BORDERS Research


BORDERS is committed to solving real-world border-relevant problems based on scientific data. With new priorities and urgencies developing daily, simply thinking of an idea is not sufficient. Ideas are a dime a dozen. Based on the foundations of design science and the last research mile, our research focuses on creating value by making ideas happen. We build systems using scientific data and develop useful theories from experience on the border. Our research approach can be summarized in the following three steps:

  • Proof of concept: Test to determine whether the technology works. Tackling a real problem, proposing a new solution, listening carefully to reactions, devising a prototype, and testing and evaluating the prototype.
  • Proof of value: Test to determine the value created. Testing whether the prototype is sufficiently robust and functional to solve one important, painful problem. This is established in the lab and the field.
  • Proof of use: Test to determine wide-spread use. This involves transferring the product to end-users and creating customized systems.

Our 3-step research methodology unravels the complexities of border security problems and an understanding of what is really going on. This results in useful advice for operational personnel and policy makers and lasting value for society in actionable terms. 

The National Center for Border Security and Immigration (BORDERS) utilizes a design-science research approach. The design-science research approach consists of building systems and theories based on scientific data to solve real-world problems. It seeks to extend the boundaries of human and organizational capabilities by creating new and innovative systems, constructs, models, methods, or instantiations. Using the design science approach, knowledge and understanding of a problem domain and its solution are achieved in the building and application of these innovations [1].

Examples of design science research at BORDERS include:

  • GroupSystems to aid group collaboration
  • Embodied conversational agents to automate rapid screening
  • The Structured Programming for Linguistic Cue Extraction (SPLICE) tool for linguistic analysis
  • Sensor networks (eye tracking, kinesic, vocalic, and linguistic sensors)  for deception detection

As outlined by Hevner and colleagues [1], the design-science approach can be summarized in the following seven guidelines:

  • Guideline 1: Produce a viable innovation such as a construct, model, method, system or product.
  • Guideline 2: Develop technology-based solutions to important and relevant real-world problems.
  • Guideline 3: Use rigorous evaluation methods for the design.
  • Guideline 4: Provide clear and verifiable research contributions.
  • Guideline 5: Utilize rigorous methods in both the construction and evaluation of the innovation.
  • Guideline 6: Rely on available means to reach a desired outcome while satisfying laws in the problem environment.
  • Guideline 7: Disseminate knowledge to both academic and practitioner communities.

Works cited:

[1] Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research. MIS Quarterly, 28(1), 75–105.

If you build it, they will use it ... if you are willing to go ... the last research mile.

The BORDERS Center is committed to developing cutting-edge technologies to assist homeland security in completing national security objectives. While a majority of our research is conducted in laboratories and other research facilities, the end-goal of our research is field testing and implementation. Our commitment to delivering high-quality systems and technologies to our partners is evidenced by our reputation of going the last research mile. In practical terms, this means collecting quality data that is complete, consistent, accurate, realistic, and relevant.

A common approach to research is simply developing an idea, but failing to implement that idea or develop it further. There is often a misconception that the gap between the lab and the field is narrow and can easily be bridged. Unfortunately, this approach rarely results in a fully-functional tool ready for use. The following three statements concisely represent the problems associated with failing to go the last research mile:

  • Your “interesting idea” is naïve until someone takes it through the last mile.
  • Your understanding is rudimentary until you go through the last mile.
  • The work you have done is trivial until it has been worked through the last mile.

The previous statements stress the importance of studying an idea in depth and transitioning that idea into a prototype that can be tested in the field. While some researchers are concerned that an idea may be “stolen” from them, they fail to recognize that the insights gained from going the last research mile cannot easily be derived.

An example illustrating the importance of going the last research mile is the 1969 mission to the Moon. What if the astronauts had stopped one mile before landing and never touched down on the surface of the Moon? The following quote from Neil Armstrong demonstrates the insight and knowledge that can be gained by going to last research mile.

“Experts had, prior to the flight, predicted…difficulty might be encountered attempting to work on the surface of the Moon due to the variety of strange atmospheric and gravitational characteristics that would be encountered. This didn't prove to be the case. After landing we felt very comfortable in the lunar gravity. It was, in fact, preferable both to weightlessness and to the Earth's gravity.”

Payoffs from Going the Last Mile

The payoffs that can achieved by taking research the “last mile” are as follows:

  • Understanding what is really going on
  • Unraveling the complexities
  • The satisfaction of having made a difference
  • It is where the value to society is created
  • It is where you can make a lasting difference


To respond to DHS identified interest areas and contribute to the public good, BORDERS focuses on three research areas: 

  • Research Area (RA) 1 – Detection, Identification and Screening
  • Research Area (RA) 2 – Sensor Networks and Communication
  • Research Area (RA) 3 – Immigration Policy and Enforcement 

RA 1 – Detection, Identification and Screening

The objectives of RA1 are (1) to effectively distinguish between legitimate travelers at Ports of Entry and those who seek to do harm, (2) better detect people and vehicles attempting to enter the country illegally, and (3) look into questions that are discriminating for deception detection. In these projects, the overarching aim is to transition technologies that are cost-efficient, have minimal errors, and respect individuals’ rights and privacy.

RA 2 – Sensor Networks and Communication

RA 2 addresses the challenges and limitations of individual sensors and sensor networks deployed at and between Ports of Entry. The overarching aim of this research area is to develop inherently resilient surveillance and tracking systems that offer realistic solutions for deployment in the field.

RA 3 – Immigration Policy and Enforcement

RA 3 examines a multitude of both legal and illegal immigration related issues in the U.S. Examples include the economic impacts of immigration policy, workforce enforcement programs, metrics for effective border control, and the dynamics and size of the undocumented and legal immigrant populations.  The overarching aims of this research area are to reduce incompatible and ad hoc policy development through non-partisan, first-class research and to provide meaningful, accurate and sustainable metrics to the discussion.

AVATAR - Automated Virtual Agent for Truth Assessments in Real-Time

University of Arizona

There are many circumstances, particularly in a border-crossing scenario, when credibility must be accurately assessed. At the same time, since people deceive for a variety of reasons, benign and nefarious, detecting deception and determining potential risk are extremely difficult. Using artificial intelligence and non-invasive sensor technologies, BORDERS has developed a screening system called the Automated Virtual Agent for Truth Assessments in Real-Time (AVATAR). The AVATAR is designed to flag suspicious or anomalous behavior that warrants further investigation by a trained human agent in the field. This screening technology may be useful at Land Ports of Entry, airports, detention centers, visa processing, asylum requests, and personnel screening. 

The AVATAR has the potential to greatly assist DHS by serving as a force multiplier that frees personnel to focus on other mission-critical tasks, and provides more accurate decision support and risk assessment. This can be accomplished by automating interviews and document/biometric collection, and delivering real-time multi-sensor credibility assessments in a screening environment. In previous years, we have focused on conducting the basic research on reliably analyzing human behavior for deceptive cues, better understanding the DHS operational environment, and developing and testing a prototype system.

Principal Investigators: Aaron Elkins, Doug Derrick, Jay F. Nunamaker, Jr., Judee Burgoon

New Immigrant Survey

University of Arizona

Little is known about the origins of legal immigrants, other than their countries of birth or last residence. We currently know little about their pre-immigration labor market experiences and the ability of immigrants to translate those experiences into labor market success in this country. A key to a more coherent picture of the American migration experience is knowing why immigrants choose to migrate to the U.S. and the factors that make this decision permanent or temporary. We also need a better understanding of the factors affecting the assimilation of immigrants and their children.

This project enlists leading and promising researchers to utilize the New Immigration Survey (NIS) data in statistical and quantitative analyses of immigration. Awards will be given based on the innovativeness and quality of the proposed research and use of NIS data, including faculty awards of $30,000 each and young researcher awards (postdoctoral fellows or doctoral students) awards of $12,000 each. 

Biometric Identification: Research Directions

West Virginia University

The past two decades has seen a substantial increase in biometrics activity accompanied by the deployment of biometric systems in diverse applications ranging from laptop access to border control systems. The inclusion of biometric evidence in military and criminal courts necessitates a careful examination of the scientific basis for biometric recognition. In particular, there is an urgent need to systematically review the scientific literature to determine if some of the common assumptions made about biometric traits with respect to criteria such as universality, uniqueness, permanence, measurability, performance, acceptability and circumvention, is borne out in the academic literature. Thus, the purpose of this study is to:

(a) Identify gaps in existing research and the implications on operational system risks; and

(b) Provide recommendations for further research and deployment scenarios. Pupil Dilation Characterization and Mitigation Studies

Principal Investigators: Arun Ross, Bojan Cukic

Border Patrol Checkpoint Effectiveness: Models and Metrics

University of Arizona

The Checkpoint Study project has been initiated to help Customs and Border Protection - Office of Border Patrol (CBP-OBP) assess the effectiveness of traffic checkpoint operations for the public good. The key goals of the project are to evaluate and address 1) checkpoint data integrity, consistency and accuracy, 2) measures of checkpoint impacts on local communities and 3) effectiveness metrics and models, as pointed out in the GAO Report No. GAO-09-824. 

Principal Investigators: Jay F. Nunamaker, Jr.

Localization and Tracking of Vehicles, Cargo and Persons

University of Minnesota, Twin Cities Campus

The overall objective of the work in this project is to develop solutions for accurate, cost effective and reliable tracking and localization of designated vehicles and cargo entering the country via the borders. The solutions developed use (to the maximum extent possible) existing technologies and are therefore cost effective. The solution developed for vehicle tracking leverages the wide-acceptance of GPS as a solution for fleet tracking. It adds to this advanced signal processing techniques to ensure that designated vehicles cannot spoof or deceive tracking efforts, thereby, providing assurance that a vehicle has (or has not) traveled along a designated route. The cargo tracking solution does the same for individual pieces of cargo (separate from the vehicle) that may be moved from one vehicle to another in the process of transit.

Principal Investigators: Demoz Gebre-Egziabher

An Assessment of CBP Consequence Delivery Programs

Migration Policy Institute

Consequence delivery programs (including Expedited Removal, Operation Streamline, Mexican Interior Repatriation Program, Alien Transfer Exit Program, and Operation against Smugglers Initiative on Safety and Security) have been adopted across the Southwest Border, though most extensively in the Tucson Sector. Recent declines in apprehensions suggest these programs may be among the factors deterring repeat illegal entries. We will assess the effectiveness of various consequence programs by reviewing the literature, meeting with technical and policy experts, visiting the Tucson Sector to meet with Border patrol staff, and analyzing CBP IDENT data to identify recidivism rates (i.e., patterns of repeat illegal entry attempts). Following the site visit and data analysis, we will discuss findings at an invitation-only roundtable with technical and policy experts similar to those assembled for our previous border metrics project. We will produce a report summarizing our findings and the roundtable discussions, and drawing conclusions about the deterrent impacts and overall effectiveness of consequence delivery programs.

Principal Investigators: Doris Meissner

Determinants of DACA Applications: A Multi-level, Bi-national Study of Incentives, Deterrents, and Consequences of Decisions to Seek Deferred Action for Childhood Arrivals

University of California - San Diego

This project will identify and estimate factors affecting the rate of applications to the Deferred Action for Childhood Arrivals (DACA) program. Our core research question is how immigrant communities in the United States and Mexico are interpreting and responding to DACA, and how these responses determine who applies for the program and who does not. We will study determinants of application decisions that operate at both the individual and receiving-community level. We will also document the short-term consequences of participation in the DACA program on immigrant integration. Our methodological approach to these questions will combine field surveys in southern California and Oaxaca, Mexico with analysis of individual-level data on DACA applicants obtained via Freedom of Information Act (FOIA) requests. The aim of the research is to provide guidance for improving program administration and increasing participation among DACA-eligible immigrants.

Principal Investigators: Wayne Cornelius

Coverage Estimates of the U.S. Mexican-Born Population and Measures of Unauthorized Migration

University of California-Irvine

Information about the extent to which the Mexican born are captured in U.S. Census surveys directly feeds into estimates of the total unauthorized Mexican population, yet little is known about their coverage error. Our earlier BORDERS-supported research used two methods (the net migration and death registration methods) to produce coverage error estimates for 1995 through 2005. We now plan to update, extend, validate, and extrapolate these results. We have four objectives: (1) to update the earlier estimates using the death and migration methods through 2010, (2) to extend the research by adding estimates using a third method, a birth registration method, for the entire 1995-2010 period, (3) to validate the results by conducting robustness checks on the results, and (4) to extrapolate the findings on Mexican-born coverage in order to assess of the adequacy of the levels of undercount used in current estimates of unauthorized Mexican migration.

Principal Investigators: Frank Bean

Development and Testing of a Cell-Phone Signal Based GPS-Denied Navigation System for Small UAVs

University of Minnesota

A prototype Small UAV (SUAV) navigation system capable of generating a Position, Navigation and Time (PNT) solution in GPS-denied, urban operational environments will be developed.  The system generates a PNT solution by relying on a Dead Reckoning (DR) navigator as a core (or inner-loop) sub-system aided by periodic position fixes from cell-phone signals.  The DR system uses sensors that are typically found on SUAV autopilots (namely, an Inertial Measurement Unit or IMU; a magnetometer triad; and an air speed sensor or pitot tube) to generate a high bandwidth solution of position, velocity and attitude.  To mitigate DR system drift, cell-phone signals will be used to periodically generate a position fix (and a timing solution) which is fused with the DR system solution via an Extended Kalman Filter (EKF).  The cell-phone position fixes are generated by a machine learning code which determines the cell-phone signal “finger print” of a given area.

Principal Investigators: Demoz Gebre-Egziabher

Pupil Dilation Characterization and Mitigation Studies

This study will focus on the design of a mathematical model for characterizing the dynamics of the pupil and the iris of the human eye in response to changes in ambient light. In particular, the study will establish if existing iris normalization models, used by several commercial iris recognition systems, have to be modified in order to account for the non-linear geometric deformations observed in the iris texture in response to changes in external illumination. This study is expected to impact the design of iris recognition systems and is, therefore, critical to Homeland Security.

The work will be undertaken in 4 different tasks:

  • Task 1 - Modeling Pupil Deformation
  • Task 2 – Data Collection
  • Task 3 – Model Evaluation
  • Task 4 – Dilation Mitigation Model

Principal Investigators: Arun Ross

Post-apprehension Survey of Undocumented Immigrants

University of Arizona

The Post Apprehension Survey project was initiated by the Office of Immigration Statistics (OIS) to assess the intent of an apprehended illegal alien to re-enter the United States and the underlying reasons for their intent to re-enter.  As part of the study, the research team captured migration histories in terms of attempts and successes/failures, intent to re-enter, factors influencing decisions to re-enter in the future, and background and demographic information from 1,000 unauthorized immigrants apprehended in the Tucson sector. Thirty-seven survey items were crafted in the following six areas: demographics, relatives, reason for crossing, apprehension experience, current attempt and future plans.

Principal Investigators: Jay F. Nunamaker, Jr.

E-Verify: Profile of Enrolled Employers

University of Arizona

Using data from the USCIS transactions database, this project proposes to examine the profile of companies using E-Verify in two states: Arizona where its use is mandated by state law, and Nevada where no such requirement exists in state law. The proposal is in two phases. Phase I is to be completed in year one of the effort and would inform implementation of Phase II in a subsequent year.

This project would work with data provided by USCIS on company E-Verify enrollment in Arizona and Nevada including company name, NAICS code, date of enrollment, and number of E-Verify screenings per month from time of enrollment to the present. These company names and NAICS codes would be cross-referenced with state and private data sources such as Dunn and Bradstreet to determine company size, verify its industry code, and profile the number and size of other employers in a given NAICS code in each state. Aggregating within NAICS codes for each state, trends in the number of monthly E-Verify screenings would be compared to trends in monthly employment data from the Bureau of Labor Statistics in order to measure the extent of their correlation.

Once the analysis is completed, the project team will meet with appropriate representatives from USCIS and other stakeholders within DHS to determine whether Phase II should be undertaken and to specifically define the questions to be addressed in Phase II.

Principal Investigators: Judith Gans

Sensors for Intelligent Monitoring of Human Interactions (RA 1.1)

University of Arizona

In this project, we will evaluate sensors and develop prototypes for intelligent monitoring of human interactions to detect deception and malicious intent. As a result, we will generate knowledge and prototype systems capable of augmenting human screeners in detecting deception and assessing intent at border entry points. To accomplish this objective, we will conduct a series of experiments to test the efficacy of advanced motion detection systems in detecting deception and hostile intent, evaluate the effectiveness of using an eye tracker to conduct guilty knowledge tests, develop algorithms for sensor fusion, and develop the third version of the SPLICE software for linguistic analysis. The knowledge gained will be communicated to DHS end-users to improve screening activities.  We will also combine this knowledge with knowledge garnered from previous years’ validation of linguistic, vocalic, and kinesic sensors and cues of deception to create integrative systems to support DHS operations.

Principal Investigators: Jay F. Nunamaker, Jr., Judee Burgoon

Decision Support for Border Operations (RA 1.2)

University of Arizona

The goal of this project is to enhance existing border processes with automated tools developed in projects underway in the COE. Specifically, the next phase of this project will take the information gained from studies conducted through the first three years and apply it to new technologies designed to address critical border agent needs. It will assist existing border screening decision processes and constraints. We will test novel mechanisms and technologies for delivering real-time alerts of suspicious activity to determine their effectiveness for improving screening decisions in an operational environment. We will also explore methods to improve agent interaction with expert systems. The ultimate impact of this research is to disseminate best practices for screening and present agents with effective real-time decision tools.

Principal Investigators: Jay F. Nunamaker, Jr., Judee Burgoon

Avatar-based Kiosk for Screening (RA 1.3)

University of Arizona and University of Nebraska at Omaha

We will continue to develop a flexible kiosk platform that can present avatars to subjects in rapid assessment scenarios and is equipped with a variety of instruments to record the subject’s physiological and behavioral reactions during screening.  We have completed several rounds of experiments and built the second-generation kiosk.  For year four, we have five primary objectives: develop a real-time algorithm for fusing vocalic and ocular data to determine veracity; implement a screening interview in Spanish and determine vocalic data baselines for Spanish; evaluate a stereoscopic camera for integration into the kiosk; incorporate into the kiosk the ability to perform biometric identification using facial recognition and fingerprints; and develop the ability to perform automated I-94 application processing.

Principal Investigators: Doug Derrick, Jay F. Nunamaker, Jr., Judee Burgoon

Airborne Detection of Illegal Activity in the Border Zone (RA 1.4)

San Diego State University

The Department of Geography at San Diego State University (SDSU) is developing techniques for automated detection of people and vehicles moving through the border region using high spatial resolution airborne imagery. The approach utilizes low cost platforms such as light aircraft (LA) or unmanned aerial vehicles (UAV) for repeat imaging over short time periods of minutes to hours depending on the border response zone (i.e. urban, rural, and remote). Specialized image collection and preprocessing procedures are utilized to obtain precise spatial co-registration (i.e., alignment) between multitemporal image frame pairs. In addition, specialized change detection techniques are employed in order to automate the detection of people and vehicles moving within the border region. Once people or vehicles are detected, small image chips showing the detection result may be wirelessly transmitted from the aircraft to command and control stations on the ground for immediate review and interdiction response.

Principal Investigators: Doug Stow

Automated Under Vehicle Inspection System (RA 1.5)

University of Arizona

A major challenge for DHS is how to stem the illegal flows of drugs, cash, weapons and people across our borders while facilitating legal travel and commerce to keep the American economy prosperous and competitive. This project is focused on the development new technologies and techniques to support the inspection and identification of high-risk vehicles at ports of entry and at check points.  A prototype automated under vehicle inspection system was developed by a team of engineering seniors as part of their multidisciplinary senior capstone course. This prototype used image processing software to scan the under carriage of a vehicle as it drives over a speed hump. The scanned image is compared to a known image from a database for the year, make, and model of the vehicle. Anomalies are detected and suspicious objects are highlighted. Vehicles are sent to a secondary inspection with the information about the suspicious objects where a more comprehensive inspection can be undertaken. The prototype system is being enhanced as a graduate research project to improve the capabilities and performance.

Principal Investigators: Larry K. Head


Checkpoint Effectiveness: Models and Metrics (RA 1-S.1)

University of Arizona

The Checkpoint Study project has been initiated to help Customs and Border Protection - Office of Border Patrol (CBP-OBP) assess the effectiveness of traffic checkpoint operations for the public good. The key goals of the project are to evaluate and address 1) checkpoint data integrity, consistency and accuracy, 2) measures of checkpoint impacts on local communities and 3) effectiveness metrics and models, as pointed out in the GAO Report No. GAO-09-824.  We will continue to work closely with OBP through the duration of the project.  This project is a continuation from Year 3 using prior year funds that will support the remaining effort.

Principal Investigators: Jay F. Nunamaker, Jr.

Localization and Tracking of Vehicles, Cargo and Persons (RA 2.1)

University of Minnesota, Twin Cities Campus

The goal of this project is to develop solutions for accurate, cost effective and reliable tracking and localization of cargo (and the vehicles carrying them) entering the country via the borders.  Being able to track and monitor shipments while in transit from their starting point (a factory, farm, warehouse) until they reach their destination allows us to detect potentially anomalous behavior en-route such as loading and unloading of contraband and, therefore, enhance the efficiency and effectiveness of the inspection process at the borders.  In addition, solutions for tracking individual pieces of cargo (separate from the vehicle) are being developed.   This allows tracking cargo that that may be moved from one vehicle to another in the process of transit.   The solution developed leverages the wide-acceptance of GPS as a solution for fleet tracking.   However, it adds new and advanced signal processing techniques to the existing technology to ensure that designated cargo carrying vehicles cannot spoof or deceive tracking efforts, thereby, providing assurance that a cargo has traveled along a designated route. 

Principal Investigators: Demoz Gebre-Egziabher

Detection & Tracking of Hidden Objects via Coherent Passive Radar (RA 2.2)

University of Washington

Border security is centered around detection and prevention of human and other contraband from covertly (and illegally) entering the U.S. However, the varied terrain of the northern and southern borders makes this a daunting task. While the southern border is characterized by deserts, mountains and urban areas, the topology of the northern border contains mountains, forests, farms, prairies and lakes. As such, the reliable detection of humans and goods crossing a perimeter continues to be a largely unsolved problem. The technical causes for this are multi-faceted, but can be largely attributed to the limitations and challenges of different sensing modalities in complex, unknown environments. Previous research suggests that a collaborative networking architecture that exploits the presence of opportunistic signals in a passive coherent imaging framework, along with appropriate suite of algorithms and decision mechanisms, are essential for enhancing performance of present-day border security apparatus and mechanisms. Our investigation focuses on the use of Radio frequency electromagnetic approaches for enhanced remote imaging in conjunction with a suitable network support infrastructure. The proposed work refines techniques developed at UW over many years and leverages current/recently funded research by other DoD agencies. These new methods will exploit existing sensing infrastructure and signals of opportunity using all available (time, frequency and spatial) information. The primary outcomes of the effort will be new tools for DHS to employ and evaluate in specific interdiction scenarios and terrains.

Principal Investigators: Sumit Roy, Yasuo Kuga

Wireless Sensor Network Development for Drug Detection and Cargo Profiling (RA 2.3)

University of Arizona

This project is aimed at using Wireless sensor networks (WSNs) for providing automated monitoring, target tracking, and intrusion detection.  State-of-the-art solar-powered WSNs that adopt innovative sensors with low power consumption and forefront networking technologies are needed for achieving rapidly deployable situational awareness and effective security control at the border at low cost.  This project will provide DHS with prototypes of new sensing technologies by developing novel sensors including ultra-sensitive all-optical fiber magnetic field sensing for cargo profiling and novel drug detection based upon high power terahertz sources.  Other practical issues in WSNs, including sensing data classification, survivability under harsh weather conditions, and efficient sensor deployment will be considered. The project responds to the most urgent needs as identified by DHS in border security, notably the identification of drug smuggling activities.  Upon development, the developed system will be used as a flexible wireless surveillance network platform integrated with customized sensors for security screening along border crossings and in other significant locations for DHS over long time periods with minimal human maintenance.

Principal Investigators: Mahmoud Fallahi, Nasser Peyghambarian, Robert A. Norwood, Stanley Pau

Sensors, Evidence Fusion, and Border Intel (RA 2.4)

University of Arizona

Many DHS applications involve processing of multiple kinds of data, generated by different types of sensors or extracted from a variety of databases. The “Sensors, Evidence Fusion, and BorderIntel” project of the BORDERS Center aims to develop novel algorithms and software systems to facilitate fusion of data and signals from multiple sources. We are currently conducting research in two DHS applications. The first is concerned with how to improve the accuracy of intent and deception detection through the use of multiple sensors (e.g., vocal analyzer and eye tracker). The data fusion software is being integrated as part of intelligent interview kiosks for secondary screening at border crossings. Our preliminary results indicate that significant improvement in detection performance can be achieved by intelligently fusing clues identified by different sensors.  The second application is concerned with developing a data fusion framework called “BorderIntel” to analyze heterogeneous data from multiple law-enforcement, border surveillance, and reconnaissance data sources. The focus is on analyzing in an integrative manner criminal records and vehicle crossing information.

Principal Investigators: Daniel Zeng, Hsinchun Chen

Biometric Identification and Surveillance (RA 2.5)

West Virginia University

International travelers pass through US borders every day.  Determining the identity of each traveler has become a matter of national security.  Biometrics is the science of personal identification from the appearance of ones face, or fingerprints, palm prints, body dimensions, etc.  This project investigates prompt, nonintrusive and privacy preserving identification of international passengers.  The research challenges include the accuracy of biometrics given the growing border traffic as well as the design of resilient surveillance systems that can achieve positive identification of travelers before they reach a border inspection point.  

Principal Investigators: Arun Ross, Bojan Cukic, Don Adjeroh, Lawrence A. Hornak

Household Income Profile of Families with U.S. Citizen Children of Foreign-born Parents (RA 3.1)

University of Arizona

This project examines household incomes of families with U.S. citizen children according to whether their parents are immigrants or native-born citizens.  The project will look at state-by-state data on children under the age of 18, detailing the number of children in households with 2 native-born parents, the number of children in households with one foreign-born parent, and the number of children in households with two foreign-born parents. This data will be combined with state-level data on the income distribution of these households according to the nativity of parents and will provide insight to a number of issues including:

  • The extent to which immigrants are impacting the growth of state populations;
  • The extent to which US citizen children of immigrants are more likely to be poor and therefore likely to rely more heavily on the social safety net.

Principal Investigators: Judith Gans

How Will We Know?: Measures of Effectiveness of Border Control (RA 3.2)

Migration Policy Institute

The need for effective border enforcement is a widely-shared point of agreement in the national immigration debate. But what defines effective border control?  Historically the Border Patrol has defined “operational control” based on apprehensions—i.e., arrests of people attempting to cross illegally. This project seeks to move beyond apprehensions to explore more comprehensive measures of border enforcement effectiveness. Information potentially useful for developing new measures includes “hits” in technology systems (such as sensors) that suggest people have evaded capture, data on migrant smuggling and smuggling prices, crime rates in US border communities, and the expert opinions of Border Patrol agents and others in the field. The project’s goal is to recommend a “standard” for border enforcement effectiveness based on a review of existing research, interviews with Border Patrol and other DHS personnel, and an assessment of the available data. Once such a standard can be developed and scientifically defended, it should be useful both in evaluating the cost-effectiveness of DHS activities and in informing future debates about border enforcement and other US immigration policies.

Principal Investigators: Doris Meissner, Michael Fix

New Immigrant Survey: BORDERS Award in Immigration Research (RA 3-S.2)

University of Arizona

Immigration processes and policies continue to be the subject of much political and scientific debate. While immigration now accounts for one-third of U.S. population growth, the U.S. has never had a nationally representative survey of immigrants and their children. In perhaps no other area of public policy is there such a large gap between information needs and existing data. The New Immigrant Survey’s (NIS), a longitudinal study partially funded by the Department of Homeland Security and the Department of Health and Human Services, was developed to examine these issues. Its main objective is to provide a public use database on new legal immigrants to the United States and their children that will be useful for addressing scientific and policy questions about migration behavior and the impacts of migration.

This project will use this database to support statistical and quantitative analyses on immigration and its impacts. In addition, it will provide research that compares the NIS with comparable major U.S. longitudinal surveys, thus facilitating comparisons of immigrants and the native-born. This will be accomplished by funding accomplished immigration researchers through a competitive award process, administered by BORDERS.

E-Verify: Profile of Enrolled Employers (RA 3-S.3)

University of Arizona

This project compares the profile of two groups of employers in Arizona:  those that HAVE enrolled in E-Verify and those that HAVE NOT enrolled in E-Verify.  These two groups of employers are examined in order to identify whether there is a pattern of enrollment by industry code or by company size. Information on Arizona employers using E-Verify is compared to that of employers not enrolled in E-Verify in spite of a legal requirement to do so.  The same analysis is done for Nevada in order to develop a comparative profile of employers who choose to use E-Verify absent a legal requirement to do so.  In addition to examining E-Verify enrollment, this project examines how often companies use E-Verify in Arizona and Nevada once enrolled in the program. Data on the number of E-Verify screenings per month is aggregated by industry and compared with Bureau of Labor Statistics data on monthly changes in employment by industry for Arizona and Nevada in order to see how well they track.

Principal Investigators: Judith Gans

Risk-based Allocation of Border Security Assets

RAND Corporation

The U.S. border is so vast and the time required to cross the border is so small that there may never be enough resources to control large areas of the border at all times. Thus, while policies may change and technologies may mature, DHS and its operational components may always confront choices and trade-offs that dictate where and when to position limited people, technology and infrastructure. Customs and Border Protection (CBP) is investing in tools (e.g., platforms in the CBP Analytical Framework for Intelligence) and methods (e.g., the Intelligence Predictive Planning Process) that may facilitate decision-making about resource allocations by helping its agents identify pattern and trends in historical interdictions. The methods and tools offer approaches to allocating border security assets based on criteria of risk. In this project, we asked: what risk-based resource allocation approaches are most effective and how do effectiveness depend on the operational environment? 

Principal Investigators: Henry Willis, Joel B. Predd

Organization and Networks of Transnational Gangs

Arizona State University

Going beyond a doorstep defense of U.S. security requires developing strategic responses to serious threats at some distance from U.S. borders. One such threat is that of third-country nationals who use Mexican territory as a gateway to enter the U.S., often legally, to engage in criminal activity or to commit political violence. This project extends existing studies of transnational criminal gangs in Central America to anticipate methods and approaches that could be used by third-country nationals to commit crime or politically-motivated violence in the United States. The two primary objectives of this study include: 1) further understanding the organizational structure and sophistication of transnational criminal gangs and their capacity to facilitate mobility and migration through Mexico into the U.S.; and 2) further understanding the dynamic social networks of transnational criminal gangs and their capacity to facilitate mobility and migration through Mexico into the U.S.

Principal Investigators: Charles Katz

Software, Demos and Prototypes

Automated Screening Kiosk (ASK)

The ASK is a modular kiosk system for human screening for human credibility risk assessment. The ASK features an automated protocol, conducting a standardized interview that controls for many cultural, demographic, and question type effects. Practical risk assessment applications for the ASK range from insider threat detection to pre-employment screening to pre-audit fraud analysis. The ASK hardware platform is configurable, allowing for rapid experimentation of sensor arrays. The ASK’s broad array of sensors and malleable design assists with discovery the contextualized interrelationships among physiological and behavioral indicators of deception.

Experiments using the ASK system have examined feasibility and interrelationship among oculometric, vocalic, kinesic, cardiorespiratory, galvanometric, and mousing activity during conditions of low veracity. Interviewing paradigms examined or scheduled to be examined include variants of the Concealed Information Test (CIT), Behavioral Analysis Interview (BAI), Control Question Technique (CQT), and novel paradigms.

AVATAR Kiosk for Deception Detection

The AVATAR kiosk is an automated interviewing platform with an embedded artificial agent that is designed to flag suspicious behavior at a port-of-entry that should be investigated more closely by a trained officer.  This primary screening technology is designed for use at ports-of-entry, including border crossings and airports.  The kiosk also has many other security application such as visa processing and personnel screening. 

Biometric Camera for Remote Surveillance and Identification

This project uses camera networks that could be suitable for an airport (or other port of entry) security situation.  In the demonstration, a subject will walk in-between cameras which will accumulate videos, collectively select frames where the face is most visible, and submit only the most promising images to facial recognition software.

Checkpoint Simulation

The Checkpoint simulation model was developed for Border Patrol using Arena software. The simulation assists Border Patrol in resource allocation planning. Using the simulation, Border Patrol can analyze current and expected traffic flows to determine how many resources are needed to reach its goals. The simulation provides a graphical view of Checkpoint wait times, as well as detailed statistics on key Checkpoint metrics such as flushing and apprehensions. Using this tool, Border Patrol can quickly answer "what if" questions about changes at Checkpoints.

Dynamic Embodied Agent for Persuasion

Dynamic Embodied Agent for Persuasion (DEAP) is a comprehensive framework which leverages state-of-the-art software to generate, animate and control embodied agents (EA) to interact with users in a variety of settings.  DEAP has real-time text-to-speech capabilities which will allow it to analyze the verbal responses it receives from its interactants.  The EA's speech is driven by text.  A text-to-speech (TTS) engine is used to translate the text to the spoken word and sync the EA's lips with the speech.  This means the EA's dialog can be changed quickly to respond to changes in its environment.  The framework is also capable of switching to and from different EA's in order to best meet the needs of the current circumstance.  For instance, people are often more comfortable with EA of the same ethnicity.  In addition, our framework has the capability to present EAs with similar facial features as the interactant.  Though it still needs to be automated, this is a fascinating aspect of the DEAP framework.

The DEAP framework has been leveraged to run a number of experiment to study the persuasive ability of EAs.  In one study, the EA's attractiveness and argument quality  was found to have a significant effect when trying to influence users' final decision when making credibility assessments.  In another study, the EAs language power was influential in persuade the users' assessments.

Eye Tracker for Vigilance

Screeners at ports of entry (land, sea, air) must process millions of passengers daily. A potential security risk in this system is fluctuating levels of vigilance and attentiveness on the part of screeners monitoring for contraband, forged documents, etc. The purpose of this project is to demonstrate how eye movements can be monitored and interpreted to measure an individual’s awareness and attention while performing this task. The eye tracker demo will show a system designed to monitor and improve vigilance based on pupillometry and blink rates.

Kinect for Deception Detection

The Kinect (developed by Microsoft) enables us to monitor and display the body position of a person standing in front of a sensor. The demo will show the real-time tracking and modeling of body position and motion which has applications for deception detection research. For example, an individual’s defensive posture (e.g., folded arms) could be indicative of deception, while an open posture may indicate truth telling. Combined with the other sensors in the AVATAR kiosk, the Kinect’s models could improve the accuracy of deception classification.

Micro UAV Sensor Network in Remote Desert Regions

A pilot micro UAV-based field test conducted in Tucson demonstrated the ability to transmit a person’s  physiological data (blood pressure, pulse rate, etc.) from a rugged remote terrain back to a central location for monitoring over an ad-hoc communication network.  The GPS-empowered ad-hoc network would also provide a strong backbone through which other real-time border information could be transferred and collected. This demo will show videos of the field tests and display the Micro UAVs used to transmit the data. 


Structured Programming for Linguistic Cue Extraction (SPLICE) is a linguistic analysis tool. It is available as a web service to aid in the development of applications that need to take advantage of powerful natural language processing techniques. There is also a GUI available. SPLICE is currently in Beta testing.

Visit the SPLICE website.


StrikeCOM is a multi-player online strategy game useful for researching group collaboration. StrikeCOM is designed to foster discourse among group members and has been used as a research tool to study leadership and deception in group decision making. Researchers use this tool to examine the development of group processes, shared awareness, and communication. The groups can be face-to-face or distributed, allowing researchers to investigate how proximity and synchronicity affects group dynamics and group performance.

The game mimics C3ISR (Command, Control, Communication, Intelligence, Surveillance, Reconnaissance) scenarios and information gathering in group activities. Built using Java and a SQL-based collaborative server platform, the game is available for use in almost any computing environment. The U.S. Department of Defense is using the tool to teach Network Centric Warfare to battle commanders. Use of StrikeCOM over the years has resulted in a number of lessons-learned, including using simple, familiar game interfaces, utilizing full and immediate feedback, and creating a flexible technical design to meet shifting research and teaching needs.

The scenario of the game is for group members to collaborate to discover where an enemy is hiding its missiles. Each user sees a topological map and can allocate surveillance and intelligence resources to search for the hidden missiles. The information gathered by one user can be communicated to his/her teammates. Variations of the scenarios include placing a confederate on the team whose secret task is to mislead the team. This scenario allows researchers to study deception and how groups cope. Other scenarios call for the group members to communicate verbally or by instant messaging to research the effects these restrictions have on group dynamics and group performance. This scenario mimics the real-world where groups may be required to collaborate across distance and time using email or instant messaging.

CMI created the StrikeCOM game to meet requirements for advanced data collection and customizability to investigate deception detection within large groups of people. StrikeCOM is designed for flexibility and allows research into any group process or interaction. StrikeCOM provides a multiplayer game capable of supporting any number of players using any number of assets searching a game board of any definable size for any number of targets and target types that the researcher chooses to define. The game includes time stamps for each player interaction with the game. In addition, the game includes map overlays with adjustable geographic information reliability statistics, the ability to have multiple independent target types, and an optional shared results visualization scheme. The game also allows the researcher to configure the game such that any or all of these features can change as the game progresses.

StrikeCOM Research Findings

  • Twitchell, D. P., Wiers, K., Adkins, M., Burgoon, J. K., & Nunamaker, J. F., Jr. (2005, January 3-6). StrikeCOM: A multi-player online strategy game for researching and teaching group dynamics. Proceedings of the 38th Annual Hawaii International Conference on System Sciences (CD-ROM), Waikoloa, HI.

Under Carriage Camera for Vehicle Anomaly Detection

Automated under vehicle inspection systems can be used in primary and secondary inspection at Ports of Entry or Checkpoints. At these locations, the processing must be done in a timely manner, e.g. less than seven seconds for primary inspection. In addition, the false alarm rate must be low and the correct detection rate high. This demonstration will provide an overview of how an automated under vehicle inspection systems would work in the field.