Home Land Security Research at CIMIC - dimacs

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Transcript Home Land Security Research at CIMIC - dimacs

Home Land Security Research at CIMIC
Presented
Nabil R. Adam and Vijay Atluri
Team members: F. Artigas, K. Barrett, S. Chun, R. Clark, M. Halem, L. Liu
Ph.D. Students: A. Gomaa, Q. Guo, D. Guo, V. Janeja, Y. Mohamoud,
A. Paliwal, L. Qin, J. Warner, S. Yu
CIMIC
(Center for Information Management, Integration and Connectivity)
Rutgers University – Newark Campus
September 23, 2003
Ongoing HS Projects

Border Security:

Secure Agency Interoperation for Effective Data Mining in Border Control and Homeland
Security Applications
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Supported by NSF $1,050,000 (Sept 03 – Aug 06) additional matching funds from SAP
Corporate Research
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Water Security:

End –to End Early Warning Decision Support System for Dinking Water Safety and
Security: Monitoring, Modeling and Info Management
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Supported by EPA $2,000,000 (Dec 03 – Nov 05) additional $2M matching from water
utilities
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Emergency Response
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GIS for the Emergency Response
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Supported by the NJMC, $350,000 (June 03 – May 04)
Protection of Critical Resources

Meadowlands Environmental Research Institute
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Supported by the NJMC $8,000,000 (Jan 02 – Dec 07)
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Border Security
 Specific Goals
 Supplement the profiling, by making it targeted towards
anomalies
 Utilize data available from different agencies, ports and customs
divisions
 Detect various flags raised by non-conforming shipments or
abnormal behavior of inbound cargos and raise a combination
of alerts
 Identify the anomalous shipment before it enters the country
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Border Security
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Proposed Work
 Provide decision makers with the ability to
 Extract and fuse information from multiple, heterogeneous
sources in response to a query
 Mine data distributed in various sources within and across various
agencies
Research Building Blocks

Semantic Interoperability

Security Enforcement

Text Mining, Data Mining and Alert Management Systems

The Diplomacy and Politics of Implementing Homeland Security
Information Technology Initiatives
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Broader Impact of Proposed Work


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Advances fundamental research in the areas of semantic
interoperability, data mining, text mining and security enforcement
Devises solutions to accomplish secure interoperation among
different government agencies
Our partnership with
 SAP, which is the supplier of software to the Customs and
Border Protection Modernization Program and contractor to
IBM, the prime contractor for eCustoms Partnership (eCP)
that is implementing the modernization program
 Provides the opportunity to directly contribute to fulfilling the
practical needs of the Bureau of Customs and Border
Protection
Serves as a reference model to be adopted by other divisions of
the Department of Homeland Security and other departments
contributing to homeland security missions.
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The Team

Researchers
Nabil R. Adam and Vijay Atluri, CIMIC, Rutgers University

Robert Grossman, National Center for Data Mining, Univ. of Illinois at Chicago
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Vasileios Hatzivassiloglou and Kathleen R. McKeown, Dept. of Computer Science,
Columbia University
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Rey Koslowski, Dept. of Political Science, Rutgers University

Tao Lin, SAP Corporate Research Labs
Domain experts

SAP labs

IBM Global services

Dr. Stephen E. Flynn, Council on Foreign Relations

C.J. Chang, Special Agent, SAIC Denver, Bureau of Immigration and Customs
Enforcement, U.S. Customs Service

Steve Cooper, CIO, Department of Homeland Security
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Luis R. Cortes, Chief of Intelligence, Office of National Risk Assessment (ONRA),
Transportation Security Administration (TSA)

Lee Holcomb, Department of Homeland Security

James R. Sutton, Managing Associate of McManis Associates, Inc. and former Senior
Intelligence Research Specialist for the U.S. Department of Justice on the Foreign
Terrorist Tracking Task Force.
Consumers

US Customs, INS
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Water Security

Specific Goals


Develop an End –to End Early Warning Decision Support System (EWS) for
Dinking Water Safety and Security
 to detect
 deliberate or accidental introduction of contaminants into a distribution
system (back flow, cross connections)
 deliberate or accidental contamination of source waters
 Cyber attacks caused by either externally or internally
 Model the behavior of the level and extent of the threats
 Develop a decision support system to generate warnings and alerts
Complement the EWS surveillance monitoring system (SMS) focuses on public
health surveillance of disease data in the population
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Real-time Monitoring, Modeling, and Alert System for Drinking Water
Safety Security
Service Area
DATA Sources
ALERT GENERATION
Managers
/ Officials
Hospitals
•Reservoir
•Treatment
plant
Community
•Treatment
plant
•Sensors
•Clinics
•Hospitals
Public
REAL-TIME MODELING
Weather station
with
data logger
Predicted toxin concentration, ppb
8/24/01
Coastal GeoTools ‘01
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Simulation
Time, hr
Location 1
Location 2
Location 3
0
2
4
6
8
10
12
14
16
18
20
20.3
14.1
10.2
8.4
6.5
4.4
3.4
2.3
1.3
0.4
0.0
0.0
8.4
14.3
18.2
13.3
9.5
7.0
5.1
3.2
2.3
1.2
0.0
0.3
11.1
15.1
17.5
15.5
11.1
9.2
7.3
5.4
4.0
Concentration, ppb
25.0
Predicted concentration at 5 locations
moving downstream
20.0
Location 1
Location 2
Location 3
Location 4
Location 5
15.0
10.0
5.0
0.0
0
5
10
15
20
Simulation Time, hr
25
30
35
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Water Security: Research Building Blocks
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Sensor and Monitoring Research
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Monitor Chemical, Biological, Radiological contaminants

Each source water monitoring station will include the installation of on-line sensors
for the collection of water quality data: Alkalinity, Temperature, UV absorbance,
Particle counts, Dissolved oxygen, pH, Turbidity
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Finished water on-line monitoring stations will also be installed to monitor the quality
of finished water: Total organic carbon, dissolved oxygen, free chlorine residual,
Turbidity, pH, UV absorbance, particle counts
Modeling Research
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tie together the sensor and monitoring systems to simulation models -- source
water and distributed water
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to predict where contaminant is moving and suggest possible remediation strategies
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calibration of models and feed back loop so that monitors can be used to
continuously self-calibrate the models
Information Management Research
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Develop Real-time data acquisition information network system, a Sensor data
management system, and Data validation and alert system
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Develop Security modules to ensure security policies among the utilities, provide
authentication, fine-grained access control, and secure data transfer
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Web-based user interface and visualization to display alerts, warnings, affected
areas
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Water Security: The Team
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Formed a Consortium
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EPA Region II, USGS, NJDEP, AWWSC, NJDWSC, PVWC, and Rutgers CIMIC
Researchers
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Nabil Adam, Francisco Artigas, Vijay Atluri, Kirk Barrett, Robert Clark (Rutgers
CIMIC), Milton Halem (NASA/Rutgers CIMIC), Yelena Yesha (UMBC)
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End users

Laura Cummings
PVWSC, Eva Ibrahim, American Waters, Pen C. Tao,
NJDWSC, Eric F Vowinkel, USGS
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