Security Engineering Minor Program

In line with the mission of the Department of Homeland Security (DHS), Texas A&M University-Kingsville (TAMUK), a minority-serving institution, is developing a multidisciplinary curriculum within the college of engineering in support of preparing engineering and science students for careers in areas related to our nation’s security. This multidisciplinary minor in Security Engineering offers courses within the Departments of Mechanical Engineering, Electrical Engineering, and Computer Science and will be fostered by research activities relevant to the DHS-STEM area of interest. This minor program is open to all engineering, math, and science students who, are interested in this field. This minor program focuses on an integrated study of Unmanned Aerial Vehicles (UAV), image processing, data mining, optimization, and information analysis and modeling. These focus areas are being served in operations/areas such as border security, transportation security, computer security, wide-area surveillance, wildfire detection and prediction, visual and data analytics, seismic activity data collection, disaster management and hazards, law enforcement data fusion, integrated data processing and analysis, and complex event modeling, simulation and analysis. Strong collaboration with the University of Texas at El Paso (UTEP), one of DHS Centers of Excellence COEs, Oak Ridge National Laboratory (ORNL), Idaho National Lab (INL), Corpus Christi Army Depot (CCAD) enhances the program through summer research activities and internships.

Earn a certificate in Security Engineering Field
Excellent Career Placement Opportunity
Graduate School Studies

In support of the mission of DHS, the overarching goal of this program is to prepare undergraduate students for the emerging field of engineering (Security Engineering) related to DHS operations. In line with this goal, the objectives of the program are:

● Develop a multidisciplinary undergraduate minor program and certificate program in engineering focusing on Security Engineering.

● Collaborate with the University of Texas-El Paso (UTEP), one of DHS’s Centers of Excellence, to promote DHS-related research for undergraduate students.

● Equip students, who will be issued a certificate in Security Engineering, with technical knowledge and experience in the areas of DHS-related operations.

● Recruit minority undergraduate students into the Security Engineering minor.

● Closely collaborate with DHS Training Centers, Coast Guard, and Federal Emergency Management Agency (FEMA), as well as commercial companies who work on DHS related technology and systems such as Boeing, Raytheon, etc. to meet the needs of the technical workforce, in addition, to continuously improving program outcomes and providing internship and student career placement.

● Developing a multi-domain real-time simulation system for analyzing and optimizing homeland security-related events using information generated from image and data mining.

● Develop techniques to enhance the images for feature extraction and image data mining.

To increase students’ knowledge and improve hands-on skills and prepare them for the professional work environment as well as for graduate studies, teaching activities will be fostered with research activities for undergraduate students. Moreover, each new course will have a research or project component. Topics will be developed in coordination with the DHS Center for Border Security and Immigration at UTEP. Some examples as outlined below.

a.) UAV assembly and operations for wide-area surveillance (Dr. Selahattin Ozcelik, ME)

Motivation: UAVs have proven remarkably useful in the skies since they have been used for various military operations and are being used by CBP’s Office of Air and Marine for border surveillance and reconnaissance. Increasingly, DHS has explored the use of UAVs in support of the U.S. Border Patrol’s mission to augment its agents’ ability to patrol the border. Apparently, UAVs are becoming an integral part of DHS in border security as well as for purposes of surveillance and reconnaissance during natural disasters. Therefore, this project aims to give hands-on experience to students in the fundamentals of flying mini aircraft equipped with a vision system.

Project Description: The project will involve the operation of a small-scale remotely controlled aircraft for surveillance and image capturing tasks. The project will involve the assembly of some equipment, design, and development of necessary interfacing for communication between the airplane and ground station, and collection of video recordings and images and analyze them for the given tasks of the project.

Undergraduate Research Opportunities: Students in teams will have the opportunity to gain hands-on experience on simple UAVs. Multidisciplinary teams formed by students from different engineering and science majors will learn major components of UAVs, investigate how to control a UAV and how to design communication and vision systems. They will also investigate image capturing techniques.

b.) Image Enhancement Techniques with Spatial Domain Filters/ Edge Detection for Homeland Security Applications (Dr. Nuri Yilmazer, EE)

Motivation: The images taken from the UAV cameras contain some undesired effects such as noise, EM interference, and degradations effects. These unwanted effects can be minimized by applying some pre-processing and filtering techniques as well as restoration techniques. The images usually contain Gaussian, impulse noise as well as periodic noise usually arises during the image acquisition from electrical or electromechanical interference which is spatially dependent noise. There are signal processing techniques that can be used for restoring the degradations in the images. The objective of this work is to reduce noise in UAV images.

Project Description: In this project, spatial filtering techniques will be investigated to enhance the images. The students will investigate some spatial filtering techniques such as mean filters, order-statistic filters, and adaptive filters for noise reduction in images. Sharpening spatial filters known as Laplacian and Gradient filters will be employed as well as some intensity transformations such as log, power-law transformations, histogram equalization, and matching techniques to enhance the images.

Undergraduate Research Opportunities: Students will participate in developing image processing techniques to enhance the images. They will conduct the simulations by using MATLAB programming. The students will learn the spatial filtering techniques and edge and line detection techniques which are widely used in the image processing field. They will gain a great in-depth of different types of filters and compare the performances of each one of them.

c.) Multi-Objective Optimization and Decision Making Model for Security Control (Dr. Kai Jin, IE)

Motivation: Operations research (OR) has had a long and distinguished history of work in homeland security applications. OR models and algorithms have been developed and used in airline security, transportation of hazardous materials, emergency preparedness and response, and threat analysis. However, papers on border security are just beginning to appear recently.

Project Description: Most of current border security research is using fingerprint images to detect the entry of criminals, suspected terrorists, and illegal immigrants. In this proposal, we propose to use UAVs to catch images, and then use image data mining to identify the patterns of suspected illegal behaviors and individuals. After that, optimization and decision-making models will be used to schedule the border’s control inspection activities and locations. A multi-objective optimization and decision-making support model will be developed to minimize the illegal entry to the states and threat risk using the available resources.

Undergraduate Research Opportunities: Students will participate in developing the decision-making support system. They will conduct the simulations by using SOLVER and MATLAB programming. The students will learn and use the different approaches and tools to solve multi-objective optimization problems.

d.) Data Processing and Mining (Dr. Mais Nijim, CS)

Motivation: Data mining is becoming one of the fastest-growing technologies as the need is becoming more to find the important information and features from the captured data. As it is well known, not all data captured is important and related to the problem. This is the case especially, in video and image capturing for purposes of surveillance and monitoring, in which data is collected on a regular basis and analyzed for later use. There is a need to identify and develop algorithms to classify and find the related data. There are some image processing techniques and data mining algorithms that could be used for the purpose of classifying images into clusters for analysis and usage. The major objective of this work is to come out with the best image mining approach that effectively classifies images and model them for real-time usage.

Project Description: The process of capturing images for monitoring and remote sensing is becoming very important. There are several mining algorithms that could be used and developed to extract patterns and behaviors from these images. In this project, we will focus on several feature extraction techniques along with image processing and analysis algorithms and several prediction schemes. There are several advantages to using data and image mining to extract patterns and features from the captured images. Several preprocessing, processing, and post-processing image mining algorithms will be developed. These algorithms will find the patterns and cluster the features together while storing them so that it is easier to extract features and help semi-automating the whole process from capturing to storing.

Undergraduate Research Opportunities: Students will participate in developing image and data mining techniques that will help in the image mining algorithms. Students will be able to learn the current related theoretical algorithms and conduct simulations. They will learn feature extractions and predictions that could be used in other computer science or engineering-related fields. This will broaden the knowledge of the students in real-life applications and help them develop their skills for practical problems that face them as they use and collect information for their personal and professional use as they graduate.

e.) Information Analysis and Modeling (Dr. Hua Li, IE)

Motivation: Improved analysis and decision-making tools are part of the representative technology needs. The effort is needed to research ways to fully integrate multiple domains, including technology, managerial, policy, organizational, political, and contextual, to enhance decision making. The man-made events are stochastic and hard to control because almost every single event is unique and represents its own specific situation. Meanwhile, it is not feasible to evaluate the efficiency and effectiveness of different response policies using actual, real homeland security events which have great impacts on national security. The major objective of this work is to improve the efficiency and accuracy of information analysis and modeling related to homeland security.Basic.net to conduct information analysis and modeling. They will also collect necessary information and data from various national databases, such as the global terrorism database. By participating in this project, students can improve their simulation and modeling skills and increase their awareness of homeland security-related issues.

Project Description: Simulation-based optimization (so-called simulation optimization) has become an active research area in homeland security. Many simulation optimization techniques have been developed, e.g., scatter search and surrogate search, but few place emphasis on the evolutionary perspective of decision making for dynamic systems. Furthermore, a substantial number of simulation evaluations are normally required to obtain a satisfactory solution. This has not been feasible in real-time decision-making cases where large-scale, expensive simulations are involved. This proposed research project will develop efficient simulation optimization algorithms to assist in making high-quality, timely decisions and managing online systems. The algorithms will utilize analytical formulations and offline experimental results to guide the online search and provide near-optimal solutions quickly. The methodology will have many potential applications for the limited homeland security resource decision-making problems.

Undergraduate Research Opportunities: Students will participate in developing and optimizing the simulation algorithms. They will learn and use Arena and Visual Basic.net to conduct information analysis and modeling. They will also collect necessary information and data from various national databases, such as the global terrorism database. By participating in this project, students can improve their simulation and modeling skills and increase their awareness of homeland security-related issues.

The project is expected to result in the following significant outcomes:

● A lasting change on the engineering discipline at TAMUK by establishing a Minor/Certificate program in Security Engineering.

● Attracting more Hispanics students to the minor in Security Engineering program. Since TAMUK is a Hispanic Serving Institution and the South Texas area is predominantly Hispanic, this project will also have a lasting impact for underrepresented students.

● Undergraduate students with different backgrounds will graduate from this minor program due to the multidisciplinary nature of the program integrated with research opportunities at UTEP.

● More engineering students of Hispanic descent will be graduating with technical knowledge and experience on Security Engineering.

● Through internships, summer research, and visits with CBP Air and Marine Operating Locations, Coast Guard, UTEP, and FEMA, better hands-on skills will be attained by students.

● Enhanced career placement opportunities in security engineering for minority students through internships/summer research at UTEP, national labs, DHS centers, and related industries.

● Initiation, fostering and development of young investigators faculty research collaborations DHS COEs as well as DHS operations sites.

● Improved faculty teaching effectiveness through the preparation of the fundamental security engineering course materials, interacting with students during lectures, and by exchanging educational and scientific ideas and approaches with DHS COE at UTEP.

This program has four main components:

Curriculum development in support of DHS-STEM disciplines,
Scholarships, training, and research experiences for undergraduate students,
Research support and enhanced research collaboration for the young investigators,
Internships and Career Placement Support for undergraduate students.

Table 1. Security Engineering Elective Courses

Course #	Course Name	Semester Offered	Instructor
MEEN 4371	Intro. to UAV	Every Spring, starting Spring 2013	Dr. Selahattin Ozcelik
EEEN 4357	Wireless Sensor Networks	Every Fall, starting Fall 2012	Dr. Nuri Yilmazer
MEEN 4372	Resource Optimization for Security	Every Spring, starting Spring 2013	Dr. Kai Jin
CSEN 4367	Data Mining	Every Spring starting Spring 2013	Dr. Mais Nijim
MEEN 4373	Intro. to Information Analysis and Modeling in Security Engineering	Every Fall, starting Fall 2012	Dr. Li

2.1. Curriculum Development for a Minor in Security Engineering - Five new undergraduate courses in Table 1 will be developed in addition to selected nine core curriculum courses offered by the departments of Mechanical, Electrical Engineering, and Computer Science to establish a minor program in Security Engineering. These courses will be introduced in the current undergraduate curriculum of Mechanical Engineering (MEEN), Electrical Engineering (EEEN), and Computer Science (CSEN) programs. The new courses to be developed will address:

Mechanical and electronic components of UAVs from a system point of view, and operation and utilization of such systems for CBP, Coast Guard, and FEMA operations.
Principles of WSN systems and their deployment and operations for terrestrial, and/or underwater monitoring activities.
Fundamental techniques and approaches for digital image processing and data mining techniques for extracting useful patterns from large amounts of data taken from different sources including UAV cameras and WSN sensors.
Optimization models and algorithms to solve the operation research problems in security control in order to get the best allocation of technical and human resources, and optimized Screening, Scanning, and Inspection Processes.
Methods and tools used in information analysis and modeling to homeland security, and skills in simulating homeland security systems using the advanced features in Arena, Visual Basic.net, and other software.

These courses are designed carefully taking into account different backgrounds of students from different majors and will require senior standing as a prerequisite. Any science and engineering senior student is expected to have enough technical and math background to satisfactorily perform in these required minor program courses. This minor program is built on existing relevant core curriculum courses from MEEN, EEEN, and CSEN programs, and they are carefully selected to strongly support the minor program. This multidisciplinary minor program prepares the undergraduate students for professional careers suitable to DHS-related jobs and/or industries, as well as for graduate studies.

Table 2. Curriculum for Minor in Security Engineering

Security Engineering Minor Program Curriculum
Core Curriculum Courses from each Major
Mechanical Engineering	Electrical Engineering	Computer Science
MEEN 4344 Control of Systems MEEN 4351 Machine Design EEEN 3331 Circuits and Electromagnetic Devices	EEEN 4329 Communications Eng. EEEN 4354 Linear Control Systems EEEN 4355 Digital Systems Eng.	CS 4314 Database Systems CS 4320 Computer Networks CS 4340 Computer Security
Elective Courses for the Minor Program (Program students must take at least 3 of the following 5 courses)
MEEN 4373 Intro. to Information Analysis and Modeling in Security Engineering MEEN 4372 Resource Optimization for Security EEEN 4357 Wireless Sensor Networks MEEN 4371 Intro. to UAVs CSEN 4367 Data Mining Security Engineering Seminar Series
Attendance is required by all program students. Non-credit.

The curriculum for minor in Security Engineering is given in Table 2. In order to complete the minor degree in Security Engineering, the prospective students must complete three courses from the core curriculum section with a passing grade of ‘C’ or better. Additionally, they must have at least three courses from Electives in Table 2 with the same passing requirement. Naturally, students from a particular major would be taking core curriculum courses from their major and would not need to take the courses from other majors. For example, a CS student would be taking only three of the CS core-curriculum courses listed.

Description of Courses:

MEEN 4371 - Introduction to Unmanned Aerial Vehicles

DHS and its two subordinate organizations; Coast Guard and FEMA can significantly benefit from the use of UAVs in its operations. In fact, DHS has recently started the use of UAVs for U.S. Customs and Border Protection operations along the Texas-Mexico border. In late 2010, a UAV is based at NAS, Corpus Christi, TX. UAVs are increasingly being used by government agencies, such as DHS, Coast Guard, and U.S. Air Force. UAVs are emerging as a separate field within the aerospace industry. Currently, the need for educating/training technical personnel in this field is mostly satisfied by short workshops through continuing education activities.

UAVs have several advantages over manned aircraft: (a) since a pilot is not required, the endurance limit is determined mainly by the fuel capacity. (b) UAVs can travel long distances without intermediate stops. (c) UAVs can carry a significant sensor payload. They have a relatively less expensive cost of operation. The course will address topics including Review of UAV Systems, Communications, Roles of Satellites, Payload, Image Capturing, Airframe, and Propulsion Components, Survivability, Electronic Warfare, Launch and Recovery, Propulsion, Stability, and Control. This course will be designed in a way suitable for all engineering and science major students. The level of technical knowledge of all science and engineering seniors should be satisfactory for the level required for this course. This course will cover the topics from a system point of view, components of the system, functional relations and interactions between the components, and give students practical working knowledge, rather than a specific theory of the system and its components.

EEEN 4357 - Wireless Sensor Networks -

WSN can be used to monitor the activities at the borders and is becoming a crucial technology for homeland security. The WSN is an emerging technology that has been used in a wide range of applications such as habitat monitoring, early forest fire detection, environmental health monitoring, just a few to name. WSN is composed of several tiny spatially scattered sensors where that are capable of measuring physical attributes such as sound, heat, and motion. Each sensor is equipped with a transmitter/receiver unit to communicate with each other wirelessly, a signal processing unit, and a battery. Sensors are scattered and deployed at the borders to monitor the activities in the region of interest. As the WSN finds its application in many fields and the variety of applications increases, it is important to increase and improve the workforce who will work in this field. It is very important to provide the engineers in this workforce with the best education and teach them the newest approaches and technologies. Understanding the concept of WSN will help the engineers to design new systems and will help them to overcome any technical challenges. This proposed course will prepare the students well in WSN areas so that they can design better systems for homeland security. In this course; the following topics will be covered: Introduction to WSN, Routing, Security, Storage, Network Localization, Wireless Communication, Networking, Energy-aware Systems and Algorithms, Protocols, Sensor Mobility, Optimization, Signal Processing. This is an introductory level course and basic knowledge of mathematics will be sufficient enough to follow the topics even for non- EE students. WSN could be utilized for operations such as border security, wide-area surveillance, and wildfire detection as well.

MEEN 4372 - Resource Optimization for Homeland Security -

This course will introduce students to the basic operation research problems in homeland security control, such as resource optimization, airport security, and patrol schedules. Students will learn how to model the problems and use appropriate algorithms and technologies to solve them. Students will gain a detailed understanding of the homeland security problems, the operation research models and algorithms, and practice to use them in homeland security applications. The following topics will be covered: Linear Programming, Simplex Method, Duality Theory and Sensitivity Analysis, The Transportation and Assignment Problems, Network Optimization Models, Dynamic Programming, Integer Programming, Game Theory, Decision Analysis, Queuing Theory. This course will provide students the basic scientific knowledge on modeling and optimization and prepare them for the research on homeland security simulation and modeling. Any senior-level engineering major student who has completed Calculus courses will be able to complete this course successfully without any other prerequisite.

CSEN 4367 - Data Mining -

Due to innovations in technology and the availability of increasingly cheap storage devices, data in different domains have been accumulating at an impressively high rate in recent years, leading to very large databases. This course presents current research in Knowledge Discovery in Databases dealing with the data integration, mining, and interpretation of patterns in such databases. Data mining has become one of the key features of homeland security. It is used as a means for detecting frauds, assessing risks, and product retailing. In the context of homeland security, data mining can be a potential means to identify terrorist activities such as money transfers, identifying and tracking individual terrorists via discovering valid patterns and relationships in large data sets. This course will give an introduction to data mining. The topics that will be covered include Knowledge Discovery, Rule-Based Learning, Statistical Analysis for Discovery of Patterns, Data Warehousing, Data Capturing and Classification, Association Rule Mining, Statistics, Prediction, Machine Learning, Sequential Patterns.

MEEN 4373 - Introduction to Information Analysis and Modeling in Security Engineering

This course will present the fundamental methods and tools used for information analysis and modeling related to homeland security. It will also introduce engineering and technical challenges of homeland security, including modeling and analysis, technological issues, command, control & situational awareness, and data integration requirements. The course is to familiarize the students with the simulation of discrete, continuous, and dynamic systems. Different scenarios in homeland security will be discussed and simulated using data from various national databases, such as the global terrorism database. The course enables the students to develop the skills and experience in simulating homeland security systems using the advanced features in Arena, Visual Basic.net, and other software. Particular attention will be focused on agent-based discrete event modeling methods. Using the knowledge from this course, the students are expected to be ready to join some ongoing DHS research projects, such as Complex Event Modeling, Simulation, and Analysis (CEMSA) Project.