Prevention Of Threats Research Articles

Development of a national antibiotic multimetric index for identifying watersheds vulnerable to antibiotic pollution

Improved surveillance of antibiotics and antibiotic resistance (AR) throughout the environment is an important aspect of the prevention and control of threats posed to human and ecological health. In response to field investigations often limited by resources and time, this study aims to develop a systematic approach to assess watershed vulnerability to antibiotic pollution and AR by integrating modeling and field studies. The national antibiotic pollution vulnerability index was developed to identify watersheds most impacted by antibiotic sources. The index incorporates multiple metrics representing antibiotic pollution driven by both agricultural activities and municipal wastewater (i.e. outpatient antibiotic prescriptions, wastewater treatment plant effluent flow, stream order and dilution factor of effluent-receiving streams, manure application, and animal facilities), alongside climate change indicators (i.e., temperature, precipitation, and runoff). The pollution index was applied at a state level in North Carolina to identify the most-impacted watersheds and inform site selection for targeted field study quantifying azithromycin, ciprofloxacin, sulfamethoxazole, and trimethoprim concentrations. Modeled-informed sites in NC demonstrated the highest reported concentrations of azithromycin, trimethoprim, and sulfamethoxazole compared to previous NC studies, confirming the index effectiveness in identifying watersheds with higher antibiotic concentrations. At the national scale, watersheds relatively more vulnerable to antibiotic pollution are predominantly located in the Midwest, South, and Northeast regions of the U.S., with Iowa and Indiana being the most impacted states. Climate change is expected to exacerbate watershed vulnerability to agriculture-driven AR in the Midwest and Northeast due to an increase in precipitation and mean temperature coupled with intense agricultural activities. In addition, due to climate change-induced reductions in precipitation and runoff, watersheds in the Midwest, Mid-Atlantic, and South Central are dominantly at higher risk of effluent-driven AR occurrences. We have disseminated the developed indices as open-source online tools to aid in prioritizing strategies to mitigate AR occurrence across the U.S.

Mathematical Modeling and Stability Analysis of the Delayed Pine Wilt Disease Model Related to Prevention and Control

Forest pests and diseases have been seriously threatening ecological security. Effective prevention and control of such threats can extend the growth cycle of forest trees and increase the amount of forest carbon sink, which makes a contribution to achieving China’s goal of “emission peak and carbon neutrality”. In this paper, based on the insect-vector populations (this refers to Monochamus alternatus, which is the main vector in Asia) in pine wilt disease, we establish a two-dimensional delay differential equation model to investigate disease control and the impact of time delay on the effectiveness of it. Then, we analyze the existence and stability of the equilibrium of the system and the existence of Hopf bifurcation, derive the normal form of Hopf bifurcation by using a multiple time scales method, and conduct numerical simulations with realistic parameters to verify the correctness of the theoretical analysis. Eventually, according to theoretical analysis and numerical simulations, some specific suggestions are put forward for prevention and control of pine wilt disease.

Insider Threat Prevention in the US Banking System

Insider threats have been a major problem for the US banking sector in recent years, costing billions of dollars in damages. To combat this, the implementation of effective cybersecurity measures is essential. This paper investigates the current state of insider threats to banks in the U.S., the associated costs, and the potential measures that can be taken to mitigate this risk. The development of a framework for the adoption of cybersecurity measures within the banking industry is the primary emphasis in order to stop fraud and lessen financial losses. Through a detailed examination of the literature, in-depth interviews with experts in the banking sector, and case studies of existing cybersecurity measures, this paper provides a comprehensive overview of the problem and potential remedies. Analysis of the research reveals that identity and access management, data encryption, and secure authentication are key components of any cybersecurity strategy. Furthermore, it is recommended that banks increase their technical capabilities and improve their employee awareness and training. The study concludes with a series of suggestions for enhancing banking industry cybersecurity and eventually reducing the danger of insider attacks. This paper explores the topic of insider threats in the US banking industry and presents cybersecurity measures to prevent fraud. Insider threats from people with access to sensitive data and systems present serious hazards to the banking industry, resulting in monetary losses, reputational harm, and compromised data integrity.

Simple, Fast, and Accurate Cybercrime Detection on E-Government with Elastic Stack SIEM

Increased public activity in cyberspace (Internet) during the Covid-19 pandemic has also increased cybercrime cases with various attack targets, including E-Government services. Cybercrime is hidden and occurs unnoticed in E-Government, so handling it is challenging for all government agencies. The characteristics of E-Government are unique and different from other service systems in general, requiring extra anticipation for the prevention and handling of cybercrime attack threats. This research proposes log and event data analysis to detect cybercrime in e-Government using System Information and Event Management (SIEM). The main contribution of this research is a simple, fast, and accurate cybercrime detection process in the e-Government environment by increasing the level of log and event data analysis with the SIEM approach. SIEM technology based on machine learning and big data is implemented with Elastic Stack. The implemented technique can be used as a mitigation program against cybercrime threats that often attack and target e-Government. With simple, accurate, and fast cybercrime detection, it is expected to improve e-Government security and increase public confidence in public services organized by government agencies.

Low Seroprevalence Of Brucella Spp. Among Remote Colombian Communities From The Sierra Nevada De Santa Marta

Brucella species cause a high burden of disease globally, infecting both humans and animals; however, One Health has been under-appreciated in Colombia. This study aimed to determine the seroprevalence of Brucella spp. in two remote indigenous communities from the Sierra Nevada de Santa Marta, Colombia. These communities live in close contact with their livestock, indicating a potential susceptibility to zoonotic pathogens. The livestock routinely kept by these communities include cattle, small ruminants and pigs, the known hosts of human pathogenic Brucella spp.. A low level of exposure to Brucella spp. was documented, with only one positive participant among 539 participants (0.2%; 95% CI 0.0 – 1.0). Nevertheless, due to the high risk that zoonoses pose, we recommend discussions with the community for the potential establishment of One Health surveillance studies for the early detection and prevention of future zoonotic disease threats.

The Role of Artificial Intelligence in Predicting Cyber Threats

As cyber threats grow in frequency and sophistication, they pose significant risks to individuals, organizations, and governments worldwide. Traditional cybersecurity measures, which often rely on reactive responses, struggle to address the complexities and speed of modern cyber-attacks. Artificial Intelligence (AI) has emerged as a transformative technology capable of predicting cyber threats before they fully materialize, enabling a proactive approach to cybersecurity. By leveraging techniques like machine learning (ML), deep learning (DL), and natural language processing (NLP), AI can analyze vast quantities of structured and unstructured data, identifying patterns and anomalies that indicate potential threats. This paper explores the crucial role AI plays in predicting cyber threats, emphasizing its capabilities in intrusion detection, malware analysis, phishing prevention, and fraud detection. Key AI techniques discussed include supervised and unsupervised learning for anomaly detection, neural networks for complex pattern recognition, and NLP for parsing potential phishing or threat indicators in text. These techniques are deployed in various cybersecurity functions, using historical data, network traffic, and malicious behavior patterns to train models that can detect, prevent, and respond to cyber-attacks in real-time. Through tables and graphs, the paper highlights AI’s advantages in cybersecurity, such as faster threat detection, improved accuracy, and cost-efficiency, while addressing challenges like dependency on data quality and ethical considerations. Furthermore, we examine the integration of AI into cybersecurity frameworks and its potential to transform future threat prevention strategies. Ultimately, this paper underscores AI’s critical role as both a predictor and responder to cyber threats, arguing that as technology evolves, AI will become an indispensable asset in the fight against cybercrime.

Proportionality of the Restrictions of Human Rights: Specifics during Martial Law

The article is dedicated to the issue of proportionality of the restrictions of human rights and freedoms during martial law in Ukraine. The concept of the protection of human rights is the core value of any democratic state, it has been developed both in the legal system of Ukraine and at the international law level. The legislation of Ukraine as well as the international standards of the human rights protection contain requirements of the proportionality of the restrictions of the rights of person. The proportionality is recognized as universal principle the restrictive measures of the states hould comply with. The proportionality principle applies also during martial law which has been enacted in the result of full-scale aggression of the Russian Federation. However in the situation of war this principle has certain specifics arising out of necessity to secure the defense of the state against the foreign military aggression. The specificity of the proportionality during martial law emanates from the characteristics of the public interests which are regarded as legitimate aim pursued by the restrictions of the human rights and freedoms applied by the state. Such interests relate to ensuring defense capability, security, territorial integrity, restoration of the state’s sovereignty over the territories of Ukraine, combat armed aggression. The significance of these interests gives rise, in case of the threat to the said interests, to the necessity of employment of special, increased restrictions of the rights and freedoms by the state to prevent such threat. The circumstances of war also give rise to the issue of competition between public interests which constitute the legitimate aim of the state’s sovereign measures since the significance of the public interests which in the time of peace had been regarded as priority may decrease. Not only should the legal measures employed by the state for the protection of the public interests and restricting human rights correspond to the public interests pursued but also such measures should secure prevention of the potential threats to the public interests of the defense of the state which has acquired special significance during martial law. Key words: principle of proportionality, martial law, human rights, the state,restrictions of human rights.

Peculiarities of some law enforcement agencies’s activities: national and foreign experience

It has been determined that the MIA system reform is aimed at improving and optimising its structure, organising activities with a view to combating crime and corruption, timely detection of collaboration and prevention of threats to Ukraine’s external and internal security, and improving the level of protection of citizens' rights and freedoms and prevention of offences. The goal of this process is to complete the transformation of the MIA system into a law enforcement agency that meets modern European requirements. The peculiarities and current trends in the development of law enforcement systems of the European Union, the USA and Japan in terms of measures aimed at ensuring the proper state of public security and public order have been studied. The principles of municipal police units functioning in Germany, the UK, the USA and Japan have been considered.
 An analysis of the National Police and other law enforcement agencies of the Ministry of Internal Affairs of Ukraine has been carried out, and the peculiarities and current trends in the development of law enforcement systems of foreign countries with regard to measures aimed at ensuring the proper state of public security and public order have been studied. The means of interaction between the police and local executive authorities, local self-government, public organisations and the public have been considered.
 Taking into account international experience, the author makes proposals for improving the main areas of activity of law enforcement agencies of the MIA of Ukraine. It has been suggested to consider the possibility of reviving the functioning of municipal (local) police units in Ukraine, which should assist regional police units in solving the tasks of public order protection and combating offences. In this regard, it is appropriate to use the experience of municipal police in Germany, the UK, the USA and Japan, as well as in Ukraine.

International cooperation on information security: experience and prospects for development

The development of information and communication technologies plays a crucial role for the economic and socio-political development of each country individually and of humanity as a whole. The paper cancels the experience of interstate cooperation, provides the main directions of development in the field under study. Effective cooperation between States based on mutual respect in the field of information security and the development of digital technologies on various international and regional platforms within the framework of various unions and associations is aimed at ensuring national and international interests in order to protect information technologies, as well as ensuring the inadmissibility of vulnerability of information systems and deterrence of information threats. This article concludes that it is necessary to develop and approve the conceptual framework for the legal provision of information security for the development of regional interstate cooperation within the framework of the Union State of the Republic of Belarus and the Russian Federation, the EAEU, CSTO, CIS, SCO and BRICS. This is important for solving the tasks of ensuring national and international information security, implementing agreements within the framework of these regional interstate associations and further forming a system of universal public-legal mechanisms for ensuring information security. We believe that interstate cooperation determines the vector of development of interaction between states in the field of international information security, which is aimed at strengthening the potential of the States participating in the interstate association with effective prevention and neutralization of threats to collective security arising in this area.

Myocardial Infarction Detection using Morphological Features of ECG Signal

Cardiovascular Diseases (CVD’s) forms the vital basis of death in the world population. The human mortality rate due to CVD’s can be reduced with early detection and prevention of cardiac threat. Electrocardiogram (ECG) indicates the state of the cardiac heart and thus, acts as a standard to the cardiac health of an individual. ECG is a non-invasive, clinical therapeutic agent, which can be used to detect CVD in early stage and prognosis of threaten cardiac diseases. Since, the ECG is an abruptly changing, non-stationary waveform; the anomalies are non-periodic and may appear at varied fluctuations and intervals on random scale. Manual observation of ECG can be hectic in time and may be misleading to medical experts. So, it is necessary to endorse a computer assist framework for rapid and precise diagnosis of CVD’s. This paper deals with the automated characterization and detection of myocardial infarction (MI), dilated cardiomyopathy (DCM) diseases using morphological features extracted from ECG signal and machine learning approach. Our proposed approach attained maximum classification accuracy 87.5% for MIT-BIH Arrhythmia dataset and 99.33% accuracy for BIDMC Congestive Heart Failure (CHF) dataset with K-nearest neighbor (kNN) clustering and decision tree classifier with entropy criterion. The clinical experts can use our methodology to make precise prognosis of mentioned CVDs. Hence, survival prospect of a patient can be notably enlarged by prompt detection and clinical therapy of CVDs.

Биотехнологические глобальные вызовы и возможности межотраслевой консолидации научных изысканий на уровне криминалистической профилактики

Purpose. Justification of the need to develop the practical field of forensic forecasting and prevention of external high-tech threats on the example of foreign dual-use biotechnologies, verified as potentially and actually having an increased public danger for Russia and its citizens. In this regard, attention should be paid to the insufficiency of scientific research related to the increased need in recent years to prosecute those who cause colossal harm to Russian citizens and the state from abroad using high technologies. Therefore, it is extremely important to determine the directions for the development of forecasting, detection and forensic prevention of biological threats in the form of cross-border crime, to analyze the main approaches in bioengineering, which can have a dual purpose as big challenges. Methodology: dialectics, comparative analysis, generalization of open sources, verification and construction of hypotheses. Conclusions. Modern external biotechnological threats are subject to forensic detection, forecasting and prevention in their relationship with the inhuman provisions of modern eugenics, and not fragmentarily in the context of journalistic informational occasions. It is necessary to systematically use the available scientific and technical tools in order to improve the procedures for collecting, verifying and evaluating evidence of cross-border crimes. Efficiency of proof can only be achieved through the use of the most advanced techniques and methods, building up forensic potential on a consolidated intersectoral basis. Scientific and practical significance. The article is aimed at concentrating the research activities of forensic scientists in the most relevant areas of forecasting and preventing external high-tech threats.

A Systematic Literature Review of Information Security in Chatbots

Chatbots have become increasingly popular in recent years, but they also present security risks and vulnerabilities that need to be addressed. This systematic literature review examines the existing research relating to information security in chatbots, identifying the potential threats, proposed solutions, and future directions for research. The review finds that chatbots face various security threats, including malicious input, user profiling, contextual attacks, and data breaches, and that solutions such as blockchain technology, end-to-end encryption, and organizational controls can be used to mitigate these concerns. The review also highlights the importance of maintaining user trust and addressing privacy concerns for the successful adoption and continued use of chatbots. A taxonomy developed in this review provides a useful framework for categorizing the articles and their findings. The review concludes by identifying future research directions that include developing more sophisticated authentication and authorization mechanisms, exploring the use of privacy-enhancing technologies, and improving the detection and prevention of security threats, among others. This review contributes to the growing body of literature on information security in chatbots and can guide future research and practice in this field.

Organizational and legal mechanism for ensuring EU migration security

Introduction. Modern security threats are becoming more and more widespread in the world, intensifying within the borders of the European Union. Migration is increasingly viewed through the prism of security in a particular country or even in the entire region, such as, for instance, European Union. Problem. Ukraine’s European integration aspirations make it necessary to study the common immigration policy of the European Union through the prism of the organizational and legal mechanism for ensuring security in this area. The aim of the study is to define the common immigration policy of the European Union through the prism of the organizational and legal mechanism for ensuring security in this area, as well as formulating proposals for its improvement. Methods. The methods of legal analysis, historical, and systemic analysis are applied. Results. The creation of the Schengen area with a common external border and no internal borders necessitated the adoption of EU supranational legislation, in particular to guarantee the security of this area. Since the Tampere Program in 1999, all five-year development plans have emphasized the security dimensions of migration. The Frontex agency was created to fulfill the goals of the EU’s common immigration policy and to strengthen the protection of the EU’s external border. The intro­duction of data collection systems contributes to the identification of persons and early warning and prevention of threats. Conclusions. In order to strategically reduce the risks associated with migration, it is important to strengthen the protection of the external border of the EU, intensify the control of the influx of citizens of third countries, and ensure an adequate integration policy. In particular, it is necessary to improve tools for data collection and processing, develop and implement new technologies for detecting illegal migrants, ensuring security at external and internal borders; improve integration policy. Only a compre­hensive approach to improving the organizational and legal mechanism for ensuring migration security will help to cope with modern challenges and threats that may cause migration flows to the EU.

MEANS OF COMBATING MORAL THREATS AND THEIR POSSIBILITIES

The article analyzes the classification based on the nature and manifestations of moral threats aimed at the national security and social stability of Uzbekistan in the Internet environment. Various approaches to threats, their scientific and official interpretations are also presented. At the moment, the nature, effects and mechanisms of prevention of external and internal moral threats to our country have been studied.

Просторово детерміновані ризики соціального відторгнення: побудова дерева ризиків

The development of every Ukrainian’s life space is an extremely important aspect of social policy, which should be aimed at improving the state of human development and the constant expansion of development opportunities, the progress in the relevant spheres of social life. The identification, certain ordering and the classification of risks for human development, in particular regarding the prevention of social rejection, using spatially determined factors should become the primary stage of community development policy formation. Understanding of the disadvantages and advantages that are characteristic of the geographical location of territorial entities, the level of their provision with social services and other social benefits allows a conscious approach to the prevention of threats of social rejection in communities.The purpose of the article is to study the spatially determined risk of social rejection, to determine its hierarchical structure through the construction of a risk tree. This article examines the hierarchy of threats of social rejection due to spatially determined factors based on the author’s concept of the space of human development as the latter’s spatial model and the content of the notion of spatially determined risk to human development, which emerges from it. The scientific novelty of the research lies in the fact that the author has determined the hierarchical structure of spatially determined risks for human development, which allows to create a theoretical and methodological basis for the assessment of risks in question. In particular, it has been determined that the structuring of risks allows to distinguish seven main groups. They are: risks of the geographical environment; risks caused by the state of environment; risks caused by the state of artificial environment; risks of spatial and temporal availability; risks caused by the state of economic environment; risks caused by the state of social environment; risks caused by the conditions of everyday life. In order to achieve the goal, the research used a number of general scientific methods — a systemic approach (for determining the main elements of the risk tree for spatially determined risk to human development as a system), the method of analysis, synthesis, generalization (for forming the elemental composition of individual branches of the risk tree for spatially determined risk of social rejection), as well as the logical-graphic method (for building a risk tree for spatially determined risk of social rejection).

Motion Sensor–Based Fall Prevention for Senior Care: A Hidden Markov Model with Generative Adversarial Network Approach

Whereas modern medicine has enabled humans to live longer and more robust lives, recent years have seen a significant increase in chronic care costs. The prevention of threats to mobility is critical for chronic disease management. Researchers and physicians often analyze data from wearable motion sensor–based information systems (IS) to prevent falls. However, prior studies on fall prevention often achieve suboptimal performance because of their limited capacities in modeling data distributions. In this study, we adopt the computational design science paradigm to develop a novel fall prevention framework, which includes the hidden Markov model with generative adversarial network (HMM-GAN) that extracts temporal and sequential patterns from sensor signals and recognizes snippet states and a logistic regression that utilizes the snippet states and determines whether and when to trigger protective devices to prevent fall injuries. We evaluate the proposed framework against prevailing fall-prevention models and the HMM-GAN component against state-of-the-art sensor analytics models on large-scale data sets. Through an in-depth case study, we demonstrate how the proposed framework can lead to significantly reduced potentially catastrophic falls. Besides practical health information technology contributions, HMM-GAN offers methodological contributions to the IS knowledge base for scholars designing novel IT artifacts for healthcare applications.

Cyber Threat Analysis in Smart Terminal Systems

Cyber threats create significant factors that challenge traditional threat prevention mechanisms in harbor areas and port terminals. It has been recognized that understanding security functionalities in the harbor area is based on a more traditional experience of what it requires. It is not enough that the maritime and harbor ecosystem repeats only physical security service routines regarding random checks of passengers and vehicles and customs functions on cargo and passenger transportation. Smart environments and infrastructures are widely expanded in urban areas and create more challenges if old practices are combined with new technologies and functionalities. Traditional threats have changed to a combination of threat types. While developing cyber or physical threats may evolve into hybrid threats, it may prevent everyday harbor activities so that damage can become long-lasting and harm business continuity management. Therefore, it is essential to analyze cyber threat factors in Smart Terminal Systems. The research provides cyber threat and vulnerability analysis and the main attack vectors in the Smart Terminal systems. This research belongs in Finland to the maritime Sea4Value (S4VF) research program that includes Smart Terminals (SMARTER) project for harbor’s digitalization.

The Impact of Cyber Attack on Emergency Energy System

An emergency energy system is a backup power system used in critical situations with the aim of protecting lives and property from the consequences of energy loss, as is the case in hospitals (heart monitors, Ventilator,…etc), and also in sensitive facilities (military industries and government buildings). The emergency power system can contain batteries of all kinds, in addition to solar and wind energy equipment and other cheap types of energy. The concept of cyber security arose several decades after the invention of the computer. At first, there was no need for cyber security, as it was difficult for electronic attacks to occur, because access to computers was limited to specific numbers of users, as the devices were giant confined to a room with certain specifications and were not Linked to networks at the time, Energy sectors expose themselves to a range of cyber threats that can damage control systems. So management, engineering, and IT must adhere to a comprehensive approach that includes threat prevention, detection, and elimination. In this research we will try to mitigate the effects of the cyber attack on these systems by applying some algorithms in order to detect, identify and prevent such attacks, and we will see through the results we obtained that we have made remarkable progress in this field.

Analysis and detection of insider attacks using behaviour rule based architecture in enterprise multitenancy

The enterprise level data security and privacy are one of the focal key challenges to the pr enterprise and security companies to prevent private data from outside and inside attacks. The insider threats and attacks can pretense a real defense risk to the various internal multi-tenants of various enterprises and companies. The data thievery by insiders of the companies is as a great deal the consequence of enterprises failing to execute the scheme and expertise to member of staff supervise activities and administrate the authenticated data-access to data as it the authentic spiteful activities of member of staff looking for economic benefits in multi-tenancy environment. This research composed with three major objectives: Description of insider attack causes with their impact factors; Implications of behavior rule-based architecture in enterprise multitenancy; Integration of behavior rules with prevention thresholds to control user accessibility for prevention of insider attacks and threats; This paper has described the efficient security scenario to avoid insider attaching complexities. This research is more helping the cyber security experts and network administrators to reduce the insider attacks by building the efficient monitoring intelligent system. The experimental scenarios built with125 authenticated, 29 non-authenticated internal users, and 62 authenticated, 18 non-authenticated external users of single enterprise level and avoided insider attacks and threats.

On the effectiveness of evaluating the prevention of drug threat in the youth environment

On the effectiveness of evaluating the prevention of drug threat in the youth environment