NPS MDP Study Outbrief Schedule, 1 JUN 2005

Transcription

1 NPS MDP Study Outbrief Schedule, 1 JUN Introductions Background/Results Cargo Inspection System (Land) Cargo Inspection System (Sea) LUNCH Sensor System C3I System Response Force System

2 NPS MDP Study Land Inspection Group LT William Westmoreland, USN

3 MDP System Operational Architecture Land Inspection System [Detect?] External Intel? Sensor System [Track COI?] Manifest Info? Anomaly? Sea Inspection System [Detect?] C3I System Force System Y Y Y [Action Taken?] [Action Success?] N N N GOOD OUTCOME BAD OUTCOME

4 Land Inspection Agenda System Insights Objectives/Requirements Functional Decomposition Alternatives Generation Model Overview Model Assumptions and Factors Results Conclusions/Insights

5 NPS MDP Study System Insights Land Cargo Inspection Effective Cargo Inspection requires industry cooperation Sea Cargo Inspection Enroute at-sea Cargo Inspections can be effective using current handheld sensor technology

6 Land System Group Objectives Characterize cargo security and inspection process Identify methods to improve container security and inspection efficiency Develop model for land inspection system Determine driving factors for land inspection system Recommend system alternatives to improve land inspection performance

7 Land System Requirements Implement within five years Maximize detection of hazardous materials (CBRNE) Minimize delay Screen, target, and inspect cargo containers Provide information about containers, shippers, and carriers

8 Land System Objectives Increase the number of containers inspected Communicate results Dedicated resources for analysis of sensor data Improve intermodal security of containers Flexible

9 Functional Decomposition Land Inspection Maintain Accountability Target Detect Communicate

10 Port of Singapore As-Is Container Security Initiative participant Five container terminals Mostly Hub transfer traffic Utilizes Free Trade Zones (FTZ) Only 1.4 % of containers inspected Limited chemical/biological detection capability Use x-ray & gamma ray imagers, radiological detection pagers, and canines

11 Land Inspection As-Is Singapore Bound Singapore Customs In Bound Port of Singapore Non-US Out Bound MDP Area of Regard US Out Bound

12 Land System Alternatives Generation Origin Container History TARGET Verification Method Human Intelligence Route Surveillance System DETECT Destination Smart Container Nuclear/Radiation Chem./Bio. Explosives Contents Foreign Objects Canine Gamma-Ray Imager Optical Flash X-Ray Machine Manifest Chromatography Manifest Comparison High Purity Germanium Arrays Shipping Vapor Company Detector Density Robotic/Mobile Imager Inspection Scintillation Counter Flame Emission Photometry Molecular Locator COMMUNICATE Shape Recognition Human Inspection Neutron Generator Photo Ionization Receive/Transmit X-Ray Visual Record/Display Tamper Seals Laser MAINTAIN Infrared Fluorescence ACCOUNTABILITY Infrared Spectrometer InfraredNeutron Activation Computer AcousticDatabase Attached Sensors Semiconductor Detector Track Chemical Sensitive Radio (UHF, Canine etc.) Voice/Video Recorder Electronics Unmanned Vehicles Automated Interpretation Encoded Laser Monitors Thermo Luminescence Surface Acoustic Wave Check Points with Sensor Mapping Human Search Cable/Fiber Audio/Visual Sensors Alarms LIDAR Ion Mobility Spectrometry Data Analysis Imaging Display Satellite Density Screening Unit Flow Cytometry Communications Wideband Radar Smart Container Intelligence Cell Phones Divers RFID Sickness Locality Internet Temper Resist Seal Verbal/Visual

13 Land System Alternatives Overview As-Is System Implement CSI concept Supply Chain Port of Origin ALT 1: Port-Centric Inspections occur in ports Intelligence limited Supply Chain Port of Origin ALT 2: Trusted Agent Enhanced security measures Heavy reliance on intelligence Supply Chain Port of Origin

14 ALT 1 -Port Centric Inspection Layered security integrating passive/active sensors Inspections occur during normal container operations Intelligence limited Port-centric security

15 ALT-1 Port-centric Inspection Customs Or Storage Area Active Team Passive Or Mover Passive Crane Passive In Bound Random Active Search Into Port Mover Staging Area Crane Alert Team Passive Passive Passive Out Bound MDP Area of Regard

16 ALT 2 Trusted Agent Layered security integrating passive/active sensors Inspections occur during normal container operations Targeting or selection of searched containers based on: Container seals Manifest Discrepancies Certified Shippers 2-3% randomly inspected Hybrid of port-centric inspection and supply chain security

17 Trusted Agent Procedural Security Physical Security Personnel Security Education and Training Access Controls Manifest Procedures Transportation Security

18 SENSORS CONSIDERED Gas Chromatography / Ion Mobility Spectrometer 2. Radiation Pager 3. X-Ray Detector 4.Gamma-Ray Detector 5.Pulsed Fast Neutron Analyzer 6.High Purity Germanium Detector 7.Flow Cytometry

19 Overarching Modeling Plan Performance Models Sensors C3I Force Sea Insp Land Insp Cost Models Sensors C3I Force Sea Insp Land Insp Pr(detect) Delay time Attack Damage Model Shipping Delay Cost Model FY05$ FY05$ Pr(Defeat) FY05$ FY05$ MOE1 Performance MOE2 Risk (Attack Damage) M1 Commercial Impact M2 MDP System Cost

20 Approach Performance and Delay Cost Models Used EXTEND v6 Model Excel Model Overview

21 Land System Model Assumptions Based on Port of Singapore: 2004 Port operations procedures port statistics. Percentage of containers sent to temporary storage Average container value of $25 K Inspection times based on port operations

22 Land Inspection Factors Number of inspection teams Number of sensors Percentage inspected randomly P(d) & P(fa) for sensors Container throughput per month Inspection time per sensor ** Varied factors in red Number of cranes and movers Percentage of containers in storage Days in storage Probability of given threat Container value Number of ports

23 Land Performance Model Overview Input Variables Outputs Number of Sensors Sensor Pd Number of Containers % Random Inspected Number of Active Teams Land Inspection Model P(Detection) Delay Time Commercial Cost System Cost

24 Land System Model Results 3500 Number of Teams vs Delay Cost (Port-Centric) Number of Teams vs Delay Cost (Trusted Agent) Delay Cost ($M) Delay Cost ($M) Number of Teams Number of Teams teams minimize delay cost

25 Land System Inspection Results Main Effects Plot for Delay Cost Active Sensor Pd Passive Sensor Pd Sensor Pd s have minimal effect on delay Mean of Delay Cost M$ Passive Sensor FA Number of Sensors Passive False Alarm drives delay cost

26 Land System Inspection Results Main Effects Plot For System Probability of Detection Active Sensor Pd Passive Sensor Pd 0.8 Mean of Pdefeat Number of Sensors Passive Sensor FA Passive detection drives performance Minimal effect on system detection

27 Land Inspection System Variable Values Values Factors Values Evaluated As-Is Alt 1 Alt 2 Number of Sensors Active P(detection).3,.4,.5,.6,.85, Active P(false alarm) Passive P(detection).1, Passive P(false alarm).01,

28 Land System Single Port Use Case: Port of Singapore System confined to the Port of Singapore

29 Land System Results Single Port* MOE / Metric As-Is ALT 1 ALT 2 Percent Cargo Inspected 6% 99% 99% P(Detect I Inspect) 99% 87% 93% P(Detect) 6% 87% 93% Comm. Delay Cost ($M) ~0 1,921 1,688 Comm. Cost ($M) 0 0 1,753 Land System Cost ($M) 38 1,143 1,150 Total System Cost ($M) 38 3,064 4,591 * Modeled after the Port of Singapore

30 China Shandong Picture/diagram Zhejiang Shanghai Shenzhen Jiangsu Guangdong Japan Yokohama Nagoya Chiba Thailand Bangkok Laem Chabang U.S.A Seattle Tacoma Oakland Los Angeles Long Beach Port of Singapore System includes 16 High-Volume Ports that export to the Port of Singapore.

31 Land System Results: Inspections in 16 Highest-Volume Ports-of-Origin MOE / Metric As-Is ALT 1 ALT 2 % Inbound Cargo Inspected 2% 47% 74% P(Detect I Inspect) 99% 88% 94% P(Detect) all inbound cargo 2% 41% 56% Comm. Delay Cost ($M) ~0 30,730 27,019 Comm. Cost ($M) 0 0 1,753 Land System Cost ($M) ,677 33,841 Total System Cost ($M) ,407 62,613

32 Overall Results Single Port 10-Year Cost vs. P(Detect) P(Detect) 100% 80% 60% 40% 20% 0% ALT 1 ALT 2 As-is 0 1,000 2,000 3,000 4,000 5, Year Cost ($M) 16 High-Volume Ports 10-Year Cost vs. P(Detect) Port system performance increases with cost P(Detect) 100% 80% 60% 40% 20% 0% ALT 2 ALT 1 As-is 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80, Year Cost ($M)

33 CONCLUSIONS Current System is inadequate in defeating an attack: Container Volume Detection Capabilities Limited Costs Associated with Delay and False Alarm Best performance achieved through a layered defense of Port Centric and Intelligence systems

34 CONCLUSIONS Passive sensor P(d) drives system Passive sensor P(fa) impacts delay cost Effective supply chain security measures can reduce delay cost Increase in security measures will act to deter illicit trade which may result in lower system costs

35 RECOMMENDATIONS Invest in passive sensor technologies Continue development of sensor technologies with penetration capabilities Offer incentives to industry

36 RECOMMENDATIONS Develop a method to test security measures More inspectors needed at domestic and international ports Countries would benefit from implementation of C-TPAT Research methods to decrease time to unload containers for inspection

37 Questions? LT William Westmoreland, USN LT Micah Kelley, USNR 1 st LT Hasan Gungor, TuAF ENS Jared Wilhelm, USNR

38 Back-Up Slides

39 Original Model Port of LA Considers single WMD Simple, baseline model

40 Second Generation Model Port of LA Expanded Considers Nuclear, Biological and Chemical WMD

41 Third Model Port of LA Expanded w/ Layered Sensors Considers Nuclear, Biological and Chemical WMD Adds in realistic sensing layers and alert team

42 Port of Singapore As-Is Model Nuclear, Biological, Chemical and Explosive WMD capability Develop to represent current system as close as possible using realistic, researched numbers Excel Input File Excel Output File

43 Alternative 1 Model Layered passive and active system Targets based on minimal intelligence Port Centric Excel Input File Excel Output File

44 Alternative 2 Model Layered passive and active system Tagets based on intelligence, manifests and container seals Excel Input File Excel Output File