Critical Assets Research Articles

Real-Time Cybersecurity threat detection using machine learning and big data analytics: A comprehensive approach

The rapid digitization of industries and the proliferation of connected devices have exponentially increased the surface area for cyber threats, making traditional cybersecurity methods increasingly inadequate. The paper explores the integration of advanced technologies to enhance threat detection capabilities in a dynamically evolving cyber landscape. This study emphasizes the critical role of machine learning (ML) and big data analytics in identifying, analyzing, and mitigating cyber threats in real time. By leveraging the massive volumes of data generated across networks, ML algorithms can detect anomalous behavior patterns and predict potential threats with high accuracy. Big data analytics further enhances this process by processing and analyzing data at unprecedented speeds, enabling swift identification and response to security breaches. The comprehensive approach outlined in this study addresses key challenges, including the complexity of modern cyber threats, the need for scalability in cybersecurity solutions, and the importance of minimizing false positives. Additionally, the research highlights the importance of continuous learning models that adapt to new and emerging threats, ensuring that the system remains resilient against sophisticated attacks. Case studies of successful implementations across various industries are examined to demonstrate the practical applications and benefits of this approach. The findings suggest that integrating ML and big data analytics in real-time threat detection systems significantly improves cybersecurity defenses, providing organizations with the tools to proactively counteract cyber threats. This approach is positioned as a vital strategy for organizations seeking to fortify their cybersecurity posture in an increasingly interconnected world, where the speed and accuracy of threat detection are paramount to safeguarding critical assets and maintaining trust. Keywords: Real-Time, Cybersecurity, Threat Detection, ML, Big Data Analytics.

Методика организации процесса мониторинга распределенных информационных систем

This article is devoted to the methodology of organizing the process of monitoring of distributed information systems. The article considers the general concept of building the process of information security monitoring. Special attention is paid to such disadvantages of distributed systems as problems of system administration, problems of limited scalability of distributed systems and problems of software portability. It was concluded that at present there is no unified approach to eliminate these disadvantages when building a monitoring process. The model of decentralized distributed system for which the methodology of monitoring process organization is developed is given. Three approaches to the organization of monitoring process of distributed information systems are described, namely the organization of monitoring of network activity of information system, the organization of monitoring of host activity of information system and mixed approach. The mixed approach based on monitoring of network and host activity is used in the methodology. The process of prioritization of sources of information security events is considered, which includes the assessment of IS risks, identification of actual IS threats and identification of critical assets of the organization. As a result, a methodology for organizing the process of monitoring distributed information systems is proposed, which consists of four stages: risk calculation, identification of actual threats, prioritization of information security event sources and connection of selected sources to the information security event monitoring system.

�Turkestan Collection� � chronicle of the life of the Kazakh people of the XIX-XX centuries

Relevance. Among the sources about Kazakhstan, a special place is occupied by the work of the famous bibliographer-local historian of tsarist Russia V.I. Mezhov �Turkestan collection of works and articles� relating to Central Asia in general and to the Turkestan region in particular. Undoubtedly, the �Turkestan Collection� is a very interesting and very important work for Kazakhstan as a whole, especially for the study of national history, as it can be assessed as one of the first and very successful steps taken to systematically summarize the main Russian and foreign written sources about Kazakhstan in the XIX and early XX centuries.Purpose. This study aims to evaluate the significance of the �Turkestan Collection� in the context of Kazakh national history and journalism. It seeks to explore how this collection has been utilized in historical research and the breadth of information it offers about the Kazakh people and their cultural heritage.Methodology. The research primarily involves a detailed review of the contents of the �Turkestan Collection�, examining the types of documents included and their relevance to various academic fields. The study also considers the historical context in which the collection was assembled and its subsequent use in scholarly works.Results. The �Turkestan Collection� has proven to be a critical asset in historical and cultural studies, providing insights not only into the history of journalism in Kazakhstan but also into the broader socio-cultural dynamics of the XIX-XX centuries. The collection�s diverse materials have supported significant scholarly inquiries and contributed to a deeper understanding of the Kazakh people�s heritage.Conclusions. This study underscores the collection�s continued relevance and potential to inform future academic works. The findings advocate for more comprehensive investigations into the collection to unlock further details about the region�s past and its journalistic endeavors.

The Association between Job Stress and Productivity among the Academic Staff

Background. Employees are critical assets of an organization, and it is necessary to investigate and identify factors affecting their performance and productivity. This study aimed to determine the relationship between job stress and job productivity in university settings. Methods. This cross-sectional study included 124 employees of Ahvaz Jundishapur University of Medical Sciences (AJUMS) based on Cochran's formula. Data collection instruments included the standard occupational stress questionnaire of the England Institute (HSE) and Echio’s productivity questionnaire. The validity and reliability of the instruments have been confirmed. Statistical analyses were performed using SPSS 22 software. Results. The mean score of job stress and job performance was 119.75 (±17.49) and 103.3 (±21.3), respectively, and their level was estimated as average. Findings indicated a significant negative correlation between job stress and performance (r = -0.59, P<0.001). In addition, three variables, including employee position, management support, and change were identified as the main predictors of employee productivity based on linear regression. There was a significant relationship between some demographic variables (age, gender, and education level) and occupational stress. Conclusion. According to our results, there was a significant negative correlation between occupational stress and staff productivity. These findings can be generalized to university administrative personnel. Three occupational stress components, including management support, change, and employee position, were identified as main predictors of productivity. Therefore, in order to improve productivity, managers need to consider more independence and support for personnel, as well as reduce the changes’ rate.

Safeguarding legacy equipment

Manufacturers are frequently saddled with outdated technology and ageing equipment, making them uniquely vulnerable in the digital age. By understanding the implications and proactive steps that can be taken, manufacturers can protect their critical assets and ensure the integrity of their production processes.

The future of airport infrastructure resilience

The threat of rising sea levels, flooding, freeze, extreme heat and changes in the intensity and frequency of severe weather poses substantial risks to critical airport assets and infrastructure. As the gateways to cities and countries around the world and engines of economic development, airports are the backbone for the movement of people and goods across the globe. This paper presents an actionable approach to building resiliency across the airport environment to climate change threats and geophysical hazards. The four-step methodology focuses on planning, designs and engineering, prioritisation of financial investments and ongoing industry research and development.

The food metabolome for precision nutrition in dementia prevention

AbstractUnderstanding which aspects of diet and lifestyle may predispose to the development of Alzheimer’s disease and identifying populations vulnerable to prevention by lifestyle modification is a critical asset for precision prevention. However, diet is a complex exposure that is extremely challenging to evaluate using questionnaires in human populations, and inherent measurement error in self‐reported dietary intake data has certainly hampered our way to study properly the impact of nutrition on brain health in epidemiological studies.Measuring markers of nutritional exposure in biological matrices represents a unique way to monitor nutrition and dietary intakes. Candidate biomarkers have been complemented recently by a comprehensive investigation in biological matrices of the chemicals derived from foods after digestion and metabolism, the so‐called food metabolome, that has started to reveal novel dietary biomarkers. High‐throughput metabolomics now enable the measurement of markers of food exposures in biological matrices with unprecedented depth, while capturing the heterogeneity in the response to dietary bioactives from diet across individuals and populations. Thus biomarkers are critical for precision nutrition, as they reflect nutritional status, a product of intakes and of endogenous metabolism, itself linked to many factors, including personal genetic background and microbiome.This “Perspectives” presentation will overview a few recent exploratory studies on signatures of healthy diets and brain health in the food metabolome as examples to discuss challenges and opportunities for further developments. We will also address opportunities of development of multi‐biomarker panels combining self‐reported nutritional intake data with biomarker data from biofluids (blood and urine) to improve assessment of healthy dietary patterns as preventive approaches in dementia.

Encapsulating Holistic Intercultural Competence Development in Higher Education

Intercultural competence (IC) has shown to be a critical asset for university graduates to appropriately and effectively perform in work- related settings that have become increasingly more diverse and intercultural. Therefore, it is fundamental to understand what constitutes effective IC development in higher education (HE). Within IC development, a more holistic understanding of IC assessment is needed. Thus, it is essential to comprehend how IC assessments work effectively, and their role in IC development. By reviewing empirical studies on IC development between 2000 and 2022, the particularities of IC assessments concerning administration, methods, and assessed competencies have been examined. Based on 31 papers, this literature review reveals the inconsistency of IC assessments in HE and proposes a holistic approach to IC assessments to bring more clarity to research and practice.

Integrated cyber resilience strategy for safeguarding the national infrastructure of Somalia: Addressing threats

In today’s digital world, cyber resilience is key element for the security and steadiness of nations. It refers to the capacity to get ready for, adjust to, endure, and swiftly bounce back from cyber threats, playing a crucial role in protecting a nation's critical infrastructure. This research outlines a comprehensive cyber resilience strategy to protect Somalia's critical infrastructure from evolving cyber threats. The study analyzes the current threat landscape, identifies vulnerabilities in key sectors, and proposes a comprehensive approach. The findings of the study present a multifaceted strategy that combines inculcation, international collaboration, and recognized frameworks, forming a structured approach to identify vulnerabilities, protect critical assets, and respond effectively to cyber incidents. The proposed strategy intents to enhance Somalia's cyber resilience, offering a practical strategy for proactive defense against evolving threats and securing a digital future.

Reliability modeling in a predictive maintenance context: A margin-based approach

Current system reliability methods (typically based on fault trees [FTs] or reliability block diagrams) can effectively propagate reliability data from the asset level to the system level in order to identify system-critical points. However, the asset reliability data employed are an approximated integral representation of past industry-wide operational experience, and thus neglect an asset's present health status (obtainable, for example, from online monitoring data and diagnostic assessments) and forecasted health projection (when available from prognostic models). Asset health should be informed solely by that specific asset's current and historical performance data and should not be an approximated integral representation of past industry-wide operational experience (as currently performed by system reliability models through Bayesian updating processes). Sensor data, diagnostic assessments, and prognostic assessments are in fact not considered in plant reliability models used to inform system engineers as to which assets are the most critical. In addition, propagation of quantitative health data from the asset level to the system level is made challenging by the diverse nature and structure of health data elements (e.g., vibration spectra, temperature readings, and expected failure time). Ideally, in a predictive maintenance context, system reliability models would support decision making by propagating available health information from the asset level to the system level to provide a quantitative snapshot of system health and identify the most critical assets. This paper directly addresses these two goals by proposing a different approach to reliability modeling—one that relies on asset diagnostic/prognostic assessments and monitoring data to measure asset health. Propagation of health data from the asset level to the system level is performed through FT models, not in terms of probability but rather in terms of margin, with margin being the “distance” between the asset's present status and an undesired event (e.g., failure or unacceptable performance). Per a cause-effect lens, while classical reliability models target the effect associated with asset performance, a margin-based approach focuses on the cause of the undesired asset performance (i.e., its health). Hence, thinking of reliability in terms of margins implies decision-making processes based on causal reasoning. We show how FT models can be solved using a margin-based reliability mindset, and how this process can effectively assist system engineers in identifying which assets are the most critical to system performance.

Addressing Access and Equity for Latine Youth through Sport-Based Positive Youth Development

Abstract Organized out-of-school time (OST) activities are critical assets that help youth develop life and social skills. Latine youth have some of the lowest rates of participation in OST activities out of all racial and ethnic subgroups due to structural and interpersonal barriers that perpetuate and reproduce patterns of inequality. The purpose of the current study was to describe a youth-led, community-driven, sport-based positive youth development program, the Los Angeles Football Club Youth Leadership Program, and examine associations with participation across three levels: (1) alumni’s enrollment and employment outcomes; (2) youth leaders’ outcomes (e.g., pre- and postprogram surveys); and (3) outputs of the program’s community outreach efforts (e.g., demographics and outputs associated with youth-led community-based activities). Drawing on the study’s findings, authors argue that this program describes an emergent “ladder to leadership” model that can guide community engagement through the delivery of culturally responsive programming and the use of sport to support social–emotional learning during OST. These findings contribute to an important discussion of how to leverage sport to address issues of access and equity during OST for Latine youth.

Puerto Rico’s Rescued Schools: A Grassroots Adaptive Reuse Movement for Abandoned School Buildings

From 2007 to 2019, over 650 public schools closed in Puerto Rico. School closures not only affect students and teachers; these spaces serve as anchor institutions providing social infrastructure for the sustained health of communities. While closed schools remove a critical community asset, these vacant buildings provide adaptive reuse opportunities for alternative social infrastructure and community resources. This article explores how abandoned schools are repurposed in Puerto Rico, focusing on “rescued schools”—that is, grassroots, voluntary initiatives that repurpose schools to support community development. Through a multi-method approach, we categorized and mapped 161 repurposed schools throughout Puerto Rico—38 were rescued schools—and conducted twelve interviews and two focus groups on rescued school initiatives. Our results describe how abandoned schools offer a galvanizing opportunity for motivated community members to meet emerging, localized needs, and the challenges in gaining school ownership and attracting sustained financial and volunteer support, the lack of which impedes their potential impact. We demonstrate how rescued schools embody alternative regional political visions within Puerto Rico and argue that government authorities can minimize the harm from school closures by forging new partnerships between community-based organizations, municipal governments, and other supportive actors to repurpose schools and reproduce their role as community anchor institutions.

Threat Modeling for Communication Security of IoT-Enabled Digital Logistics

The modernization of logistics through the use of Wireless Sensor Network (WSN) Internet of Things (IoT) devices promises great efficiencies. Sensor devices can provide real-time or near real-time condition monitoring and location tracking of assets during the shipping process, helping to detect delays, prevent loss, and stop fraud. However, the integration of low-cost WSN/IoT systems into a pre-existing industry should first consider security within the context of the application environment. In the case of logistics, the sensors are mobile, unreachable during the deployment, and accessible in potentially uncontrolled environments. The risks to the sensors include physical damage, either malicious/intentional or unintentional due to accident or the environment, or physical attack on a sensor, or remote communication attack. The easiest attack against any sensor is against its communication. The use of IoT sensors for logistics involves the deployment conditions of mobility, inaccesibility, and uncontrolled environments. Any threat analysis needs to take these factors into consideration. This paper presents a threat model focused on an IoT-enabled asset tracking/monitoring system for smart logistics. A review of the current literature shows that no current IoT threat model highlights logistics-specific IoT security threats for the shipping of critical assets. A general tracking/monitoring system architecture is presented that describes the roles of the components. A logistics-specific threat model that considers the operational challenges of sensors used in logistics, both malicious and non-malicious threats, is then given. The threat model categorizes each threat and suggests a potential countermeasure.

Integrating business impact analysis and risk assessment for physical asset criticality analysis: A framework for sustainable operations in process industries

The paper tackles the issue of managing physical assets in asset-intensive industries, where continuity plans are crucial for business operations during disruptions. However, resource constraints often hinder companies from implementing these plans for all their assets. Moreover, efforts to maximize resource utilization efficiency and minimize environmental impacts are limited to isolated disciplines, necessitating an integrated approach across natural, social, and technological systems. To address these challenges, this study proposes a framework based on a hybrid fuzzy BWM-TOPSIS methodology for identifying critical physical assets. The framework incorporates Business Impact Analysis (BIA) to determine essential products, a physical asset risk assessment matrix (PARAM) to assess critical assets based on likelihood and impact, and a mathematical model to estimate asset continuity parameters. The framework is applied to a petrochemical company in a case study, offering a guide for estimating the probability and impact of physical asset failure while accounting for inherent uncertainties. By adopting this framework, companies can efficiently manage their physical assets, prioritize continuity plans, and address resource constraints and uncertainties. This research contributes to practical tools and approaches that assist industries in sustaining operations and ensuring business continuity during disruptions.

SymbSODA: Configurable and Verifiable Orchestration Automation for Active Malware Deception

Malware is commonly used by adversaries to compromise and infiltrate cyber systems in order to steal sensitive information or destroy critical assets. Active Cyber Deception (ACD) has emerged as an effective proactive cyber defense against malware to enable misleading adversaries by presenting fake data and engaging them to learn novel attack techniques. However, real-time malware deception is a complex and challenging task because (1) it requires a comprehensive understanding of the malware behaviors at technical and tactical levels in order to create the appropriate deception ploys and resources that can leverage this behavior and mislead malware, and (2) it requires a configurable yet provably valid deception planning to guarantee effective and safe real-time deception orchestration. This article presents symbSODA, a highly configurable and verifiable cyber deception system that analyzes real-world malware using multipath execution to discover API patterns that represent attack techniques/tactics critical for deception, enables users to create their own customized deception ploys based on the malware type and objectives, allows for constructing conflict-free Deception Playbooks , and finally automates the deception orchestration to execute the malware inside a deceptive environment. symbSODA extracts Malicious Sub-graphs (MSGs) consisting of WinAPIs from real-world malware and maps them to tactics and techniques using the ATT&CK framework to facilitate the construction of meaningful user-defined deception playbooks. We conducted a comprehensive evaluation study on symbSODA using 255 recent malware samples. We demonstrated that the accuracy of the end-to-end malware deception is 95% on average, with negligible overhead using various deception goals and strategies. Furthermore, our approach successfully extracted MSGs with a 97% recall, and our MSG-to-MITRE mapping achieved a top-1 accuracy of 88.75%. Our study suggests that symbSODA can serve as a general-purpose Malware Deception Factory to automatically produce customized deception playbooks against arbitrary malware behavior.

Multi-stage optimization for energy management and trading for smart homes considering operational constraints of a distribution network

The increase in the uptake of distributed energy resources (DERs) makes the distribution network more complex. Inadequate management of these DERs may lead to escalated power transmission, potentially resulting in challenges within the distribution network and provoking degradation of critical assets like distribution transformers. The smart home has a home energy management system (HEMS) to schedule the DERs at the home level based on the objectives of the end-user. However, HEMS is not coordinated with the distribution network operators, which can cause different network issues at the distribution level. To mitigate this, effective management of DERs across different levels of the distribution network is essential. This paper introduces a four-stage optimization within a three-level coordination framework that aims to maximize benefits for all stakeholders. A mixed integer linear programming (MILP)-based HEMS is formulated in the first stage to perform home energy management effectively. At the aggregator level, in the second stage, a MILP-enabled peer-to-peer (P2P) trading mechanism is designed. At the same level, a third-stage loss of life optimization is performed pertaining to the optimal power status of the HEMS and P2P trading. In the last stage, a three-phase optimal power flow-based optimization is proposed to maintain the operational constraints of the unbalanced distribution network. Optimizing HEMS and P2P trading while addressing transformer limitations, our proposed method reduces peak power by 38.85%. The transformer life loss using P2P is only 0.00059%, while in HEMS, it is 0.62% per day. Additionally, our method substantially lowers electricity costs for P2P prosumers. Thus, our proposed method outperforms other existing mechanisms from both financial and physical network operation suitability perspectives.

A Framework for Sustainability of Small and Medium-scale Businesses in Nigeria Amidst the Covid-19 Pandemic

The impact of the COVID-19 pandemic on small and medium-scale businesses in Nigeria has exposed the ill-preparedness of business owners and government in guarding against the collapse of these critical assets of the economy and, subsequently, saving livelihoods. Nigeria suffers from a colossal infrastructure inadequacy (for example, power supply and access to the internet are two critical inputs of business), and this problem has for a long time impeded the growth of most companies that cannot afford to run their constant operations on generators and expensive internet. These utilities would have, to a substantial extent, cushioned the effects of lockdowns and enabled e-commerce to thrive, rather than the reliance on the traditional face-to-face approach of doing business. The sustainability principle must be brought to bear on all aspects of life in Nigeria so that the thinking of efficient utilization of available resources will ensure the availability of the same resources in the future; long-term planning by small and medium-scale businesses are anchored on the sustainability concept; business mindsets must change to reflect the reality that it is not business as usual. Managers must begin to see the importance of applying sustainability principles in business, which will positively impact the short and long-term cycle of their business. This paper will peruse the different strategies necessary to keep small and medium-scale businesses afloat in the COVID-19 pandemic period and beyond; it will dissect all the avenues required to navigate the muddy waters occasioned by the advent of the Novel Coronavirus disease to safeguard businesses and jobs in the future in the event of another problematic situation.

416 Urgency to Address Infrastructure in Animal sciences–A Preliminary Report

Abstract The purpose of the ASAS Public Policy Committee (PPC) is to help ASAS shape public policy and public opinion on current issues affecting farms and companion animals. PPC sets goals to make federal agencies aware of the scientific expertise and resources available within ASAS that could be used to develop science-based federal policies affecting poultry and livestock production. Recent reports point to a poor state of agricultural facilities at public colleges of agriculture which puts research priorities related to adaptation to and mitigation of climate change, food safety, zoonotic disease preparedness, animal populations and their care, diet-health, nutrition, biosecurity, new biobased packaging, energy innovations, and advanced market analysis at risk (APLU, 2021). To ascertain input specific to the Animal Sciences (AS), an IRB approved ‘Survey About Infrastructure in Animal Sciences’ (#22-495) was offered by the PPC to department heads and faculty of Animal Science programs across the country. The survey instrument was constructed to allow open-ended responses as well as 5-point Likert scale questions regarding participants views about infrastructure (IF) and thereby learn what members closest to the animal sciences community perceive to be the strengths, weaknesses, and opportunities for improvement in our research infrastructure. Analysis of coded responses in the open-ended questions among varied disciplinary arenas within AS revealed ‘facilities’ as the largest Grand Challenge. About 98% of respondents affirmed sustainable food and animal production is a critical national asset in terms of economic growth and development and 98% indicated an overlooked maintenance of IF in AS undermines national food security. Additionally, 68% indicated the state of core labs, at least for AS programs are only average or below. All respondents (100%) agreed that without comprehensive investment in infrastructure within AS, the USA will continue to fall behind in competing with other countries in areas of research. Study results provided insight into potential consequences of deferred maintenance which should elevate awareness of urgency to address the deficiencies. Since IF needs included future workforce development and working environments, an eroded IF and consequences of deferred maintenance threatens the capacity of AS to pursue Grand Challenges in research and ability to create future workforce readiness of graduates from AS programs.

Enhancing rural Ghanaian women’s economic empowerment: the cassava dough enterprise

ABSTRACT Grounded in a qualitative case study design and relying on key informant interviews and focus group discussion, this study assesses the influence of the cassava dough enterprise on women’s economic empowerment in a rural Ghanaian community. Women in the study community are marginalised in accessing arable land, which is a critical livelihood asset. Cassava dough processing, which is a women-dominated activity, has become an alternative and lucrative business for women. Women's engagement in cassava dough processing is driven by myriad factors that are rooted in their sociocultural settings and gender norms. Women engaged in cassava dough processing and sales have enhanced their economic empowerment through increased access to regular income, improved financial autonomy and saving behaviour, and contributed to community development. The study recommends the need to prioritise policies, programs, and interventions that create an enabling environment for community-based women’s economic empowerment strategies in poor and vulnerable communities.

Seamless Industry 4.0 Integration: A Multilayered Cyber-Security Framework for Resilient SCADA Deployments in CPPS

The increased connectivity and automation capabilities of Industry 4.0 cyber-physical production systems (CPPS) create significant cyber-security vulnerabilities in supervisory control and data acquisition (SCADA) environments if robust protections are not properly implemented. Legacy industrial control systems and new IP-enabled sensors, instruments, controllers, and appliances often lack basic safeguards like encryption, rigorous access controls, and endpoint security. This exposes manufacturers to substantial risks of cyberattacks that could manipulate, disrupt, or disable critical physical assets and processes related to their production lines and facilities. This study presents a multilayered cybersecurity framework to address these challenges and harden SCADA environments by implementing granular access controls, network micro-segmentation, anomaly detection, encrypted communications, and legacy system upgrades. The multilayered defense-in-depth (DID) approach combines policies, processes, and technologies to counter emerging vulnerabilities. The methodology was implemented in an electronics manufacturing facility across access control, zoning, monitoring, and encryption scenarios. Results show security improvements, including 57.4% fewer unauthorized access events, 41.2% faster threat containment, and 79.2% fewer hacking attempts. The quantified metrics highlight the CPPS resilience and threat mitigation capabilities enabled by the securely designed SCADA architecture, which allows manufacturers to confidently pursue Industry 4.0 integration and digital transformation with minimized disruption.