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.
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.
Sensors for Intelligent Monitoring of Human Interactions (RA1.1)
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.
Decision Support for Border Operations (RA1.2)
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.
Avatar-based Kiosk for Screening (RA1.3)
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.
Airborne Detection of Illegal Activity in the Border Zone (RA1.4)
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.
Automated Under Vehicle Inspection System (RA1.5)
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.
Checkpoint Effectiveness: Models and Metrics (RA1-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.
Localization and Tracking of Vehicles, Cargo and Persons (RA2.1)
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.
Detection & Tracking of Hidden Objects via Coherent Passive Radar (RA2.2)
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.
Wireless Sensor Network Development for Drug Detection and Cargo Profiling (RA2.3)
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.
Sensors, Evidence Fusion, and Border Intel (RA2.4)
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.
Biometric Identification and Surveillance (RA2.5)
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.
Household Income Profile of Families with U.S. Citizen Children of Foreign-born Parents (RA3.1)
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.
How Will We Know?: Measures of Effectiveness of Border Control (RA3.2)
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.
New Immigrant Survey: BORDERS Award in Immigration Research (RA3-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 (RA3-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.
Risk-based Allocation of Border Security Assets
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?
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.