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Container Container Network Data Network Data Analysis Analysis Garrett Wolf Garrett Wolf

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Page 1: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via

Container Container Network Data Network Data

AnalysisAnalysis

Garrett WolfGarrett Wolf

Page 2: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via

BackgroundBackground Over 90% of the world’s cargo Over 90% of the world’s cargo

moves via container [9]moves via container [9]

Container security could be improvedContainer security could be improved

Requirements:Requirements: Detect breech of containerDetect breech of container Environmental conditions (humidity, Environmental conditions (humidity,

temperature, shock, vibration, etc.)temperature, shock, vibration, etc.) Location of container (ship, rail, truck)Location of container (ship, rail, truck) Power lifetime of 30,000 hoursPower lifetime of 30,000 hours Etc.Etc.

Dept. of Homeland Security developed the Dept. of Homeland Security developed the Advanced Advanced Container Security Device (ACSD)[2] Container Security Device (ACSD)[2] guidelinesguidelines

Page 3: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via

ProblemsProblems Ability to detect events/intrusions is needed Ability to detect events/intrusions is needed

for container securityfor container security Small containers require security tooSmall containers require security too

Containers must be tracked through various Containers must be tracked through various environments through which they travelenvironments through which they travel Smaller containers also travel via airplaneSmaller containers also travel via airplane

Limited battery power requires intelligently Limited battery power requires intelligently setting the reporting frequenciessetting the reporting frequencies Not all sensors are created equal when it comes Not all sensors are created equal when it comes

to detecting events/intrusionsto detecting events/intrusions

Page 4: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via

ContributionsContributions Past work focuses on large shipping containers Past work focuses on large shipping containers

whereas I focus on smaller “FedEx” sized packageswhereas I focus on smaller “FedEx” sized packages

Past work focuses on oceanic or land based Past work focuses on oceanic or land based transportation whereas I include an analysis of air transportation whereas I include an analysis of air transportationtransportation

Past work [8] adjusts the reporting frequency at the Past work [8] adjusts the reporting frequency at the node level whereas I suggest adjusting the reporting node level whereas I suggest adjusting the reporting frequency at the sensor levelfrequency at the sensor level

vs.vs.

TempAccel.

Light

TempAccel.

Light

TempAccel.

LightTempAccel.

LightTempAccel.

LightTempAccel.

LightTempAccel.

Light

TempAccel.

LightTempAccel.

LightTempAccel.

LightLightAccel.

LightTempAccel.

LightAccel.Accel.

Lightvs.vs.

Page 5: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via

GoalsGoals Analyze sensor data collected across different Analyze sensor data collected across different

environments (airplane vs. automobile)environments (airplane vs. automobile)

Identify events in each of the environments Identify events in each of the environments (loading/unloading of container, start of (loading/unloading of container, start of engine, speed/acceleration, etc.)engine, speed/acceleration, etc.)

Detect intrusions in each of the environmentsDetect intrusions in each of the environments

Determine which sensors are more helpful for Determine which sensors are more helpful for intrusion detection given the environmental intrusion detection given the environmental settings and prior eventssettings and prior events

Page 6: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via

Experimental SetupExperimental Setup 3 Containers3 Containers

≈≈1ft1ft3 3 eacheach Slightly insulatedSlightly insulated

1 Stargate [3] and PDA1 Stargate [3] and PDA

5 Motes5 Motes 2 Telos B – temp, humidity, microphone, visible/IR light2 Telos B – temp, humidity, microphone, visible/IR light 2 MTS310 – temp, light, microphone, 2-axis accelerometer, 2 MTS310 – temp, light, microphone, 2-axis accelerometer,

2-axis magnetometer2-axis magnetometer 1 MTS300 – temperature, light, microphone1 MTS300 – temperature, light, microphone

Configuration:Configuration: Container 1: 1 MTS310 & 1 Telos BContainer 1: 1 MTS310 & 1 Telos B Container 2: 1 MTS300 & 1 StargateContainer 2: 1 MTS300 & 1 Stargate Container 3: 1 MTS310 & 1 Telos BContainer 3: 1 MTS310 & 1 Telos B

Page 7: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via

Experimental Setup Experimental Setup (cont.)(cont.)

1 Cirrus[10] SR22-GTS1 Cirrus[10] SR22-GTS

1 Honda Accord1 Honda Accord

Page 8: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via
Page 9: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via

Data Collection and Data Collection and ResultsResults

Opened 1 of the 3 containers for 10 Opened 1 of the 3 containers for 10 second intervals in each environmentsecond intervals in each environment Same container opened each time Same container opened each time

(Container 1)(Container 1) Container opened at different points in time Container opened at different points in time

(e.g. on the ground, in the vehicle, after (e.g. on the ground, in the vehicle, after engine started, while moving slowly, while engine started, while moving slowly, while moving quickly, etc.)moving quickly, etc.)

Took note of the time when intrusion or Took note of the time when intrusion or other event occurredother event occurred

Compared the sensor readings with the Compared the sensor readings with the recorded intrusion timesrecorded intrusion times

Page 10: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via

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Time (min.[sec/60])

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Humidity drops when intrusion occursTemp also drops but its not as apparent as humidity

Humidity was the one of the best indicators for intrusion detection

Page 11: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via

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TSR (a.k.a visible and infrared light) was good but in the plane, the results were less informativePAR (a.k.a visible light) is a very good indicator

Page 12: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via

84.5

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Cont1 - CAR Cont2 - CAR Cont3 - CAR INTRUSION

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Thermistor in Container 2 increased steadily because of the heat given off from the Stargate

MTS 300/310 light sensor gave less helpful results when compared to the Telos sensor boards

Page 13: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via

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Page 14: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via

What I LearnedWhat I Learned Motes needed a higher reporting frequencyMotes needed a higher reporting frequency

Regardless of application, some sensors should Regardless of application, some sensors should report more frequently than othersreport more frequently than others E.g. changes in temp. are slower than changes in E.g. changes in temp. are slower than changes in

accelerationacceleration

More motes are needed to reduce noise in the More motes are needed to reduce noise in the datadata

Need to be careful that the motes are stationed Need to be careful that the motes are stationed level when dealing with 2-axis sensors to level when dealing with 2-axis sensors to prevent incorrect readings caused by tiltprevent incorrect readings caused by tilt

Page 15: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via

ReferencesReferences [1] Havinga, Paul J.M., [1] Havinga, Paul J.M., Sensor Networks for Monitoring.Sensor Networks for Monitoring. IST 2004 IST 2004

PresentationPresentation http://europa.eu.int/information_society/istevent/2004/cf/document.cfm?doc_ihttp://europa.eu.int/information_society/istevent/2004/cf/document.cfm?doc_id=1234d=1234

[2] Department of Homeland Security. [2] Department of Homeland Security. Advanced Container Security Device –Advanced Container Security Device –Broad Agency Announcement (BAA04-06).Broad Agency Announcement (BAA04-06). May 7, 2004. May 7, 2004. http://www.hsarpabaa.com/Solicitations/AdvContSecDev_BAA_FINAL_508.pdhttp://www.hsarpabaa.com/Solicitations/AdvContSecDev_BAA_FINAL_508.pdff

[3] 2006 Crossbow Technology. [3] 2006 Crossbow Technology. MTS/MDA Sensor, Data Acquisition Boards MTS/MDA Sensor, Data Acquisition Boards Datasheet.Datasheet. http://www.xbow.com/Products/Product_pdf_files/Wireless_pdf/MTS_MDA_Dahttp://www.xbow.com/Products/Product_pdf_files/Wireless_pdf/MTS_MDA_Datasheet.pdftasheet.pdf

[4] XCube Communication. [4] XCube Communication. SEAL Cargo System. SEAL Cargo System. http://www.x3-c.com/downloads/Industrypaper%20Cargo%20V1R1.pdfhttp://www.x3-c.com/downloads/Industrypaper%20Cargo%20V1R1.pdf

[5] T. Larsson, M. Taveniku, C. Wigren, P. Wiberg, B. Svensson. [5] T. Larsson, M. Taveniku, C. Wigren, P. Wiberg, B. Svensson. T4 – T4 – Telematics for Totally Transparent Transports. Telematics for Totally Transparent Transports. In Proceedings of 8th In Proceedings of 8th International IEEE Conference on Intelligent Transport Systems, 2005.International IEEE Conference on Intelligent Transport Systems, 2005.

[6] G. Hackmann, C. Fok, C. Zuver, K. English. [6] G. Hackmann, C. Fok, C. Zuver, K. English. Agile Cargo Tracking Using Agile Cargo Tracking Using Mobile Agents. Mobile Agents. In SenSys 2005.In SenSys 2005.

[7] F. Ridoutt, C. Mueller-Dieckmann, P. Tucker, M. Weiss. [7] F. Ridoutt, C. Mueller-Dieckmann, P. Tucker, M. Weiss. An Automated An Automated Temperature-Monitoring System for Dry-Shippers. Temperature-Monitoring System for Dry-Shippers. Journal of Applied Journal of Applied Crystallography 2004.Crystallography 2004.

[8] O. Akan and I. Akyildiz, [8] O. Akan and I. Akyildiz, Event-to-Sink Reliable transport in Wireless Event-to-Sink Reliable transport in Wireless Sensor NetworksSensor Networks, IEEE/ACM Trans. On Networking, 13(5), Oct. 2005., IEEE/ACM Trans. On Networking, 13(5), Oct. 2005.

[9] U.S. Customs and Border Protection. [9] U.S. Customs and Border Protection. Container Security Initiative.Container Security Initiative. http://www.customs.treas.gov/xp/cgov/enforcement/international_activities/cshttp://www.customs.treas.gov/xp/cgov/enforcement/international_activities/csi/i/

[10] Cirrus Aviation. [10] Cirrus Aviation. Cirrus Design Brochure. Cirrus Design Brochure. http://http://www.cirrusdesign.com/downloads/pdf/brochure.pdfwww.cirrusdesign.com/downloads/pdf/brochure.pdf

Page 16: Container Network Data Analysis Garrett Wolf. Background Over 90% of the world’s cargo moves via container [9] Over 90% of the world’s cargo moves via

Questions?Questions?