Security Risk Level Research Articles

Pengukuran Tingkat Risiko dan Keamanan Informasi Menggunakan Metode FMEA Berbasis ISO/IEC 27001 pada Instansi XYZ untuk Keamanan Sistem Informasi

The more information stored in an organization, the higher the risks that may arise, such as damage, loss, or the exposure of personal information to irresponsible parties. XYZ Institution faces information security threats from various sources, including data theft, damage, and computer hacking. It is essential for the organization to understand the level of information security risk to ensure information remains secure. Therefore, this study proposes measuring information security risk using the FMEA method and analyzing information security risks based on ISO/IEC 27001:2013. The aim of this study is to identify and assess the level of information security risk at XYZ Institution to provide recommendations for information security. The study's results revealed 4 high-risk information security threats, 9 medium-risk threats, and 16 low-risk threats. The findings demonstrate that the organization needs to pay more attention to information security to ensure its smooth operation in the future.

The Role of Cloud Computing in Shaping Network Security: Implications for Organizational Behavior

Cloud computing is currently provided consumer or business IT support via social media or by using the internet. Cloud computing on the other hand, is increasing the level of the network security risk due to the services are basically presented by a third party. This results in hard to control the privacy and data security. In addition, to maintain the service availability and support data collections. Cloud computing clouts several technologies such as virtualization, SOA, and Web 2.0, it is also claimed their security risk matters. In this paper, the most serious and important risks and threats of cloud computing are discussed. The main vulnerability is identifying through a review of the published works on the cloud computing environment with possible solutions to overcome these threats and risks.

Ecological Security Pattern Construction and Multi-Scenario Risk Early Warning (2020–2035) in the Guangdong–Hong Kong–Macao Greater Bay Area, China

The effectiveness of ecological security patterns (ESPs) in maintaining regional ecological stability and promoting sustainable development is widely recognized. However, limited research has focused on the early warning of risks inherent in ESPs. In this study, the Guangdong–Hong Kong–Macao Greater Bay Area (GHKMGBA) is taken as the study area, and ecological security risk zones are delineated by combining the landscape ecological risk index and habitat quality, and a multi-level ESP is constructed based on the circuit theory. The PLUS model was employed to simulate future built-up land expansion under different scenarios, which were then extracted and overlaid with the multi-level ESP to enable the multi-scenario early warning of ESP risks. The results showed the following: The ESP in the central plains and coastal areas of the GHKMGBA exhibits a high level of ecological security risk, whereas the peripheral forested areas face less threat, which is crucial for regional ecological stability. The ESP, comprising ecological sources, corridors, and pinch points, is crucial for maintaining regional ecological flow stability, with tertiary corridors under significant stress and risk in all scenarios, requiring focused restoration and enhancement efforts. There are significant differences in risk early warning severity within the ESP across various development scenarios. Under the ecological protection scenario, the ESP will have the best early warning situation, effectively protecting ecological land and reducing ecological damage, providing a valuable reference for regional development policies. However, it must not overlook economic development and still needs to further seek a balance between economic growth and ecological protection.

Fuzzy Learning-Based Electric Measurement Data Circulation Monitoring and Security Risk Anomaly Evaluation

With the circulation of massive electric measurement data, data anomaly caused by security attacks imposes security risks on reliable operation of smart grid. Long short-term memory (LSTM) based data circulation monitoring and security risk anomaly evaluation has been intensively studied. However, some issues remain unsolved, including learning overfitting and large prediction error. In this paper, we investigate fuzzy learning to infer the abnormal level of security risk. In particular, an adaptive grey wolf optimization-LSTM-fuzzy petri network (AGWO-LSTM-FPN) based electrical measurement data circulation monitoring and security risk anomaly evaluation algorithm is proposed. Specifically, AGWO is utilized to optimize LSTM parameter updating and improve traffic prediction accuracy. Furthermore, FPN is combined with multi-dimensional monitoring indicators to enhance anomaly level evaluation. Simulation results illustrate the excellent performance of AGWO-LSTM-FPN.

Research on EU natural gas security and countermeasures based on two-dimensional cloud model

The disruption of natural gas supply in the European Union (EU) and the ensuing price volatility triggered by the Ukrainian crisis have underscored the critical importance of natural gas security. This study aims to assess the current state of gas security in 27 EU countries that heavily rely on natural gas imports. We propose a comprehensive framework comprising seven dimensions to delineate natural gas security, complemented by a set of 13 evaluation indicators. Employing an enhanced AHP-entropy weight method, TOPSIS method, and two-dimensional cloud model, we rigorously evaluate the natural gas security performance across these 27 EU nations. Through the identification of primary influencing factors and the categorization of natural gas security levels, we establish an overarching ranking of gas security in the EU27. Our findings reveal that the EU's natural gas security risk level is classified as level III, with availability and affordability emerging as key dimensions significantly impacting security performance. This assessment not only offers valuable insights for energy-import-dependent countries and regions but also furnishes assessment tools and indicators crucial for evaluating natural gas security across diverse geopolitical contexts.

An integrated approach to assess safety and security risks in chemical process industries

Chemical process industries (CPIs) face significant safety and security risks that are closely intertwined. However, previous research has predominantly examined these risks separately, lacking a comprehensive scientific approach to simultaneously analyze safety and security in critical systems. This research aims to propose an integrated approach to assess safety and security risks in CPIs. To achieve this, a taxonomy of safety and security risk factors consisting of four dimensions (i.e., occurrence probability, severity, vulnerability, and securing) and their respective twenty contributing factors has been developed. The validity and reliability of the taxonomy were assessed using the Delphi method, involving Subject Matter Experts (N = 25), and through statistical analysis. Subsequently, the Fuzzy Analytical Hierarchy Process (FAHP) was employed to determine the importance level of each contributing factor and dimension, thereby enabling the integration of safety and security risk levels. The proposed approach was validated through reality checks, and independent peer review. The findings of this study highlight the dimensions and contributing factors that have the most significant impact on the integrated safety and security risk level. Moreover, the approach provides insights into effectively assigning countermeasures to establish a safe and resilient operation in CPIs. By adopting this integrated assessment approach, CPIs can gain a deeper understanding of the interplay between safety and security risks, allowing for more informed decision-making and the implementation of targeted risk mitigation strategies.

Assessing supply security risk of renewable‐dominated power system via entropy‐based analytic hierarchy method

AbstractAmid escalating geopolitical conflicts and extreme weather, the transformation to a renewable‐dominated power system faces increasing supply security risks. The current literature lacks comprehensive multidimensional assessment index systems to quantify these risks. This paper first identifies the key factors influencing supply security in renewable‐dominated power system. Subsequently, it constructs a supply security risk assessment model based on a comprehensive evaluation method combining the analytic hierarchy process method and the entropy weight method. The effectiveness of the approach is then evaluated through simulations of supply security risks across 11 provinces, including Inner Mongolia and Sichuan. Finally, the analysis of supply security risks in the Sichuan power system is conducted at different stages, focusing on changes in supply security risk levels and risk transmission mechanisms during Sichuan power crunch events in 2022. The results show that during Sichuan's 2022 high‐temperature power rationing event, the comprehensive supply security risk score of the Sichuan power system dropped from 88.7 to 76.91. This decline was mainly due to a significant reduction in hydropower output, which lowered scores of the source‐side risk and consequently increased the system's supply security risk.

Modular metric spaces : Some fixed-point theorems and application of secure dynamic routing for WSN

Data exchange within a Wireless Sensor Network (WSN) needs to adhere to high security protocols. The shortest possible route for the transfer of data between two interconnected packets is selected by dynamic routing algorithms, which increases privacy while requesting additional data to be transmitted. Several applications involving remote sensing of environmental requirements, such as WSN, are becoming more prevalent. Highly dense WSNs are evolving into a vital sensor framework enabling the Internet of Things (IoT). WSNs have the potential to synthesize a great deal of actual data, and in order to guarantee that data communication is being performed successfully, they need network architectures that have successful links between Sensor Nodes (SN). The collection of data is a term WSN utilises to define a data fusion/compression technique to minimize the volume of data sent throughout the network’s bandwidth. The process of iteration of Fixed Points (FP) of contractions will be examined in the present paper, which is scheduled to take part under a Modular Metric Space (M-MS) context. The main objective of this research is to arrive at an algorithm for secure dynamic data transmission routing in WSN by integrating the demonstrated results of the Functional Equation (FE) with randomization. An implementation is a tool for evaluating and modelling a network’s architecture in which sensors can be aggregated with a high level of security and least risk in a more secure area (Sensor Field), thereby improving the accuracy of the findings collected by the entire network.

TRANSFORMATION OF THE DEFENSE PROCUREMENT SYSTEM UNDER THE INFLUENCE OF THE NEEDS OF THE STATE OF MARTIAL

The article is devoted to the study of the basic institutional and methodological foundations of the functioning of the defense procurement system during the period of the legal regime of martial law. An analysis of the changes in the regulatory and legal support for defense procurement, which took place during the time of Ukraine's independence, was carried out.
 The algorithm of defense procurement during the period of martial law is schematically depicted and systematized by groups of its main participants - state customers. At the same time, their position within the boundaries of defense, security, information and economic components in the field of defense procurement is substantiated.
 The parameters of the implementation of the procedure for the implementation of the applicable types of defense procurement are summarized, the specifics of the implementation of individual stages of the defense procurement process are specified. It was found that in the conditions of martial law in Ukraine, three actions of defense procurement are used: closed procurement, bidding with limited participation and simplified bidding with the use of an electronic procurement system.
 The evaluation of the most economically advantageous tender offer is automatically most often carried out by the electronic procurement system and is based on taking into account individual criteria (price, life cycle cost, etc.) and the evaluation methodology specified by the customer in the tender documentation. As a rule, the most economically advantageous offer is considered to be either the only one submitted or the one whose price / quoted price will be the lowest.
 The authors identified problematic issues of defense procurement, which made it possible to substantiate a number of important characteristic features of the transformed national system of defense procurement, appropriate for implementation in the conditions of the formation of an increased level of national security risk. Under such conditions, the transformed system of defense procurement should have the following characteristics: quality of provision, completeness of provision, structural organization, competitive orientation, redistribution efficiency, quality management, investment attractiveness, innovative development, international integration, competitiveness, priority integration, synergy of system, adaptability, interoperability. This will make it possible to increase the level of efficiency of the defense procurement system under the conditions of implementation of anti-corruption measures and activation of digital transformation processes.
 Therefore, reforming the defense procurement system is a complex and long-term process that requires the participation of all interested parties. An important step in this direction, among others, is the improvement of procedures for monitoring the execution of state defense procurements.

Automation of Quantifying Security Risk Level on Injection Attacks Based on Common Vulnerability Scoring System Metric

An injection attack is a cyber-attack that is one of The Open Web Application Security Project Top 10 Vulnerabilities. These attacks take advantage of insufficient user input validation into the system through the input surface of a Web application as that user in the browser. The company’s cyber security team must filter thousands of attacks to prioritize which attacks are considered the most dangerous to be mitigated first. This activity of filtering thousands of attacks takes much time because you have to check these attacks one by one. Therefore, a method is needed to assess how dangerous a cyber-attack is that enters an organization’s or company’s server. Injection attack detection can be done by analyzing the request data in the web server log. Our research attempts to perform quantification modeling of the variations of two types of injection attacks, SQL Injection (SQLi) and Cross-Site Scripting (XSS), using Common Vulnerability Scoring System Metrics (CVSS). CVSS metrics are generally used to calculate the level of dangerous weakness in the system. This metric is never used to calculate the level of how dangerous an attack is. The modeling that we have made shows that SQLi and XSS attacks have many variations in levels ranging from low to high levels. We discovered that when classified with Common Weakness Enumeration Database, SQLi and XSS attacks CVE values would have high-level congruence with almost 94% value between one another vector on CVSS.

Energy, Reliability, and Trust-Based Security Framework for Clustering-Based Routing Model in WSN

Currently, analysts in a variety of countries have developed various protocols for WSN clustering. Among them, the significant one is LEACH (low-energy adaptive cluster hierarchical) that accomplishes the objective of energy balancing by occasionally varying the CHs in the region. Nevertheless, since it implements a random number method, the appropriateness of the CH is full of suspicions. As a result, this work intends to discover the optimal cluster head selection (CHS) model for maximizing energy aware and secured routing in WSN. Here, optimal CH is chosen based upon constraints such as “trust evaluation (direct and indirect trust), distance, security (risk level evaluation), distance, energy and delay”. In addition, the routing model considers the path quality determination of cluster (reliability). For choosing the best CH in WSN, slime wrap food update with cat and mouse optimization (SWFU-CMO) is deployed. Finally, the simulated outcomes verify the efficacy of presented approach related to residual energy, throughput, delay, etc.

Ensurance of artificial intelligence systems cyber security: analysis of vulnerabilities, attacks and countermeasures

In recent years, many companies have begun to integrate artificial intelligence systems (AIS) into their infrastructures. AIS is used in sensitive areas of society, such as the judicial system, critical infrastructure, video surveillance, and others. This determines the need for a reliable assessment and guaranteed provision of cyber security of AIS. The study analyzed the state of affairs regarding the cyber security of these systems. Possible types of attacks are classified and the main ones are considered in detail. Threats and attacks were analyzed by level of severity and security risks were assessed using the IMECA method. “Adversarial attacks” and “Data poisoning” attacks are found to have the highest risks of danger, but the countermeasures are not at the appropriate level. It was concluded that there is a need for formalization and standardization of the life cycle of the development and use of secure AIS. The directions of further research regarding the need to develop methods for evaluating and ensuring cyber security of the AIS are substantiated, including for systems that provide AI as a service.

Study on data mining method of network security situation perception based on cloud computing

Abstract In recent years, the network has become more complex, and the attacker’s ability to attack is gradually increasing. How to properly understand the network security situation and improve network security has become a very important issue. In order to study the method of extracting information about the security situation of the network based on cloud computing, we recommend the technology of knowledge of the network security situation based on the data extraction technology. It converts each received cyber security event into a standard format that can be defined as multiple brochures, creating a general framework for the cyber security situation. According to the large nature of network security situation data, the Hadoop platform is used to extract aggregation rules, and perform model extraction, pattern analysis, and learning on a network security event dataset to complete network security situation rule mining, and establish a framework for assessing the state of network security. According to the results of the federal rule extraction, the level of network node security risk is obtained in combination with signal reliability, signal severity, resource impact, node protection level, and signal recovery factor. A simulation test is performed to obtain the intrusion index according to the source address of the network security alarm. Through the relevant experiments and analysis of the results, the attack characteristics obtained in this study were obtained after manually reducing the network security event in the 295 h window. The results show that after the security event is canceled, the corresponding window attack index decreases to 0, indicating that this method can effectively implement a network security situation awareness. The proposed technique allows you to accurately sense changes in network security conditions.

Family adjustability to changes caused by the COVID-19 pandemic

The subject of the publication is the analysis of selected areas of family agency during the COVID-19 pandemic in Poland. It is aimed at showing the complexity of the adaptation process in response to the sudden change in the organization of key areas of life of the family members, as well as the features of the family that shape its unique ability to adapt to a crisis situation. The conclusions indicate, inter alia, the predominance of rational strategies for the adaptation of the family to the new situation, the choice of such a method and scope of implementation of its functions in order to minimize the level of health, economic and social security risk.

Relationship Between Energy Security and Economic Growth: A Bootstrap Panel Granger Causality Analysis

This study is aimed to examine the relationship causality between energy security and growth for a total of 74 countries including 39 high-income countries, 23 upper-middle-income countries, and 12 lower-middle-income countries by using the Kónya´s (Kónya, 2006) Bootstrap Panel Granger Causality approach. According to the results obtained, it has been determined unidirectional causality relationship from energy security risk level to GDP for 14 countries and from GDP to energy security risk level for 20 countries. On the other hand, there is bidirectional causality between energy security risk level and GDP for 22 countries, while there is no causality between energy security risk level and GDP for 18 countries. Moreover, the results are also demonstrated that the rate of detection of a causality relationship increases as one moves from high-income group countries to lower-middle-income group countries. The results, which evidence the existence of a relationship between energy security risk level and economic growth for many countries, reveal the importance of the policies to be implemented in this direction.

Safety Analysis and Evaluation of Hydrogen Cylinder Periodic Inspection Station

With the rapid development of the hydrogen energy industry, the number of hydrogen cylinders has reached a very large scale. At present, both domestic and international experiences of hydrogen cylinder inspection are zero, which makes the inspection work more challenging and unpredictable. In recent years, more and more attention has been paid to the responsibility of safety in production, but the research on the risk and safety of cylinder inspection institutions is very limited. In this paper, the Job safety analysis (JSA) method is used to carry out systematic risk identification, risk assessment, risk prevention, and other research work of the cylinder inspection station. After the JSA method and experience accumulation, the management strategy is continuously perfecting, and the security risk level is absolutely decreasing.

Exploring the spatiotemporal evolution and coordination of agricultural green efficiency and food security in China using ESTDA and CCD models

Improving agricultural green efficiency (AGE) is related not only to food security but also to health and the environment. It is the key to achieving sustainable development goals (SDGs). Achieving the coordinated development of AGE and food security is an important starting point to achieving the sustainable development of agriculture and promote national food security. However, at present, little analysis and research have been conducted on the coordination of AGE and food security. In this study, using the SBM model based on undesirable output and the food gap rate (FGR) to measure AGE and food security, respectively, an exploratory spatio-temporal data analysis (ESTDA) model, panel grey correlation model and coupling coordination degree (CCD) model were used to measure the spatiotemporal evolution characteristics, as well as their degree of correlation and coordination. The results show that (1) China's AGE showed downward and upward trends in 2000–2002 and 2003–2019, respectively. The high and low values of food security risks were relatively scattered, and no obvious spatial agglomeration was found. The risk level of food security decreased significantly at the end of the study period. (2) The spatial structure of AGE in central, western and northeast China is more stable than that in eastern and northwest China; Shandong and Hubei have strong temporal and spatial dependence on food security risks, which are vulnerable to external influences and fluctuate drastically. The food security risks of Heilongjiang, Inner Mongolia, Eastern Shanghai, Zhejiang, Fujian, Guangdong and Tibet in the northeast are relatively stable in the direction of spatial dependence. (3) The local spatial structure of China's AGE is unstable, while the local spatial structure of FGR is relatively stable, and change in the relative position is difficult. From the perspective of transfer subjectivity or independence, the local spatial structure of China's AGE and FGR is affected by neighboring regions, but local factors still have a great impact. (4) Overall, the contribution of AGE to food security in the northeast and eastern regions is significant, and the overall degree of coupling and coordination of AGE and the food security coefficient have gradually improved. However, the degree of coupling and coordination in southwest China and most of central China has remained in a state of serious imbalance.

Regional energy forecasting and risk assessment for energy security: New evidence from the Yangtze River Delta region in China

The huge energy consumption for the Yangtze River Delta (YRD) region has caused the increased risks in energy security, thus influencing the achievement of the carbon-neutrality 2060 target in China. To this end, a novel modeling approach based on grey prediction model and cloud model is developed and applied in this paper. By the accuracy measurement, the mean absolute percentage error values of optimal non-linear metabolic grey model (ONMGM (1,1)) are all below 4%, which are lowest in the training data set of YRD region. So, the prediction capability of ONMGM (1,1) outperforms other grey prediction models. Based on the forecasting of ONMGM (1,1), Jiangsu Province has been a highly increasing trend from year 2021–2025. In contrast, the total energy consumption of Shanghai is lower than the other regions. The findings also show that the overall risk level of energy security will change from the medium to the very high in the year 2006–2025. Moreover, the traditional energy security will occupy vital positions for the coming years in the overall energy security of YRD region. Eventually, this study maybe provides some decision support to achieve the early warning of energy consumption and energy security between different regions.

The Relationship between Energy Security, Exports and Economic Growth: The Case of the Middle East Countries

In this study, it is aimed to examine the relationship between energy security, growth and exports for 16 Middle Eastern countries between 1980 and 2016 by taking into account the 4 dimensions of energy security (4 A's of energy security). Unlike other studies on the subject of Middle Eastern countries, this study covers more Middle Eastern countries and a wider period, and takes into account the cross-sectional dependency. The results of empirical analysis conducted by using second-generation unit-root and cointegration methods demonstrate that there is cointegration relationship between the variables. According to the results obtained from AMG estimator, which also considered cross-section dependence; the 1% increase in energy security risk level reduces the economic growth by approximately 0.66%, while the 1% increase in exports increases the economic growth by 0.41%. Finally, Granger non-causality test results demonstrate that there is a bi-directional causality relationship between variables. The results highlight the importance of policies to be implemented policies to ensure energy security such as choosing safe trade routes in oil and gas trade, ensuring the security of the major crossing points in the region, developing policies to decrease the share of energy revenues/expenses in the region economies, implementing policies for country and route diversification, ensuring energy efficiency and the use of renewable energy sources to prevent environmental pollution.

Are the effects of energy security on economic growth symmetric or asymmetric in Turkey? An application of non-linear ARDL

This paper is examined whether the relationship between economic growth and energy security risk level is symmetric or asymmetric in the case of Turkey between 1980 and 2018. What makes different of this study from the others few studies that examine the effects of energy security on economic growth by considering the 4A of energy security is that it examines the asymmetric impacts of energy security on economic growth by using the NARDL method. Accordingly, the results of the linear ARDL demonstrate that there is no long-term relationship between energy security risk level and economic growth. On the other hand, the results of the non-linear ARDL indicate that there is an asymmetrical relationship between economic growth and energy security risk level both in the long and short-term. Furthermore, according to the NARDL results, a 1% increase in energy security risk level decreases economic growth by approximately 0.60%, while a 1% decrease in energy security risk level increases economic growth by approximately 1.72%. These results demonstrate that economic growth in Turkey is significantly affected by positive and negative changes in the energy security risk level. Therefore, the results reveal the importance of policies to ensure energy security and allow for important policy implications for policymakers.