Centers and Institutes

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A Crowded Sky: New Threats and Opportunities for Homeland Security in the Cislunar Economy
(Institute for Homeland Security, 2023-10-15) Reese, Nick
Homeland security has not traditionally been thought of as a mission area supporting space activities. Homeland security organizations, however, have been long time consumers of space data and services. Today, the space domain has opened for commercial activity and geopolitical competition alike. The security of the homeland is closely tied to the security of the space domain across multiple risk factors. The homeland security field faces an opportunity to pivot to be more involved in government and commercial space activities by bringing its unique capabilities and authorities to bear against challenges that did not exist a decade ago. This paper will study the evolution of the space economy and the role it now plays in the security of the homeland.
A gene selection method for GeneChip array data with small sample sizes
(2010-07) Chen, Zhongxue; Liu, Qingzhong; McGee, Monnie; Kong, Megan; Huang, Xudong; Deng, Youping; Scheuermann, Richard H.
In microarray experiments with small sample sizes, it is a challenge to estimate p-values accurately and decide cutoff p-values for gene selection appropriately. Although permutation-based methods have proved to have greater sensitivity and specificity than the regular t-test, their p-values are highly discrete due to the limited number of permutations available in very small sample sizes. Furthermore, estimated permutation-based p-values for true nulls are highly correlated and not uniformly distributed between zero and one, making it difficult to use current false discovery rate (FDR)-controlling methods. Results: We propose a model-based information sharing method (MBIS) that, after an appropriate data transformation, utilizes information shared among genes. We use a normal distribution to model the mean differences of true nulls across two experimental conditions. The parameters of the model are then estimated using all data in hand. Based on this model, p-values, which are uniformly distributed from true nulls, are calculated. Then, since FDR-controlling methods are generally not well suited to microarray data with very small sample sizes, we select genes for a given cutoff p-value and then estimate the false discovery rate. Conclusion: Simulation studies and analysis using real microarray data show that the proposed method, MBIS, is more powerful and reliable than current methods. It has wide application to a variety of situations.
A Logic Approach to Granular computing
(International Journal of Cognitive Informatics and Natural Intelligence, 2008-04) Zhou, Bing; Yiyu, Yao
Granular computing is an emerging field of study that attempts to formalize and explore methods and heuristics of human problem solving with multiple levels of granularity and abstraction. A fundamental issue of granular computing is the representation and utilization of granular structures. The main objective of this article is to examine a logic approach to address this issue. Following the classical interpretation of a concept as a pair of intension and extension, we interpret a granule as a pair of a set of objects and a logic formula describing the granule. The building blocks of granular structures are basic granules representing an elementary concept or a piece of knowledge. They are treated as atomic formulas of a logic language. Different types of granular structures can be constructed by using logic connectives. Within this logic framework, we show that rough set analysis (RSA) and formal concept analysis (FCA) can be interpreted uniformly. The two theories use multilevel granular structures but differ in their choices of definable granules and granular structures.
A new statistical approach to combining p-values using gamma distribution and its application to genome-wide association study
(BMC Bioinformatics, 2014-12-16) Liu, Qingzhong; Chen, Zhongxue; Yang, William; Yang, Jack Y.; Li, Jing; Yang, Mary Qu
Background: Combining information from different studies is an important and useful practice in bioinformatics, including genome-wide association study, rare variant data analysis and other set-based analyses. Many statistical methods have been proposed to combine p-values from independent studies. However, it is known that there is no uniformly most powerful test under all conditions; therefore, finding a powerful test in specific situation is important and desirable. Results: In this paper, we propose a new statistical approach to combining p-values based on gamma distribution, which uses the inverse of the p-value as the shape parameter in the gamma distribution. Conclusions: Simulation study and real data application demonstrate that the proposed method has good performance under some situations.
A Report on Physical Fitness Testing and Training in the San Antonio Police Department
(Law Enforcement Management Institute of Texas (LEMIT), 1989) Balmos, Fred N.
Discusses physical fitness testing and training.
A Systematic Review of Challenges in Applying Immersive Technologies for Critical Infrastructure Emergency Response
(Institute for Homeland Security, 2024-08) Olonilua, Oluponmile; Aliu, John
Given the rapid advancements and growing importance of immersive technologies in the critical infrastructure sector, it is essential to understand the challenges to their effective implementation. Thus, this article aimed to identify and investigate the challenges hindering the application of these technologies for emergency response, irrespective of the specific technology or sector involved. This was achieved through a qualitative approach, utilizing a systematic review via bibliometric analysis using VOSviewer software. Additionally, R Studio and the biblioshiny package were used to create interactive visualizations for the project. Scopus was chosen for this search due to its comprehensive coverage of current scientific literature and its efficiency in handling large datasets. The research yielded a comprehensive list of 114 challenges, which were then reviewed and reduced to 33 challenges after rounds of refinement. These were subsequently grouped into five key categories based on thematic similarities. By categorizing these challenges into key thematic areas, this study contributes to a deeper understanding of the obstacles that need to be addressed to leverage the full potential of immersive technologies in enhancing emergency response and critical infrastructure resilience. The originality of this study lies in its rigorous approach to identifying and categorizing the myriad challenges faced by the critical infrastructure sector, offering both researchers and practitioners a structured approach to guide future efforts in overcoming these issues. This contribution not only highlights the specific areas requiring attention but also paves the way for targeted innovations and policy developments that can facilitate the broader implementation of immersive technologies in emergency management.
A Unique Win-Win: Bostering Texas' Energy Security by Leveraging Existing Infrastructure to Effectively Decarbonize
(Institute for Homeland Security, 2024-08) Dierker, Benjamin
The 2021 Texas Winter Storm Uri was a watershed moment for many Texans regarding energy security. The statewide incident exacerbated an increasing tension between climate-centric sustainability goals and power demands anchored to energy security. While environmental activists saw decarbonization as even more critical, traditional energy advocates saw the need for hydrocarbons and pointed out liabilities created by unpredictable wind and solar. Despite these views, through innovative collaboration, it may be possible to generate a scenario that benefits the Texas economy and delivers on the goals for all advocates.
Android System Partition to Traffic Data?
(International Journal of Knowledge Engineering, 2017-12) Zhou, Bing; Liu, Qingzhong; Byrd, Brittany
The familiarity and prevalence of mobile devices inflates their use as instruments of crime. Law enforcement personnel and mobile forensics investigators, are constantly battling to gain the upper-hand at developing a standardized system able to comprehensively identify and resolve the vulnerabilities present within the mobile device platform. The Android mobile platform can be perceived as an antagonist to this objective, as its open nature provides attackers direct insight into the internalization and security features of the most popular platform presently in the consumer market. This paper identifies and demonstrates the system partition in an Android smartphone as a viable attack vector for covert data trafficking. An implementation strategy (comprised of four experimental phases) is developed to exploit the internal memory of a non-activated rooted Android HTC Desire 510 4g smartphone. A set of mobile forensics tools: AccessData Mobile Phone Examiner Plus (MPE+ v5.5.6), Oxygen Forensic Suite 2015 Standard, and Google Android Debug Bridge adb were used for the extraction and analysis process. The data analysis found the proposed approach to be a persistent and minimally detectable method to exchange data
Arson: fire or police the problem: Responsibilities for Arson Investigations: Fire or Police
(Law Enforcement Management Institute of Texas (LEMIT), 1990) Allen, Samuel L.
Discusses arson and the importance of police officers understand the crime.
Assessing Critical Energy Infrastructure Using Geo-Spatial Technologies
(Institute for Homeland Security, 2023-10-15) Leipnik, Mark
This paper discusses the use of Geographic Information Systems (GIS) in mapping and analysis of incidents related to security and integrity of critical energy infrastructure. It includes a discussion of what GIS and related geospatial technologies involve; sources of energy infrastructure related geo-spatial data. As the leading energy producing state, Texas has a major economic reliance on the energy sector and the energy sector uses GIS and related technologies. The energy sector uses GIS extensively for its ongoing needs, but it also faces a range of threats such as floods, winter storms, cyber-attacks, sabotage, vandalism, and physical attacks that can be mapped and analyzed with GIS. This paper shows the use of GIS to map examples of all these threats and analyzes their spatial distribution throughout the United States, but with a central focus on Texas.
Assessment of gene order computing methods for Alzheimer’s disease
(BMC Medical Genomics, 2013-01-23) Liu, Qingzhong; Hu, Benqiong; Pang, Chaoyang; Wang, Shipend; Chen, Zhongxue; Vanderburg, Charles R; Rogers, Jack T.; Deng, Youping; Huang, Xudong; Jiang, Gang
Background: Computational genomics of Alzheimer disease (AD), the most common form of senile dementia, is a nascent field in AD research. The field includes AD gene clustering by computing gene order which generates higher quality gene clustering patterns than most other clustering methods. However, there are few available gene order computing methods such as Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Further, their performance in gene order computation using AD microarray data is not known. We thus set forth to evaluate the performances of current gene order computing methods with different distance formulas, and to identify additional features associated with gene order computation. Methods: Using different distance formulas- Pearson distance and Euclidean distance, the squared Euclidean distance, and other conditions, gene orders were calculated by ACO and GA (including standard GA and improved GA) methods, respectively. The qualities of the gene orders were compared, and new features from the calculated gene orders were identified. Results: Compared to the GA methods tested in this study, ACO fits the AD microarray data the best when calculating gene order. In addition, the following features were revealed: different distance formulas generated a different quality of gene order, and the commonly used Pearson distance was not the best distance formula when used with both GA and ACO methods for AD microarray data. Conclusion: Compared with Pearson distance and Euclidean distance, the squared Euclidean distance generated the best quality gene order computed by GA and ACO methods.
Attack Modeling and Mitigation Strategies for Risk-Based Analysis of Networked Medical Devices
(Proceedings of the 53rd Hawaii International Conference on System Sciences, 2020-01) Hodges, Bronwyn J.; McDonald, J. Todd; Glisson, William Bradley; Jacobs, Michael; Van Devender, Maureen; Pardue, J. Harold
The escalating integration of network-enabled medical devices raises concerns for both practitioners and academics in terms of introducing new vulnerabilities and attack vectors. This prompts the idea that combining medical device data, security vulnerability enumerations, and attack-modeling data into a single database could enable security analysts to proactively identify potential security weaknesses in medical devices and formulate appropriate mitigation and remediation plans. This study introduces a novel extension to a relational database risk assessment framework by using the open-source tool OVAL to capture device states and compare them to security advisories that warn of threats and vulnerabilities, and where threats and vulnerabilities exist provide mitigation recommendations. The contribution of this research is a proof of concept evaluation that demonstrates the integration of OVAL and CAPEC attack patterns for analysis using a database-driven risk assessment framework.
Attack-Graph Threat Modeling Assessment of Ambulatory Medical Devices
(Proceedings of the 50th Hawaii International Conference on System Sciences, 2017-01) Luckett, Patrick; McDonald, J. Todd; Glisson, William Bradley
The continued integration of technology into all aspects of society stresses the need to identify and understand the risk associated with assimilating new technologies. This necessity is heightened when technology is used for medical purposes like ambulatory devices that monitor a patient’s vital signs. This integration creates environments that are conducive to malicious activities. The potential impact presents new challenges for the medical community. \ \ Hence, this research presents attack graph modeling as a viable solution to identifying vulnerabilities, assessing risk, and forming mitigation strategies to defend ambulatory medical devices from attackers. Common and frequent vulnerabilities and attack strategies related to the various aspects of ambulatory devices, including Bluetooth enabled sensors and Android applications are identified in the literature. Based on this analysis, this research presents an attack graph modeling example on a theoretical device that highlights vulnerabilities and mitigation strategies to consider when designing ambulatory devices with similar components.
Behavior-Based Malware Detection Using Deep Learning with ChatGPT
(Institute for Homeland Security, 2024-08) Akinsowon, Tosin; Jiang, Haodi
In the ever-evolving landscape of cybersecurity, the threat posed by malware continues to loom large, necessitating innovative and robust approaches for its effective detection and classification. In this paper, we introduce a novel method for malware classification that utilizes malware behavior and the power of deep learning. The utilization of Large Language Models (LLMs) or ChatGPT by attackers makes the recognition of malicious behaviors more challenging, significantly increasing alert fatigue and investigation costs. Our dataset combines malware samples from the BODMAS dataset. The proposed deep learning framework aims to capture the fundamental relevance across various malware families using their dynamic behavior features generated by a sandbox. The model leverages ChatGPT to abstract features in the malware dynamic behavior report, enhancing its capacity for malware detection. The insights derived from this work contribute significantly to the field of cybersecurity and pave the way for further advancements in the realm of malware detection.
A Bleeding Digital Heart: Identifying Residual Data Generation from Smartphone Applications Interacting with Medical Devices
(Proceedings of the 52nd Hawaii International Conference on System Sciences, 2019-01) Grispos, George; Glisson, William Bradley; Cooper, Peter
The integration of medical devices in everyday life prompts the idea that these devices will increasingly have evidential value in civil and criminal proceedings. However, the investigation of these devices presents new challenges for the digital forensics community. Previous research has shown that mobile devices provide investigators with a wealth of information. Hence, mobile devices that are used within medical environments potentially provide an avenue for investigating and analyzing digital evidence from such devices. The research contribution of this paper is twofold. First, it provides an empirical analysis of the viability of using information from smartphone applications developed to complement a medical device, as digital evidence. Second, it includes documentation on the artifacts that are potentially useful in a digital forensics investigation of smartphone applications that interact with medical devices.
Blended Learning & Unicorns: What's Choice Got to Do With it?
(2023) Ashley Crane
Blended Learning & Unicorns: What’s Choice Got to Do With it? Little did I know when I walked through the convention center doors at the 2023 Texas Computer Educators Association (TCEA) Convention & Exposition, one of my greatest take-aways would come from a simple poster session shared by a self-proclaimed “culture unicorn.” Prior to this convention, I had dabbled in the world of blended learning. A learner-centered methodology, blended learning leverages the purposeful alignment of traditional face-to-face teaching practices and technology-enabled learning opportunities to create a personalized learning experience. (Keynes, 2017) I read and watched videos, but struggled to understand how to strategically implement this powerful teaching method for the benefit of my students and myself. Then I met Candice Adcock, an Instructional Technology Coach from Mesquite ISD, who asked me to take a step back from the technology aspect of blended learning and focus on the kind of choice blended learning could offer my students. Providing students with choice empowers them to take ownership of their learning and positively impacts classroom culture as it builds community, creates a safe environment, empowers student voice, cultivates risk taking, and fosters collaboration. Blended learning emphasizes five elements of choice: • Place • Path • Time • Pace • Evidence of learning (Product) The key piece of information I was missing – the instructor doesn’t have to provide choice in all these areas. Rather, they should select one element of choice to focus on, especially when building up the practice of blended learning. Determining what choice to offer is complex and is dependent upon multiple factors. Some questions we should ask ourselves include: • Is there space for flexibility in choice within my course’s curriculum and/or timeline? • Do my students typically have electronic devices and internet available in class? At home? • How much control over the learning process am I willing to concede to students? • Do I have existing instructional material (recorded lectures, readings, videos, podcasts, etc.) that could be used to facilitate choice? • How much effort am I willing to put into preparing or restructuring lessons and/or assignments to provide choice? • Can I give myself permission to streamline my assessment and/or grading practices to keep students accountable while providing quick feedback? • Am I willing to fail forward with my students as we figure out the practice of blended learning together? With those questions in mind, the challenge now falls to me. What choice can I reasonably offer students in my courses? How can I use technology to support and/or leverage that choice? Can I, too, be a “unicorn teacher”? Many thanks for the Engaging Classrooms Team for awarding me the Odyssey Grant which enabled me to attend TCEA gaining this insight and more into the power and practice of blended learning. Keynes, J. M. (2017). Redesigning the Learning Experience. In E. C. Sheninger & T. C. Murray (Eds.), Learning Transformed: 8 Keys to Designing Tomorrow’s Schools, Today (pp. 54–82). ASCD; Gale eBooks. https://link.gale.com/apps/doc/CX7330800011/GVRL?sid=bookmark-GVRL&xid=2bacd5d8
Breaking Barriers: Refreshing the Reputation of Community Supervision by Introducing Defendants to an Educational Tool
(Texas Probation Institute for Leadership Excellence, 2021) Whitehead, Corina
John Augustus, acknowledged as the first American probation officer, believed he could save offenders from crime by his method of sympathetic supervision rather than cruel punishment (Chute & Bell, 1956). Barriers in community supervision, such as offenders lacking knowledge regarding the procedure of community supervision and negative offender and supervision officer relationships are regularly causes of recidivism. Research suggests a pivotal factor in influencing defendant behavior is the nature of the Community Supervision Officer (CSO) and defendant relationship (Leibrich, 1994). This paper focuses on the significance for Community Supervision and Corrections Departments to have an educational tool that informs offenders of the mission of community supervision and their expectations throughout their supervision term. CSOs receive education established on improving the supervision experience, objectively lessening recidivism but on the other end of the aspect, offenders do not. An introduction to offenders upon placement of supervision could result in the creation of a positive visualization of community supervision, motivation to seek positive offender and supervision officer relationships, and more successful supervision term completions.
Calm Before the Storm: The Challenges of Cloud Computing in Digital Forensics
(International Journal of Digital Crime and Forensics, 2012-04) Grispos, George; Storer, Tim; Glisson, William Bradley
Cloud computing is a rapidly evolving information technology (IT) phenomenon. Rather than procure, deploy, and manage a physical IT infrastructure to host their software applications, organizations are increasingly deploying their infrastructure into remote, virtualized environments, often hosted and managed by third parties. This development has significant implications for digital forensic investigators, equipment vendors, law enforcement, as well as corporate compliance and audit departments, amongst other organizations. Much of digital forensic practice assumes careful control and management of IT assets (particularly data storage) during the conduct of an investigation. This paper summarises the key aspects of cloud computing and analyses how established digital forensic procedures will be invalidated in this new environment, as well as discussing and identifying several new research challenges addressing this changing context.
CDBFIP: Common Database Forensic Investigation Processes for Internet of Things
(IEEE Access, 2017-10) Al-Dhaqm, Arafat; Razak, Shukor; Othman, Siti Hajar; Choo, Kim-Kwang Raymond; Glisson, William Bradley; Ali, Abulalem; Abrar, Mohammad
Database forensics is a domain that uses database content and metadata to reveal malicious activities on database systems in an Internet of Things environment. Although the concept of database forensics has been around for a while, the investigation of cybercrime activities and cyber breaches in an Internet of Things environment would benefit from the development of a common investigative standard that unifies the knowledge in the domain. Therefore, this paper proposes common database forensic investigation processes using a design science research approach. The proposed process comprises four phases, namely: 1) identification; 2) artefact collection; 3) artefact analysis; and 4) the documentation and presentation process. It allows the reconciliation of the concepts and terminologies of all common database forensic investigation processes; hence, it facilitates the sharing of knowledge on database forensic investigation among domain newcomers, users, and practitioners.
Cloud Forecasting: Legal Visibility Issues in Saturated Environments
(Computer Law & Security Review, 2018) Brown, Adam J.; Glisson, William Bradley; Andel, Todd R.; Choo, Kim-Kwang Raymond
The advent of cloud computing has brought the computing power of corporate data pro- cessing and storage centers to lightweight devices. Software-as-a-service cloud subscribers enjoy the convenience of personal devices along with the power and capability of a service. Using logical as opposed to physical partitions across cloud servers, providers supply flexible and scalable resources. Furthermore, the possibility for multitenant accounts promises considerable freedom when establishing access controls for cloud content. For forensic analysts conducting data acquisition, cloud resources present unique challenges. Inherent proper- ties such as dynamic content, multiple sources, and nonlocal content make it difficult for a standard to be developed for evidence gathering in satisfaction of United States federal evidentiary standards in criminal litigation. Development of such standards, while essential for reliable production of evidence at trial, may not be entirely possible given the guarantees to privacy granted by the Fourth Amendment and the Electronic Communications Privacy Act. Privacy of information on a cloud is complicated because the data is stored on resources owned by a third-party provider, accessible by users of an account group, and monitored according to a service level agreement. This research constructs a balancing test for competing considerations of a forensic investigator acquiring information from a cloud.

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