Risk Of Attack Research Articles

Environmental Contamination by Agrochemicals and Its Indiscriminate Use by Dry Season Farmers in Sudan Savannah of Katsina State

A field survey was conducted in five dry season irrigation sites consisting of Ajiwa, Zobe, Jibia, Sabke, and Sulma dams in Katsina state. The survey was carried out to find out dry-season farmers’ attitudes on the use and misuse of agrochemicals. A multi-choice structured questionnaire was administered to one hundred (100) purposively selected dry-season farmers. Data collected were analysed and interpreted using descriptive statistics in the form of bar charts of the SAS package. The result showed that many dry-season farmers obtained information on the safe use of agrochemicals from pesticide retailers (90%). The market recorded the highest (98%) of farmers purchasing agrochemicals. Most dry-season farmers throw away empty pesticide containers after use (91%) while 7% and 4% respectively burn and deep bury these containers. In others, some farmers rewash these containers for household use or resell them to hawkers. Symptoms of pesticide toxicity after application were identified with the highest percentage being recorded by skin rashes (90%). Based on the findings of this study, a poor attitude toward throwing away empty containers could serve as a chance of increased chemical residues in the environment and a high risk of attack especially by the vulnerable people in the study area. It is therefore recommended that dry season farmers be encouraged to purchase agrochemicals from reputable agents to avoid purchasing adulterated or expired chemicals and dispose of empty containers appropriately and hygienically by environmental standards.

Zoning the occurrence of Thyrinteina arnobia in eucalypts and its relationship with the spectral behaviour of canopies and soil attributes

This study aimed to outline areas at risk of the occurrence of eucalypt defoliator caterpillars and their relationship with variations in the spectral behaviour of canopies and soil attributes. The study was conducted in three eucalypt plantation areas of the Bracell Bahia company, located in the state of Bahia, Brazil. Initially, the spatiotemporal distribution of climatic variables and water balance was evaluated. Subsequently, using geographic information systems and fuzzy logic, occurrence risk zoning was developed for defoliator caterpillars associated with different classes of eucalypt crop aptitude. After defining the areas at risk of pest occurrence, specific plots in different aptitude classes were selected to assess, intra-plot, characteristics that can increase or reduce the risk of defoliator caterpillar attack and damage intensity, as well as the plant’s ability to recover after a controlled outbreak. Information on the spectral behaviour of the canopies and the availability of nutrients in the soil was used in this step. Zone modelling enabled the delineation of areas and periods at a higher risk of pest occurrence for the different aptitude conditions of the eucalypt crop. The intra-plot methodology proved that the class of eucalypt crop aptitude with the greatest potential for recovering vegetative vigour 60 days after caterpillar damage was the apt class. This result can be attributed to K limitation and the high spatial resolution of the PlanetScope orbital sensor.

ATT&CK-based Advanced Persistent Threat attacks risk propagation assessment model for zero trust networks

In recent years, the growing frequency and intensity of Advanced Persistent Threats (APTs) have significantly undermined the legitimacy and financial stability of government agencies, enterprises, and other entities. Moreover, these attacks have shown the inherent vulnerabilities in conventional border defense strategies. The emergence of the zero trust network architecture can be attributed to the increasing complexity of the cyber threat landscape. With the application of risk assessment, this paper effectively tackles the challenges posed by conventional network defense limitations and enhances the efficiency of the access control decision-making process. Nevertheless, the existing risk assessment approaches primarily focus on conventional security assessment objectives, which exhibits a deficiency in the ability to dynamically assess APT attacks. The Adversarial Tactics, Techniques, and Common Knowledge (ATT&CK) Framework introduced in this paper is a novel approach to mitigating APT attacks. This paper aims to mine and analyze the frequent item set and correlation of cyber threat penetration attack techniques. The paper also intends to construct an attack technique relationship diagram and develop a tactical prediction model for cyber threat penetration attacks using the Markov chain model. Finally, our study aims to establish a risk propagation model for APT threats based on the aforementioned model. The approach presented in this paper significantly enhances the capacity of zero trust networks in addressing sophisticated cyber threats.

Cyber Resilience Approaches for Cyber Physical Systems

Cyber-physical systems (CPS) integrate physical processes with computing, communication, and control systems to increase efficiency, reliability, and safety. However, these systems are also vulnerable to cyber attacks, which could have severe consequences, such as loss of life, property damage, and economic disruption. To ensure the safety and security of modern society, it is crucial to ensure that CPS are cyber- resilient, meaning they can continue to function and recover from cyber attacks. This requires a multi-faceted approach that includes secure design, risk assessment, monitoring and response, redundancy and backup, and training and education. By implementing these strategies, organizations can improve the cyber resilience of their CPS, reducing the risk of cyber attacks and promoting the safety and security of modern society.

Autonomous Threat Response at the Edge Processing Level in the Industrial Internet of Things

Industrial Internet of Things (IIoT) technology, as a subset of the Internet of Things (IoT) in the concept of Industry 4.0 and, in the future, 5.0, will face the challenge of streamlining the way huge amounts of data are processed by the modules that collect the data and those that analyse the data. Given the key features of these analytics, such as reducing the cost of building massive data centres and finding the most efficient way to process data flowing from hundreds of nodes simultaneously, intermediary devices are increasingly being used in this process. Fog and edge devices are hardware devices designed to pre-analyse terabytes of data in a stream and decide in realtime which data to send for final analysis, without having to send the data to a central processing unit in huge local data centres or to an expensive cloud. As the number of nodes sending data for analysis via collection and processing devices increases, so does the risk of data streams being intercepted. There is also an increased risk of attacks on this sensitive infrastructure. Maintaining the integrity of this infrastructure is important, and the ability to analyse all data is a resource that must be protected. The aim of this paper is to address the problem of autonomous threat detection and response at the interface of sensors, edge devices, cloud devices with historical data, and finally during the data collection process in data centres. Ultimately, we would like to present a machine learning algorithm with reinforcements adapted to detect threats and immediately isolate infected nests.

Coming Back Down to Earth: A Grounded Look at Space Cybersecurity in Southeast Asia

This paper aims to open discussion regarding the absence of cybersecurity efforts for space systems in Southeast Asia and its implications. Although there is a consensus on the need for action, Southeast Asian states have not taken any concrete steps to address the challenge of space cybersecurity. Lacking sovereign capabilities, regulatory structures, and initiatives to tackle complex accidents that are waiting to happen, Southeast Asia is not adequately equipped to deal with the growing risk of attack on its space ecosystem. With increasing militarization of space programs, exponentially growing dominance of private sector, and reduced barriers of entry for malicious non-state actors, delaying any action for strengthening space cybersecurity can produce detrimental impact given the necessity of space sector for civil, commercial, and national sustenance in the region. Southeast Asia is in a unique position where the nascency of space sector and lack of rigid structures allows flexibility to learn, translate, and adapt existing initiatives and frameworks. To be on a path to bridge the gap between reality and the ideal, the region should focus on articulating principles and guidelines. The author proposes realistic policy recommendations and directions Southeast Asian states and the region at-large should pursue for promoting medium and long-term sustainability and usability, and for maintaining cybersecurity of space assets.

Abstract P381: Geographic Variation in Financial Strain and Food Insecurity After the COVID-19 Pandemic: Implications for Cardiovascular Health Equity

Reduced food security is associated with higher healthcare expenditures and increased risk of coronary heart disease, angina, heart attacks, and hypertension. State-level responses to the COVID-19 pandemic and support policies may contribute to regional differences in financial strain and food insecurity, which could have implications for cardiovascular outcomes. Hypothesis: We assessed the hypothesis that there is geographic variation in financial strain and food insecurity in the United States three years after the start of the pandemic. Methods: This study utilizes weighted data from the U. S. Census Bureau’s Household Pulse Survey Phase 3.10 conducted from August 23 - September 4, 2023. We organized data responses according to the Department of Health and Human Services regions - Boston, New York, Philadelphia, Atlanta, Chicago, Dallas, Kansas City, Denver, San Francisco, and Seattle. Food insecurity was measured using a single survey item about having sufficient food to eat in the last 7 days. Financial strain was defined as difficulty paying expenses in the last seven days. Results: There were 254,966,752 adults in the total sample population, (59%) reported difficulty with expenses due to the COVID-19 pandemic. The Atlanta region reported the most financial strain (13%), while the Denver region reported the least (2%), p-value=0.000. The rate of food insecurity was highest in the Atlanta region at 8% compared with 5% or less in other regions, p-value=0.000. Among the 8 states in the Atlanta region, Black individuals were disproportionately more likely to be food insecure, with the greatest difference for Kentucky, Florida, Tennessee, and South Carolina. All states in the Atlanta region had similar odds of food insecurity, but Mississippi residents were nearly twice as likely to experience food insecurity than residents of other states (OR 1.87, p =0.016). Conclusions: The Atlanta region (i.e., the “Deep South”) consists of the most populous states for non-Hispanic Black people and is experiencing the worst food insecurity and financial strain post-pandemic. The economic toll of the pandemic and post-pandemic inflation may contribute to worsening food insecurity and cardiovascular outcomes in a region that is already burdened by poor cardiovascular health. Multilevel intervention is needed to support full pandemic recovery and avoid exacerbating inequities in cardiovascular disease.

Model extraction via active learning by fusing prior and posterior knowledge from unlabeled data

As machine learning models become increasingly integrated into practical applications and are made accessible via public APIs, the risk of model extraction attacks has gained prominence. This study presents an innovative and efficient approach to model extraction attacks, aimed at reducing query costs and enhancing attack effectiveness. The method begins by leveraging a pre-trained model to identify high-confidence samples from unlabeled datasets. It then employs unsupervised contrastive learning to thoroughly dissect the structural nuances of these samples, constructing a dataset of high quality that precisely mirrors a variety of features. A mixed information confidence strategy is employed to refine the query set, effectively probing the decision boundaries of the target model. By integrating consistency regularization and pseudo-labeling techniques, reliance on authentic labels is minimized, thus improving the feature extraction capabilities and predictive precision of the surrogate models. Evaluation on four major datasets reveals that the models crafted through this method bear a close functional resemblance to the original models, with a real-world API test success rate of 62.35%, which vouches for the method’s validity.

TbDd: A new trust-based, DRL-driven framework for blockchain sharding in IoT

Integrating sharded blockchain with IoT presents a solution for trust issues and optimized data flow. Sharding boosts blockchain scalability by dividing its nodes into parallel shards, yet it is vulnerable to the 1% attacks where dishonest nodes target a shard to corrupt the entire blockchain. Balancing security with scalability is pivotal for such systems. Deep Reinforcement Learning (DRL) adeptly handles dynamic, complex systems and multi-dimensional optimization. This paper introduces a Trust-based and DRL-driven (TbDd) framework, crafted to counter collusion attack risks and dynamically adjust node allocation, enhancing throughput while maintaining network security. With a comprehensive trust evaluation mechanism, TbDd discerns node types and performs targeted resharding against potential threats. The TbDd framework maximizes the tolerance for dishonest nodes, optimizes node movement frequency, ensures even node distribution in shards, and balances sharding risks. Extensive evaluations validate TbDd’s superiority over conventional random-, community-, and trust-based sharding methods in shard risk equilibrium and reducing cross-shard transactions.

Intelligent management process analysis and security performance evaluation of sports equipment based on information security

This paper discusses the application and analysis of information security in the intelligent management of sports equipment. With the rapid development of information security, the intelligent management of sports equipment has become more and more convenient, fast and safe. Through the information security situation assessment algorithm and Petri net model of natural language processing, the intelligent management of sports body is realized, personalized service and recommendation are provided, user participation and interaction are enhanced, marketing strategies are optimized, and user experience and user loyalty are enhanced. In the design of sports equipment management, SVM model, attack and defense tree model and SVM-Bayesian model are used in the classification of sports equipment. In the experimental comparison of the three models, it is found that the number of attack and defense SVM-Bayesian alarms is 11, the false alarm rate is 0.55%, the number of missed alarms is 57, the false alarm rate is 2.85%, and the accuracy rate is 96.6%. SVM-Bayesia has obvious advantages in attack success rate and risk defense probability. By constantly comparing the path data and the number of nodes, the algorithm in this paper also has a good application effect.

Associations of asthma control with hypertension, cardiovascular disease, and mortality in obese individuals.

The objective of this study was to assess the associations of asthma control with hypertension, cardiovascular disease, and mortality in obese individuals. We used data from the National Health and Nutrition Examination Survey (NHANES), 2001-2018. Weighted logistic regression analyses and Cox proportional hazard models were performed to evaluate the influence of asthma control onhypertension, cardiovascular disease, and mortality.A total of 2744 obese participants were included. Of them, 937 participants had poorly controlled asthma, 873 had well-controlled asthma, and 934 did not have asthma. We found that poorly controlled asthma was associated with an increased risk of angina pectoris, congestive heart failure (CHF), stroke, and all-cause mortality in obese participants, while well-controlled asthma was associated with an increased risk of CHF and all-cause mortality. Compared with patients with poorly controlled asthma, patients with well-controlled asthma were at low risk of angina pectoris (OR [odds ratio], 0.49; 95% CI [confidence interval], 0.29-0.81), heart attack (OR, 0.54; 95% CI 0.34-0.87), CHF (OR, 0.62; 95% CI 0.39-0.99), and stroke (OR, 0.45; 95% CI 0.27-0.73).The present study suggested that obese individuals with poorly controlled asthma were associated with increased risks of angina pectoris, CHF, stroke, and all-cause mortality. Well-controlled asthma had fewer negative health effects than poorly controlled asthmain obese individuals.

Posttraumatic Stress Disorder Is Associated With Elevated Risk of Incident Stroke and Transient Ischemic Attack in Women Veterans.

Posttraumatic stress disorder (PTSD) has been associated with ischemic heart disease in women veterans, but evidence for associations with other cardiovascular disorders remains limited in this population. This retrospective longitudinal cohort study evaluated the association of PTSD with incident stroke/transient ischemic attack (TIA) in women veterans. Veterans Health Administration electronic health records were used to identify women veterans aged ≥18 years engaged with Veterans Health Administration health care from January 1, 2000 to December 31, 2019. We identified women veterans with and without PTSD without a history of stroke or TIA at start of follow-up. Propensity score matching was used to match groups on age, race or ethnicity, traditional cardiovascular risk factors, female-specific risk factors, a range of mental and physical health conditions, and number of prior health care visits. PTSD, stroke, TIA, and risk factors used in propensity score matching were based on diagnostic codes. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs for associations of PTSD with an incident stroke/TIA composite. Subanalyses considered stroke and TIA separately, plus age- and race- or ethnicity-stratified analyses were carried out. The analytic sample included 208 092 women veterans (104 046 with and 104 046 without PTSD). PTSD was associated with a greater rate of developing stroke/TIA (HR, 1.33 [95% CI, 1.25-1.42], P<0.001). This elevated risk was especially pronounced in women <50 years old and in Hispanic/Latina women. Findings indicate a strong association of PTSD with incident stroke/TIA in women veterans. Research is needed to determine whether addressing PTSD and its downstream consequences can offset this risk.

Patient With Sitosterolemia With Slow Healing Sternal Wound From Coronary Artery Bypass Surgery.

Sitosterolemia, also known as phytosterolemia, is a rare recessive genetic disorder characterized by accumulation of sitosterol from vegetable oils, nuts, and other plant-based foods in the body. In those with sitosterolemia, there is an increase of fatty deposits in the arteries (atherosclerosis), which may occur in early childhood, impeding blood flow and increasing the risk of a heart attack, stroke, or sudden death at a very early age. Visual signs of sitosterolemia may include small yellowish xanthomas beginning in early childhood. Xanthomas are accumulated lipids that develop in the heels, elbows, and buttocks. A clinical case study of a patient with sitosterolemia with slow healing surgical wound from coronary artery bypass surgery is described. Treatment of sitosterolemia is aimed at lowering plasma plant sterol levels with dietary restriction intake of both animal- and plant-based sterols. However, plant-based products (collagen, chitosan, etc) are also used for wound dressings, so alternative wound dressings were selected to decrease the possibility of systemic absorption. This case study describes a young adult male with sitosterolemia who presented with a slow healing surgical incision following coronary artery bypass surgery. Sitosterolemia is often characterized by atherosclerosis of the coronary arteries that occurs in children and early adulthood, especially affecting men. Treatment is aimed at lowering plasma sterol levels with the restriction of animal and plant sterols. There is considerable interest today in natural versus synthetic wound care products. Dressings containing chitosan, cellulose, collagen, etc, to be avoided to decrease the chance of systemic absorption.

Risk of Secondary Attacks among Ischaemic Heart Disease Patients in Ismailia

Risk of Secondary Attacks among Ischaemic Heart Disease Patients in Ismailia

Population reduction in salt intake for the prevention of cardiovascular disease: the “Four Imperatives”

Salt consumption is now much greater than needed for survival. High salt intake increases blood pressure in both animals and humans. Conversely, a reduction in salt intake causes a dose-dependent reduction in blood pressure in men and women of all ages and ethnic groups, and in patients already on medication. The risk of strokes and heart attacks rises with increasing blood pressure, and a reduction of blood pressure with drugs reduces the risk. However, most events occur in individuals with ‘normal’ blood pressure levels. Non-pharmacological prevention is therefore the only option to reduce such events in the population at large. Reduction in population salt intake reduces the number of vascular events. It is one of the most important public health measures to reduce the global cardiovascular burden. Salt reduction policies are feasible and effective (preventive imperative), cost-saving (economic imperative), powerful, rapid, equitable (political imperative) and life-saving (moral imperative). The World Health Organization recommends reducing salt consumption by 30% globally by 2025, aiming to reduce salt consumption to less than 5g per day, eventually.

Assessing the Risk of Terrorist Attacks Against Technical Infrastructures Intended for the Storage of Explosives For Civil Uses

Abstract The paper presents the results of the theoretical and practical research on the development of the infrastructure for assessing the risk of terrorist attacks associated with undesirable events such as major accidents that can occur at explosives storehouses. The scientific research was carried out within the framework of Project PN 16 43 02 15 - CORE Program titled “Researches regarding the increase of security degree in the technical infrastructures for storing explosives for civil uses”. The use of the DIRE version 1.0 software package specialized in the field of risk assessment of terrorist attacks on explosives storehouses has provided the necessary premises for an objective and highly accurate assessment of this type of risk in the technical infrastructure and the quantification of the degree of damage to the human component and on-site or neighbouring targets, as well as to the area in their proximity.

Security Threats and Promising Solutions Arising from the Intersection of AI and IoT: A Study of IoMT and IoET Applications

The hype of the Internet of Things as an enabler for intelligent applications and related promise for ushering accessibility, efficiency, and quality of service is met with hindering security and data privacy concerns. It follows that such IoT systems, which are empowered by artificial intelligence, need to be investigated with cognisance of security threats and mitigation schemes that are tailored to their specific constraints and requirements. In this work, we present a comprehensive review of security threats in IoT and emerging countermeasures with a particular focus on malware and man-in-the-middle attacks. Next, we elaborate on two use cases: the Internet of Energy Things and the Internet of Medical Things. Innovative artificial intelligence methods for automating energy theft detection and stress levels are first detailed, followed by an examination of contextual security threats and privacy breach concerns. An artificial immune system is employed to mitigate the risk of malware attacks, differential privacy is proposed for data protection, and federated learning is harnessed to reduce data exposure.

Yoga meditation: A path to holistic health and healing

The word meditation is derived from a Latin word ‘madri’ which means “to heal”. Meditation can certainly be considered as a great healing process - spiritual, mental, and emotional - with proven benefits to physical well-being. In the current communication, an attempt has been made to explain some of these benefits and provide science based evidence to explain them. Meditation develops our ability to maintain inner peace at all times in our actions and thereby achieve the best physical and mental health. With psychosomatic ailments, meditation provides the vital element that modern therapies lack. During Yogic breathing, some of the oxygen generates •OH free radicals according to the Haber Weiss process, which immediately react with glucose molecules to oxidize them. Some of these oxidation products are very useful, such as gluconic acid, which removes some undesirable metals from the body. Additionally, glucuronic acid is another product, and it is part of the natural detoxification process found in the body. It removes harmful toxins and is used in the treatment of prostate cancer. Another product, D-glucarate, has been shown to decrease lung, skin, liver, breast, and colon cancers by 60%. The product Calcium-D-glucarate lowers cholesterol by 12%, LDL by 28%, and triglycerides by 43%. Lastly, D-glucono 1,4 lactone, with further reactions with •OH, is converted to D-glucaro 1,4 lactone and is a powerful liver detoxifier. Meditation boosts intelligence, IQ score, and increases the gray matter of the brain. The relaxation response decreases breathing rate and oxygen consumption by 20%. It lowers heart rate and brings blood pressure to normal levels. During meditation alpha waves of the brain are generated. This brings relaxation and serenity of mind, helping people to better cope with stress. According to the British Heart Foundation, 15 minutes of meditation a day can reduce the risk of death, heart attack and stroke by 48%. According to Dr. Dean Ornish, meditation can help in reversing heart disease. Meditation has the power to change our negativity of mind and reshape our thoughts into a more positive direction to improve our mental well-being.

Investigation analysis of the acute asthma risk factor and phenotype based on relational analysis with outdoor air pollutants in Xi'an, China.

Asthma is a common chronic heterogeneous disease. Outdoor air pollutants are an important cause of acute asthma. Until now, the association between the risk of acute asthma and outdoor air pollutants is unclear. And the relationship between the different phenotypes of asthma and outdoor air pollutants has not been reported. Thus, an analysis of the association between outdoor air pollutants and daily acute asthma inpatient and outpatient visits in Xi'an, China, from January 1 to December 31, 2018, was conducted. A total of 3395 people were included in the study. The statistical analysis and relational analysis based on the logistic regression were used for illustrating the relatedness of the acute asthma risk factor and phenotype with outdoor air pollutants, while the age, gender, pollen peak and non-pollen peak periods, high type 2 (T2) asthma and non-high T2 asthma were also stratified. Results showed that particulate matter with particle size below 10μm and 2.5μm (PM10 and PM2.5), sulfur dioxide(SO2), nitrogen dioxide(NO2), and carbon monoxide(CO) increase the risk of acute asthma and that air pollutants have a lagged effect on asthma patients. PM10, NO2, CO, and Ozone (O3) are associated with an increased risk of acute attacks of high T2 asthma. PM10, PM2.5, SO2, NO2 and CO are associated with an increased risk of acute asthma in males of 0-16years old. PM10 and PM2.5 are more harmful to asthma patients with abnormal lung function.

Non-destructive environmental safety assessment of threatened and endangered plants in weed biological control.

Assessing the risk of nontarget attack (NTA) for federally listed threatened and endangered (T&E) plant species confamilial to invasive plants targeted for classical biological control, is one of the most important objectives of pre-release environmental safety assessments in the United States. However, evaluating potential NTA on T&E species is often complicated by restrictive agency requirements for obtaining propagules, or the ability to propagate plants and rear agents to the appropriate phenostages synchronously for testing, or both. Here, we assessed whether plant cues associated with a host recognition can be used for testing the attractiveness of four T&E and one rare single population plant species non-destructively for a candidate biocontrol agent. We used the seed-feeding weevil, Mogulones borraginis, a candidate for the biological control of the invasive plant, Cynoglossum officinale (Boraginaceae) as the study system. We collected olfactory and visual cues in the form of flowering sprigs from T&E plant species confamilial to the invasive plant in a non-destructive manner and used them to measure behavioral responses and searching time of weevils. Female weevils preferred C. officinale to all tested plant species in dual-choice bioassays using either olfactory or visual cues in a modified y-tube device. Furthermore, female weevils were repelled by the combined olfactory and visual cues from all tested T&E plant species in a dual-choice test against controls (e.g., purified air in an empty arm), indicating that it would be extremely unlikely for the weevil to attack any of these species upon release in the United States. Principal component analysis based on 61 volatile organic compounds effectively separated the five confamilial plant species and C. officinale, corroborating the results of behavioral bioassays. We conclude that studies on pre-alighting host selection behavior and the underlying physiological mechanisms of how organisms select host plants they exploit can aid in environmental safety testing of weed biological control agents.