington, DC

JHU Applied Physics LabLaurel, MD

ShipShip ASCM threatASCM threat

SSDSSSDSRAMRAM SIMDISSIMDIS

RTI Interface LayerRTI Interface Layer

NulkaNulka CECCECScenario ControlScenario Control

SLQ-32SLQ-32 SPQ-9BSPQ-9BSPS-48ESPS-48ESIPRNET

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Captive CarryEW Field Tests

ASW (AUV Fest) JTFEX San Diego Harbor

• Analysis and Visualization of the “Seen” and “Unseen” (sensor data)

• Scripted & Interactive Multimedia Playbacks using 3D, 2D, Images, Sound, and Video.

• Networked Real-Time 2D/3D Display

• Supported on Linux, Silicon Graphics, Solaris & Windows PC Workstations

NRL SIMDIS T&E, Training, Operational, & Homeland Security use rs

Low Cost PC BasedAdvanced Display

Web ToolSIPRNET or INTERNET

Server

FleetT&E Community Warfare Centers

RangesLaw Enforcement

Simulation ResultsField Test ResultsSurveillance Data

SIPRNET or

INTERNET

Warfare CenterRange

ServersGIS DatabasesNIMA, USGS

https://https://simdis.nrl.navy.milsimdis.nrl.navy.mil

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Other Defense Needs for Quantitative Methods

• Image understanding• Natural language processing• Emergent behavior in networks• Logistics and readiness modeling• . . .

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Summary

www.onr.navy.mil

• Defense and Homeland Security face difficult new challenges

• Quantitative methods are essential to finding workable solutions

• This community has responded in the past and we need your help again

FOUO

Questions?

Quantitative Methods for Defense and National Security

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