Institute for Homeland Security

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https://hdl.handle.net/20.500.11875/4231

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Rationale and Process for Continuity of the Economy
(Institute for Homeland Security, 2023-10-15) Ruddell, Benjamin
A regional economy is a vibrant ecosystem comprising critical infrastructures and economic agents like power and telecommunications, ports and logistics, networks of producers and suppliers, human capital, and government agencies. In the increasingly connected and chaotic global economy, resilient regional economies must implement economic development and regulatory policies that ensure "Continuity of the Economy" (COTE) during major social, economic, or environmental shocks. COTE requires that all providers and operators of critical infrastructures and critical functions establish adequate capacity to self recover after a major disruption and prepare adequate input supply chain buffers so that supplier disruptions do not take down critical services before the economic network can recover itself. Non-critical suppliers support interdependent critical infrastructures, blurring the artificial lines between critical and non-critical sectors and highlighting the need for a cross-cutting whole-of-economy approach instead of a sectoral approach to preparedness. This whole-of-economy planning and preparation is made possible by implementing a recurring community-based participatory process that maps supply chains, measures buffers and recovery requirements, and connects critical infrastructure service providers and recovery responders directly with suppliers to share recovery priorities and plans. This participatory process also screens out non-critical suppliers that are not necessary in the short term to recover or sustain critical infrastructures and critical functions during a major disruption, enabling recovery operations to focus on critical infrastructures and critical suppliers and speed recovery. Establishing adequate supply chain buffer time and inside-out recovery capacity are identified as the key foci for COTE preparedness. COTE is an all-hazard approach to resilience and preparedness that complements existing economic development, five-year emergency planning, cyber preparedness, and emergency management processes.
Supply Chain Mapping for Emergency Management Decision-Making
(Institute for Homeland Security, 2023-10-15) Scott, Mark
Supply chain issues are a growing concern for public sector emergency managers because communities rely on these privately-owned and operated systems to deliver goods needed for daily life and survival. Recent events have highlighted the many ways supply chains can be disrupted. Knowing how these systems are configured and how they operate is essential to making more effective operational decisions during emergencies and to support supply chain owners/operators restore flow following a disruption. Mapping the supply chain is a proven private sector practice for gaining visibility into these systems that may have application in the public sector. This paper describes why mapping helps improve emergency preparedness, how mapping has been done, and two case studies of its application for lifeline commodity supply chains in the National Capital Region. The paper concludes with a path forward for emergency managers seeking to use mapping to strengthen supply chain resilience in their communities, regardless of scale.
Countering Workplace Violence in Healthcare: Voices from the Field
(Institute for Homeland Security, 2023-10-15) Denham, Magdalena A; Denham, Mark V
Overall, the U.S. healthcare system has the highest workplace violence (WPV) rates of any occupational setting in the United States. Specifically, among 25,000 incidents of WPV reported annually, 75% percent occur in the healthcare system. Workers in healthcare are four times more likely to be victimized than workers in other private industries.
Convergence of Mission and Moment: Imagining the Emerging Technology Analyst
(Institute for Homeland Security, 2023-10-15) Reese, Nick
The Department of Homeland Security (DHS) was built to prevent terror attacks in the homeland and its culture and structure reflect its birth in 2002. Unlike the world changing event that created DHS, the gradual fading of the terror threat has left it misaligned to respond to new nation-state sponsored threats. The homeland security mission is at a true inflection point as it looks for new ways to use its capabilities and authorities while the central force driving global competition is being established. Just as the field of cyber was being established in the late 1990s and early 2000s in response to new threats, so too must the field of emerging technology be developed today. Examining the realities of the world today, we see the need for professionals who specialize in how emerging technologies create risks and opportunities in a way that is distinct from how cyber professionals do the same for the cyber domain. This work examines the geopolitical reality and how it reflects on the homeland. It goes a step further by conducting a comparative analysis between current cyber analyst requirements and skills and what would be required for an equivalent emerging technology analyst. This analysis informs governments, academia, and industry by creating a baseline from which emerging technology professionals can be created and evaluated with direct application on practitioners in critical infrastructure.
Workplace Harassment and Violence: A Primer on Critical Strategies for Small and Medium-Sized Businesses
(The Sam Houston State University Institute for Homeland Security, 2023-10-15) Shashidhar, Narasimha K
DeepGray: A Novel Approach to Malware Classification Using Grayscale Images with Deep Learning
(Institute for Homeland Security, 2023-10-15) Polsani, Harshitha; 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, DeepGray, for multi-class malware classification utilizing grayscale images and the power of deep learning. Our dataset combines the malware sample from the BODMAS dataset and the benign sample from the DikeDataset. Our approach involves transforming executable files into a format suitable for deep learning by converting them into grayscale images while retaining the essentialdata characteristics. During the data preprocessing step, applied Principal Component Analysis (PCA) was applied to distill the most significant features. To achieve state-of-the-art results in multi-class malware classification, we harnessed the power of deep learning and transfer learning, employing well-established neural network architectures such as a customized Convolutional Neural (CNN), VGG16, EfficientNet, and Vision Transformers (ViT). The models were meticulously trained and rigorously evaluated using a 5-fold cross-validation methodology. Notably, our approach yielded remarkable results, with ViT achieved an impressive accuracy of 0.95. This research underscores the potential of grayscale image analysis and deep learning within the domain of multi-class malware classification. The insights derived from this study contribute significantly to the field of cybersecurity and pave the way for further advancements in the realm of malware detection and classification.
Resilience to High Consequence Cascading Failures of Critical Infrastructure Networks
(Institute for Homeland Security, 2023-10-15) Mouco, Arthur; Ruddell, Benjamin L.; Ginsburg, Susan
Critical infrastructure networks such as telecommunications, power, water, natural gas, diesel, transportation, and cyber networks are interdependent with one another, forming a vast and dauntingly complex web of institutions and physical systems that must be engineered and secured for reliability. No single utility operator, engineering consultant, emergency management organization, financial institution, or local, regional or other government entity is capable of understanding, monitoring, or managing the whole system. Yet, failures are unavoidable, and when those failures cascade through the network the result may be high-consequence cascading “catastrophes” or Black Swan events. In one recent and tragic example, the February 13–17, 2021 Winter Storm Uri in Texas initiated a failure in the natural gas production system that cascaded first to the natural gas power generation system and then to the wider ERCOT power system, the water distribution system, and the petrochemical industry of Texas. No single system operator was responsible, and yet the consequences – including fatalities, recovery challenges, regulatory attention, and extreme costs – are everyone’s problem. As networked interdependencies grow, the likelihood of cascading failures has increased accordingly, necessitating technical solutions tailored to this problem. This report introduces the basic principles of interdependent critical infrastructure networks and reviews approaches for analyzing and mitigating the vulnerability of the network to make it resilient. Resilience and reliability in critical infrastructures are complementary and orthogonal. In resilient networks, the inevitable failures due to “all hazards” stay small and don’t become catastrophes.
Toward a More Effective Policy Model for Responding to Workplace Violence in the Texas Healthcare System
(Institute for Homeland Security, 2023-10-15) Kinney, Alexander B.; Lehmann, Peter S.
Workplace violence is a growing social problem that that has caught the attention of public stakeholders and policymakers. Likewise, industry observers have pushed for more attention to be paid to how violence in the workplace uniquely impacts healthcare professionals. Recently, Texas legislators responded to these calls by passing the Workplace Violence Prevention Act. This new law represents a significant milestone in the effort to develop durable protections for employees in the healthcare Texas system and prevent future incidents of workplace violence. The aim of this technical paper is to provide policymakers and corporate stakeholders with an introduction to this issue and to suggest future improvements to this landmark piece of legislation. In what follows, we will provide a brief overview of the background and significance of workplace violence as a challenging issue that uniquely impacts the healthcare system, outline a working definition of workplace violence that respects the healthcare context, and review existing regulatory and corporate policies that have emerged to combat workplace violence in practice. We will then provide an overview of this new legislation and suggest several ways that this law can be strengthened in light of existing research.
The Rise of Workplace Violence: Addressing Healthcare's Greatest Threat
(2023-10-15) Clay, Eric
Workplace violence (WPV), specifically Patient-Generated Violence (PGV) committed in healthcare facilities represents a significant threat to not only caregivers, but to access to quality healthcare and patient outcomes. PGV is the most common form of violence in the healthcare setting, occurring in emergency departments, inpatient units, behavioral health units, and home health settings. Current research has identified staff, environmental, and patient risk factors as the major precursors of WPV committed by patients. Healthcare workers experience significant physical and psychological consequences as a result of PGV. A review of the evidence, alongside interviews with industry thought leaders, was conducted to identify current evidence-based interventions that can help healthcare organizations eliminate or reduce incidents of PGV.
Safe and Secure Addressing Workplace Violence
(Institute for Homeland Security, 2023-10-15) Muñoz, Griselda
Workplace violence entails any act or threat of violence, verbal abuse, or physical assaults towards individuals at work. This could arise from criminal intent, customer/client interactions, worker-on-worker disputes, or personal relationships. Industries dealing with the public, money handling, lone work, or operating in high-crime areas face elevated risk. It is critical for organizations to have preventive policies for workplace violence that include risk assessments, enhanced security measures, and employee training for recognizing and addressing potential violence. A culture of open communication, respect, and confidential incident reporting should be promoted. Workplace violence response plans must be comprehensive, encompassing support for affected employees, incident investigations, law enforcement engagement, and suitable disciplinary actions. Regular training should focus on prevention, recognition of warning signs, situation deescalation, and incident reporting. Special training should be provided for management and HR to handle sensitive situations and support affected staff. Post-incident support, including counseling, flexible work arrangements, and trauma coping resources, is crucial. Regular policy review and update are necessary for legal compliance and interdepartmental collaboration. Thorough background checks for potential hires are recommended. Early detection of warning signs, such as aggressive behavior, verbal threats, weapon possession, substance abuse, or sudden behavioral changes, can prevent violence and promote a safer workplace. Prevention and response strategies involve fostering a safe environment through conflict resolution, employee assistance programs, and active employee participation. Emphasis should be on zero-tolerance for violence, regular training, and policy communication to all staff. Emergency preparedness requires response plans for violent incidents, regular drills, physical security assessments, and updates. Constant evaluation of implemented strategies, promotion of diversity and inclusivity, collaboration with external agencies, and ongoing communication with employees are key. It's beneficial to recognize and reward employees for maintaining safety, promoting overall wellbeing, adapting measures for remote employees, monitoring social media, and conducting post incident analysis. Benchmarking, implementing visible security measures, promoting open communication, involving employees in strategy development, providing whistleblower protection, and offering customized training are also necessary. 5 The strategy should encompass mental health support, clear behavior expectations, policy reviews, awareness campaigns, and exit interviews. Cross-functional teams should be established, external consultants engaged, incidents tracked, a crisis management plan developed, communication channels established, educational materials provided, safety drills conducted, and partnerships with community organizations formed. Organizational leadership must promote a safety culture and be accountable for implementing initiatives. A proactive approach to workplace violence prevention can enhance organizational performance, reputation, employee satisfaction, and retention rates, while building trust and credibility, reducing legal risks, fostering engagement, and boosting overall resilience.
Cyber-Security Threat: Benchmarking Cybersecurity Response Procedure for Hospitals in Texas
(Institute for Homeland Security, 2023-10-15) Shashidhar, Narasimha K; Varol, Cihan; Gupta, Khushi
Drones and Port Security at the Port of Brownsville
(Institute for Homeland Security, 2023-10-15) Sullivan, John P
This technical paper recounts a geospatial drone security assessment for the Port of Brownsville, Texas (Brownsville Navigation District). The Port of Brownsville is a major intermodal transportation center and is expanding into a major venue for industrial development. The Port of Brownsville is the only deep-water port directly on the US-Mexico Border. The drone assessment will evaluate the threats posed by aerial drones/unmanned or uncrewed aerial systems (UAS) to the port; assess the potential effects of drones on port operations and port security; suggest potential counter measures (counter-UAS); provide an introduction to emerging drone threats, including unmanned/uncrewed vessels and ground vehicles; and drone swarms (or swarming attacks). The impact of various drone threats with port operations is discussed. Mechanisms for enhancing indications and warning, detection, and response to drone threats on the Port of Brownsville, and potential vehicles for sharing these threat data with other ports, port security personnel, law enforcement, and emergency responders will be discussed.
Social Network Analysis Using Machine Learning
(Institute for Homeland Security, 2023-10-15) ABM Rezbaul Islam, PhD; Islam, Ahsan Ul
Electronic Mail (Email) has emerged as a widespread technique for exchanging messages through electronic devices, becoming an indispensable and universal communication medium. Its significance cannot be overstated, as an email address is vital for swift interactions in business, government, trade, entertainment, and various other aspacts of daily life. This mode of communication has progressively replaced traditional written methods for important correspondences, including personal and business trans- actions, where an email is given the same weight as a signed document. In social net- work analysis, a significant challenge lies in identifying essential and influential nodes within a network based on its structure. These nodes can be critical in information dissemination, decision-making processes, and network dynamics. Sentiment Analysis (SA) in text mining has emerged as an automated process to discern subjective information from textual data, such as opinions, attitudes, emotions, and feelings. While many existing approaches treat SA as a text classification problem, requiring labeled data for training machine learning models, obtaining such labeled data can be laborious and time-consuming, often requiring manual annotation efforts. Additionally, the need for transferability across different domains hinders using the same labeled data in diverse applications, necessitating the creation of unique labeled datasets for each part. Overcoming these challenges is crucial for sentiment analysis’s wider adoption and effectiveness in various realworld applications. The objective of the research is to analyze the Enron email dataset by creating a directed graph that represents the email communication network. Two important graph theory metrics are used to find out the number of direct connections (emails sent) for each sender and the influence of each sender as a bridge or critical point of communication in the network. On the other hand, we will use sentiment analysis to analyze the Enron email dataset using different type of pre-trained deep learning models to find the communication type for top ten email sender which we will find using graph theory.
Unseen Threats to Texas Critical Infrastructure: The Risk to Buried Utilities and Targeted Policy Solutions to Protect them
(Institute for Homeland Security, 2023-10-15) Dierker, Benjamin
Excavation damage to underground infrastructure is a nationwide challenge. Ranging from a local nuisance to both lethal and regional crises, the damage and costs from buried facility strikes are almost entirely preventable. Texas is at unique risk because of its concentrated energy infrastructure, its considerable and growing population, and its competitive economy that ensures constant development activity. Each of these factors correlate to excavation damage and help explain why Texas routinely leads the nation in excavation damage incidents that disrupt critical energy and services. Billions of dollars in economic harm, waste, and inefficiency emanate from this issue and ripple throughout the Lone Star State every year. Solutions include systemic implementation of validated technology, adherence to best practices, and public policy reforms proven to reduce this damage to virtually zero – sparing lives, saving dollars, and protecting critical infrastructure.
Forensic Digital Data Sanitization: A Guide for Small and Medium-Sized Businesses
(Institute for Homeland Security, 2023-10-15) Shashidhar, Narasimha K
Deep Learning Approaches for Fingerprint Verification
(Institute for Homeland Security, 2023-10-15) Dalvi, Nikita; Pham, Van Vung
Fingerprint verification is vital because it provides a unique and permanent way to identify individuals. This technology is widely used in various areas like law enforcement, access control, and identity verification processes. Existing approaches for fingerprint verification tasks suffer from low accuracy due to training directly on low-quality and latent fingerprints. Therefore, this work proposes to utilize recent advancements in deep learning and computer vision to (1) enhance fingerprint image quality; (2) extract and verify that the minutiae are retained after enhancement; and (3) perform fingerprint verification tasks. Specifically, this work experiments with (1) Super-Resolution Convolutional Neural Network (SRCNN), Fast SRCNN, and Very Deep Super Resolution (VDSR) for fingerprint image enhancement; (2) Finger-Flow for minutia extraction; and (3) Siamese neural network for fingerprint verification. The experiment results indicate that among the experimented super resolution approaches, VDSR outperforms the others. Additionally, it can retain minutiae in the enhanced version and shows great potential to enhance latent fingerprints, which are less visible. Most importantly, the verification performances improve on the enhanced fingerprints versus low-resolution counterparts.
Mobile Emergency Power During and After Natural Disasters and Shortages
(Institute for Homeland Security, 2023-10-15) Karan, Ebrahim
This study explores the potential utilization of electric school buses as an alternative emergency power source during power outages. With the increasing adoption of electric vehicles and advancements in energy storage technologies, repurposing electric school buses for emergency power generation presents a novel approach to addressing critical energy needs in times of crisis. This research investigates the technical feasibility, economic viability, and operational effectiveness of integrating electric school buses into emergency power systems. Through simulations and scenario analyses, the study examines the capacity of electric school buses to provide backup power over various durations, considering factors such as battery degradation, energy demand, and vehicle availability. Furthermore, the research evaluates the economic implications, including the cost-effectiveness of retrofitting and upgrading existing school bus fleets, and the potential revenue streams from participating in demand response programs and grid services. The findings of this study reveal that electric school buses have the potential to significantly enhance emergency preparedness and response capabilities. Although this alternative is technically feasible, it may not be financially justifiable for several reasons such as higher upfront costs, charging infrastructures, operational complexity, and the complexity of the policies and regulations involved in running the grid.
Ensuring the Cybersecurity of Texas’ Critical Infrastructures
(Institute for Homeland Security, 2023-10-15) Nodeland, Brooke
The daily threat of cyber-attacks on Texas’ critical infrastructure present significant challenges for public and private critical infrastructure providers. COVID-19 related supply chain issues provided insight into the catastrophic effects that could be caused by a cyber-attack on the transportation sector. These disruptions effect our ability to distribute products and medical necessities as well as essential personnel in times of crisis. Protecting the state’s transportation, energy, and chemical cyber networks is imperative in ensuring the sustainability of daily life and business continuity in the event of a cyber-attack. Of additional concern is a growing reliance on cyber-based control, navigation, tracking, positioning, and communications systems creating ample opportunities for exploitation of the transportation cyber systems on which industry have become dependent (Transportation Systems Sector-Specific Plan, 2015). The cyber security of the energy sector ensures the health and welfare of Texans by ensuring steady energy is supplied via electricity, oil and other natural gas resources. The energy infrastructure is primarily owned in the private sector, supplies fuel to the transportation industry, and electricity to businesses and households. Recent ransomware attacks aimed at Western targets, including the energy sector, continue to pose challenges in cybersecurity (Montague, 2023). The recent accidental chemical spill in Ohio also provides insight into the possible outcomes of an intentional cyber-attack against this infrastructure. The regular operations of the chemical sector are imperative to the economic and manufacturing health of state and often involves transporting dangerous chemicals on which other critical infrastructures are dependent (Introduction to the Chemical Sector Risk Management Agency, n.d.). Cyber threats are of particular concern in Texas, where large corporations continue to relocate, and the population continues to climb. It is imperative industry leaders are able to recognize and identify their cyber risks to develop prevention strategies and respond to cyberattacks more quickly and effectively. Disruptions to critical infrastructures could lead to theft of intellectual property; supply chain disruption; electricity disruption; loss of operations capacity; or chemical theft, diversion, or release (Introduction to the Chemical Sector Risk Management Agency, n.d.). Texas’ industrial vulnerability to cyber-attacks through phishing, ransomware, and malware pose significant threats to the security of critical infrastructures. Securing networks against internal and external cyber-attacks requires industry leaders to be proactive and reactive in their approach. The proposed paper seeks to present a translational synthesis of the existing literature regarding best cybersecurity practices for securing critical infrastructure in Texas. In doing so, agencies will be able to better align and prioritize cybersecurity initiatives with industry missions, risk tolerance, and resources (Cybersecurity, C.I., 2018). This review will also include recommendations for improving risk readiness for the transportation, energy, and chemical industry in the state moving forward.
Violence and Harassment in the Workplace: Umbrella Reviews
(Institute for Homeland Security, 2023-10-15) Kim, Bitna
This technical report presents the findings of a grant-funded project, dedicated to exploring the complex issue of workplace violence and mistreatment. Its ultimate aim is to augment the global understanding of this subject and yield actionable insights applicable to a diverse range of organizations, businesses, and corporations across various sectors. Specifically, this project was conducted in two distinct yet interconnected phases. Utilizing an exhaustive, cross-disciplinary literature search, the project's first phase located five existing umbrella reviews on various forms of workplace violence and harassment. The in-depth analysis of these reviews facilitated a comprehensive understanding of the domain by aggregating insights from an array of synthesis research studies. This methodology underscored the most salient and recurrent findings across multiple studies, encompassing areas such as prevalence, risk determinants, mediating and moderating factors, repercussions, and intervention strategies. Detailed discussions of each topic were presented, providing a comprehensive overview of current knowledge and its implications. The project's second phase involved an umbrella review of nine synthesis research studies focusing on interventions for workplace mistreatment. This part aimed 2 to provide empirically supported recommendations for strategies and interventions to prevent and mitigate workplace mistreatment. The findings revealed the prevalence of workplace mistreatment and identified that certain interventions are more effective than others. Due to the multifaceted and complex nature of workplace mistreatment, it was suggested that multi-level, multi-target, and multi-component interventions be implemented. Furthermore, the research underscored the significance of leadership commitment in the successful implementation of interventions and the transformation of organizational culture. In conclusion, this project contributes to a comprehensive understanding of workplace mistreatment and its prevention, providing invaluable insights for practitioners. By informing strategy and intervention design with empirical evidence, this project aimed to equip organizations with the necessary tools to combat this pressing issue effectively.
Towards Trajectory Prediction-based UAV Deployment in Smart Transportation Systems
(Institute for Homeland Security, 2023-10-15) Liang, Fan
A smart transportation system (i.e., intelligent transportation system) refers to a transportation critical infrastructure system that integrates advanced technologies (e.g., networking, distributed computing, big data analytics, etc.) to improve the efficiency, safety, and sustainability of the transportation system. However, the rapid increase in the number of vehicles on roads and significant fluctuations in the flow of traffic can cause the coverage holes of Road Side Units (RSUs) and local traffic overload in smart transportation systems, which can negatively affect the performance of systems and causes accidents. To address these issues, deploying Unmanned Aerial Vehicles (UAVs) as mobile RSUs is a viable approach. Nonetheless, how to deploy UAVs to the optimal position in the smart transportation system remains an unsolved issue. This paper proposes a Vehicle Trajectory-based Dynamic UAV Deployment Algorithm (VTUDA). The VTUDA utilizes vehicle trajectory prediction information to improve the efficiency of UAV deployment. First, we deploy a distributed Seq2Seq-GRU model to the UAVs and train the model. We leverage the well-trained model to predict vehicle trajectory. VTUDA then uses the predicted information to make informed decisions on the optimal location to position the UAVs. Further- more, VTUDA considers both the condition of communication channels and energy consumption during the deployment process to ensure that UAVs are deployed to optimal positions. Our experimental results confirm that the proposed VTUDA can effectively improve the deployment of UAVs. The experimental results also demonstrate that VTUDA can significantly enhance vehicle access and communication quality between vehicles and UAVs.

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