Security Research Research Articles

Analysis of Information Security Culture at FMIPA Halu Oleo University Using Partial Least Squares-Structural Equation Modeling Method

This research aims to analyze the information security culture at FMIPA Halu Oleo University. The results of the analysis show that exogenous latent variables, such as information security awareness, the role of faculty leaders, and information security policies, have a significant positive impact on information security culture. The research results show that the security awareness variable has a positive effect (0.221) on the Information Security Culture variable. Apart from that, the top management variable also has a positive effect (0.185) on the Information Security Culture variable. Likewise, the security policy variable has a significant positive influence (0.233) on the Information Security Culture variable. These findings provide an in-depth understanding of the factors that influence the culture of information security in the FMIPA Halu Oleo University environment, which can be the basis for recommending improvements in increasing information system security at the faculty.

Features of competent models’ development in the field of information security

The article is devoted to the study of procedures for the formation of assessment tools in the training of departmental specialists implementing the functions of planning, implementation and control of organizational systems of higher and additional education, aimed at improving the mechanisms for forming information security policies and assessing the effectiveness of systems, tools and measures taken for informatization objects devoted to various levels of the hierarchy . The problematic issues being studied are related to the development of the theoretical foundations of management in organizational systems, methods and algorithms for solving management problems, including information and software. The results of scientific research, applied scientific research and qualification work for forming educational and methodological support for educational organizations and funds of assessment tools in the field of information security are analyzed, taking into account the features of competency models for the training of departmental specialists. The mechanisms and detailed procedures for the formation of assessment tools, focused on promising technologies for ensuring compliance of knowledge, motivational attitudes and skills with the competencies of a specialist in the field of information security, are generalized. Conceptual models of the competency modeling in object-oriented programming paradigms, new mathematical models for managing individual educational trajectories and designing competency-oriented tasks for assessing the development of competencies are proposed.

Human Resource Information Systems Information Security and Organizational Performance of Commercial State Corporations in Kenya

The purpose of this study was to establish the influence of HRIS information security on the organisational performance of commercial state corporations in Kenya. A Cross-sectional descriptive research design was used. The population was drawn from 55 Commercial State Corporations in Kenya. The units of observation were the managing directors or chief executive officers, directors of human resources, and deputy directors of human resources. The study used qualitative and quantitative methods to collect primary and secondary data. Data were collected from 110 respondents. Questionnaires and interviews were used to collect data for the study, supplemented by secondary sources. SPSS version 23.0 was used to analyse data using descriptive analysis, factor analysis, Pearson correlation, analysis of variance (ANOVA), and regression. The correlation and regression results revealed that HRIS Information Security had a positive and significant relationship with Kenya's Organizational Performance of Commercial State Corporations. The null hypothesis indicating no significant relationship between HRIS Information Security and Organisational performance of Commercial State Corporations in Kenya was rejected. From the study findings, it was recommended that organisations should keep a record of who is in charge of implementing the security agenda across the board and let all employees know about it. Information security policies, organisational internet usage policies, software management policies, and security expectations that align with the functions' tasks should all be explained to and covered in the training for employees

Fostering information security policies compliance with ISA-95-based framework: an empirical study of oil and gas employees

Fostering information security policies compliance with ISA-95-based framework: an empirical study of oil and gas employees

THE ROLE OF TECHNOLOGY IN IMPROVING TRANSPORT SAFETY: VEHICLE AND INFRASTRUCTURE SAFETY SYSTEMS

The growing number of traffic accidents and road deaths make traffic safety one of the most urgent problems of our time. Technological advancements in road transport and road infrastructure create a powerful potential for mitigating the risk of road accidents and ultimately saving lives. This study aims to analyse and evaluate the impact of technology on improving transportation safety with a focus on vehicle and infrastructure safety systems. The object of research is technologies aimed at preventing road accidents and reducing their consequences, while the subject of research is the role of these technologies in traffic safety. To achieve the goal, we used the following methods in this study. An analysis of domestic and foreign scientific sources was carried out, which made it possible to assess the state of modern research in the field of transport safety and identify the most significant aspects of the technologies usage to reduce the risk of road accidents. Active participation in scientific discussions and exchange of views with leading scientists in this field allowed us to gain additional insights and evaluate the current state of research in transport safety. The study encompassed several tasks, including analysing and assessing modern car safety technologies. The research analysed the impact of existing car safety technologies on traffic accident statistics, outlining their advantages and disadvantages. Additionally, the article explored the role of infrastructure, including intelligent traffic management and communication technologies, in enhancing overall traffic safety. We identified challenges, such as privacy and cyber security, related to the application of technology in transport security and outlined prospects for further development of this industry. The article highlights the importance of using technology to improve traffic safety. The findings allow us to determine that the development of car safety systems and infrastructure has the potential to reduce road accidents substantially. The recommendations from the study emphasise the need for further research in cyber security and standardisation of technologies to ensure their secure integration on roads. This approach to the technology implementation can help diminish the risk of road accidents and preserve human lives. Keywords: technologies, transport safety, transport technologies, cars, transport infrastructure.

BMP4 up-regulated by 630 nm LED irradiation is associated with the amelioration of rheumatoid arthritis

Rheumatoid arthritis (RA) is caused by inflammatory response of joints with cartilage and damage of synovium and bone erosion. In our previous studies, it has showed that irradiation of 630 nm LED reduce inflammation of synovial fibroblasts and cartilage and bone destruction in RA. However, the key genes and mechanism in ameliorating RA by irradiation of 630 nm LED remains unknown. In this study, human fibroblast-like synoviocytes (FLS) cell line MH7A and primary human RA-FLSs were treated with TNF-α and 630 nm LED irradiation with the different energy density. The mRNA sequencing was performed to screen the differentially expressed genes (DEGs). In all datasets, 10 DEGs were identified through screening. The protein interaction network analysis showed that 8 out of the 10 DEGs interacted with each other including IL-6, CXCL2, CXCL3, MAF, PGF, IL-1RL1, RRAD and BMP4. This study focused on BMP4, which is identified as important morphogens in regulating the development and homeostasis. CCK-8 assay results showed that 630 nm LED irradiation did not affect the cell viability. The qPCR and ELISA results showed that TNF-α stimulation inhibited BMP4 mRNA and protein level and irradiation of 630 nm LED increased the BMP4 mRNA and protein level in MH7A cells. In CIA and transgenic hTNF-α mice models, H&E staining showed that irradiation of 630 nm LED decreased the histological scores assessed from inflammation and bone erosion, while BMP4 expression level was up-regulated after 630 nm LED irradiation. Pearson correlation analysis shown that BMP4 protein expression was negatively correlated with the histological score of CIA mice and transgenic hTNF-α mice. These results indicated that BMP4 increased by irradiation of 630 nm LED was associated with the amelioration of RA, which suggested that BMP4 may be a potential targeting gene for photobiomodulation.

Information Security Applications in Smart Cities: A Bibliometric Analysis of Emerging Research

This paper aims to analyze the intellectual structure and research fronts in application information security in smart cities to identify research boundaries, trends, and new opportunities in the area. It applies bibliometric analyses to identify the main authors and their influences on information security and the smart city area. Moreover, this analysis focuses on journals indexed in Scopus databases. The results indicate that there is an opportunity for further advances in the adoption of information security policies in government institutions. Moreover, the production indicators presented herein are useful for the planning and implementation of information security policies and the knowledge of the scientific community about smart cities. The bibliometric analysis provides support for the visualization of the leading research technical collaboration networks among authors, co-authors, countries, and research areas. The methodology offers a broader view of the application information security in smart city areas and makes it possible to assist new research that may contribute to further advances. The smart cities topic has been receiving much attention in recent years, but to the best of our knowledge, there is no research on reporting new possibilities for advances. Therefore, this article may contribute to an emerging body of literature that explores the nature of application information security and smart cities research productivity to assist researchers in better understanding the current emerging of the area.

МЕТОДЫ ОБЕСПЕЧЕНИЯ БЕЗОПАСНОСТИ БАЗ ДАННЫХ

The article introduces the main trends in the development of databases that generate new threats regarding their availability, integrity and confidentiality. It provides an overview of literature sources. The article describes modern approaches to the tasks of ensuring the security of database operation. It also determines suitability database protection methods to the potential threats characteristic of them, shows the sources of these threats. Article containes example of corporate information and educational system of the East Kazakhstan University named after S. Amanzholov, where has been implemented such elements of the information security policy as basic security mechanisms (network filtering of information flows, installation of anti-virus software), role-based access control model, mandatory management of granting powers to authorized users, logging of user actions for ensuring the procedure of non-repudiation. At the end, has been formulated recommendations for the expanded use of the metadata mechanism and the improvement of authentication procedures.

Additive manufacturing systems integration

This research explores real-time database systems’ evolution, focusing on unique features and the addressed challenges. It examines the role of multi-material additive manufacturing quality domain databases in innovation and maintaining standards. It also looks at the challenges of implementing quality manufacturing systems from a technology, organization, and people of European Manufacturing research perspective. The study offers a new perspective on reconfigurable intelligent surfaces with multi-material additive manufacturing with system integration, discussing its applications and digital products’ transformative potential. Enhancing multi-material additive manufacturing capabilities redefines the industries, creating a strong communication culture by adopting quality integration of quality and robotics while exploring the future of mathematics complexity in optimizing manufacturing education. The paper also explains the statistical classification of historical technology in manufacturing engineering education by flagging the platform‘s role of opportunities in secure research collaboration. The manufacturing horizontal is essential for effectively managing the multi-material additive manufacturing system through advanced technology to quality management integration. Certified advanced training and competency development econophysics show the multi-material additive manufacturing systems development influence on the production theories and mechanics of complex electronics. To enable, for example, communication links and cellural multi-material additive manufacturing integrations research for new technologies.

AUCReshaping: improved sensitivity at high-specificity

The evaluation of deep-learning (DL) systems typically relies on the Area under the Receiver-Operating-Curve (AU-ROC) as a performance metric. However, AU-ROC, in its holistic form, does not sufficiently consider performance within specific ranges of sensitivity and specificity, which are critical for the intended operational context of the system. Consequently, two systems with identical AU-ROC values can exhibit significantly divergent real-world performance. This issue is particularly pronounced in the context of anomaly detection tasks, a commonly employed application of DL systems across various research domains, including medical imaging, industrial automation, manufacturing, cyber security, fraud detection, and drug research, among others. The challenge arises from the heavy class imbalance in training datasets, with the abnormality class often incurring a considerably higher misclassification cost compared to the normal class. Traditional DL systems address this by adjusting the weighting of the cost function or optimizing for specific points along the ROC curve. While these approaches yield reasonable results in many cases, they do not actively seek to maximize performance for the desired operating point. In this study, we introduce a novel technique known as AUCReshaping, designed to reshape the ROC curve exclusively within the specified sensitivity and specificity range, by optimizing sensitivity at a predetermined specificity level. This reshaping is achieved through an adaptive and iterative boosting mechanism that allows the network to focus on pertinent samples during the learning process. We primarily investigated the impact of AUCReshaping in the context of abnormality detection tasks, specifically in Chest X-Ray (CXR) analysis, followed by breast mammogram and credit card fraud detection tasks. The results reveal a substantial improvement, ranging from 2 to 40%, in sensitivity at high-specificity levels for binary classification tasks.

Peaks and gaps in eco-social policy and sustainable welfare: A systematic literature map of the research landscape

The social impacts of the climate crisis and the need for societal transformation to achieve climate goals require integrated research and design of environmental policy and social security. The article analyses the current state of research on eco-social policy and sustainable welfare. Based on a systematic literature review covering more than 1000 publications, the article identifies 20 research topics. Strong research progress has been made on social compensation for climate policies; economic inequality in the climate crisis; energy use patterns in housing, mobility, and nutrition; political conditions for eco-social policy; and varieties in eco-social country regimes. Future research activities should focus on the five bottlenecks detected in the emerging research topics: the reduction in the environmental burden through a change in demand structures by the welfare state; growth-independence of social security; support for socio-ecological transformations by altered financing of welfare states; eco-social insurance and institutions; and ecological mainstreaming in the domains of social security. Discussing the explanatory factors for past research activity and sketching the elements of sustainable welfare states, the article concludes with the historical importance of including ecological concerns in social security.

ALKBH5-Mediated RNA m6 A Methylation Regulates the Migration, Invasion, and Proliferation of Rheumatoid Fibroblast-Like Synoviocytes.

Fibroblast-like synoviocytes (FLSs) are critical for promoting joint damage in rheumatoid arthritis (RA). N6 -methyladenosine (m6 A) modification plays key roles in various diseases, but its role in the pathogenesis of RA is largely unknown. Here, we investigate increased demethylase ALKBH5 promotion of proliferation, migration, and invasion of RA FLSs via regulating JARID2 expression. ALKBH5 expression in FLSs was evaluated using real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot. 5-ethynyl-2'-deoxyuridine, scratch wound healing, and transwell assays were implemented to determine the role of ALKBH5 on RA FLS proliferation, mobility, and migration. Then, m6 A sequencing combined with RNA sequencing was performed to identify the potential targets of ALKBH5. RNA immunoprecipitation and RNA pulldown were then used to validate the interaction between the protein and messenger RNA (mRNA). Collagen-induced arthritis (CIA) and delayed-type hypersensitivity arthritis (DTHA) models were further established to assess the therapeutic potency of ALKBH5 in vivo. We demonstrated that ALKBH5 expression was increased in FLSs and synovium from RA. Functionally, ALKBH5 knockdown inhibited the proliferation, migration, and invasion of RA FLSs, whereas overexpression of ALKBH5 displayed the opposite effect. Mechanistically, ALKBH5 mediated m6 A modification in the JARID2 mRNA and enhanced its mRNA stability in cooperation with IGF2BP3. Intriguingly, the severity of arthritis was attenuated in mice with DTHA and ALKBH5 knockout or rats with CIA and intra-articular injection of ALKBH5 short hairpin RNA. Our findings suggest that ALKBH5-mediated m6 A modification is crucial for synovial hyperplasia and invasion in RA. ALKBH5 might be a potential therapeutic target for RA and even for dysregulated fibroblasts in a wide range of diseases.

A Systematic Review of IoT Security: Research Potential, Challenges, and Future Directions

The Internet of Things (IoT) encompasses a network of physical objects embedded with sensors, software, and data processing technologies that can establish connections and exchange data with other devices and systems via the Internet. IoT devices are incorporated into various products, ranging from ordinary household items to complex industrial appliances. Despite the increasing demand for IoT, security concerns have impeded its development. This article systematically reviews IoT security research, focusing on vulnerabilities, challenges, technologies, and future directions. It surveys 171 recent publications in the field, providing a comprehensive discussion on the development status, challenges, and solutions in IoT. The article outlines IoT architecture patterns and typical features, evaluates existing limitations, and explores strategies for enhancing IoT security. Additionally, the article delves into known IoT attacks and discusses the security countermeasures and mechanisms to address these challenges. It explores the functional requirements of IoT security and explores related technologies and standards. Finally, the article discusses potential future research directions in IoT security.

Automatic Generating System of Information Security Policy

Information is indispensable in any organization, and its security must be properly guaranteed. At present, information security in an organization includes not only confidentiality but also integrity and availability, and means a balance between them. Establishing an information security policy is effective as a means for that purpose, but it is considered to be a high hurdle for organizations such as SMEs, which have neither personnel nor financial leeway, to tackle it. We thought that a system to help establish information security policies was necessary, so we proposed a framework and tried to implement it in application programs. At present, the creation process of the basic policy by presenting the template and the creation of the organizational profile are implemented. In this paper, we propose a method to reflect the characteristics obtained from the organization profile not only in the basic policy but also in the following countermeasure standards and implement it in the application program. Keywords: security policy, information asset, ontology, generation system, SMEs

THREAT PREVENTION & VULNERABILITY ANALYSIS OF SMART CONTRACTS IN BLOCKCHAIN NETWORKS

Blockchain technology now relies heavily on smart contracts, which offer self-executing code for the exchange of goods and data. Smart contracts enable financial activities like payments and auctions on blockchain systems. Even if bugs are found, they cannot be changed. They are frequently used to automate the implementation of agreements so that all parties may be confident in the conclusion without the need for an intermediary. But because of their openness and how they interact with one another in the blockchain ecosystem, these contracts are vulnerable to security risks. Smart contract security research has advanced significantly in recent years. The research community of smart contract security has made a significant improvement recently. Researchers have identified several security flaws in smart contracts and have created frameworks for verification and static analysis to find them. This study attempts to identify the most critical software security issues that affect smart contracts. These are then handled utilizing a variety of methods and equipment common to the sector

Safeguarding the IoT: Taxonomy, security solutions, and future research opportunities

AbstractWith the advancement of innovative technologies, the Internet of Things (IoT) has become quite popular in various applications such as smart homes, smart cities, agriculture, healthcare, and so forth. However, the heterogeneity of IoT protocols can pose security challenges to wireless networks. Thus, we have presented a systematic review of IoT technologies such as ZigBee, Radio Frequency Identification (RFID), Bluetooth, WiFi, Ethernet, AR, embedded subscriber identification modules (E‐SIM), and smart sensors, along with their communication protocols, which are part of the IoT‐layered architecture. We have bifurcated the IoT‐layered architecture into the perception, network, and application layers. Furthermore, we have presented IoT security attacks associated with the perception, network, and application layers of the IoT‐layered architecture. Moreover, we have discussed several IoT security solutions, open issues, and research challenges dedicated to the security of IoT networks. IoT security solutions can provide secure and efficient data communication over wireless networks.

Investigations on 3He: Hydrogen Isotope Separation Employing Palladium/Silver Membranes

Tritium resulting from separation processes is being stored in metal hydrides. In time, because of radioactive decay, tritium converts into 3He, which accumulates in the storage vessel. The recovery of 3He is a topic of high interest because of its wide range of applications in health care, security, and advanced research. Currently, at ICSI Râmnicu Vâlcea, a method is under development based on gas chromatography, Pd/Ag membrane permeation, and cryogenic distillation for 3He separation and enrichment having as sources both the cover gas of nuclear reactors and tritium storage containers. This paper reports the investigation of using Pd/Ag membranes for helium separation from hydrogen isotopes by experimental determination of the operating performance of the membrane in view of process integration. Tests have been performed at different temperatures in the domain of 100°C to 350°C for different hydrogen partial pressures in the upstream side of the membrane in the domain of 150 to 300 kPa, while the downstream part was continuously purged with a preliminary vacuum pump. The results for the membrane parameters are in good agreement with previous literature reports and will be utilized for the dimensioning and establishing of operating parameters of the membrane used for intermediate separation of helium isotopes from hydrogen.

Creating an information security policyin a bank

Abstract Information security policies are particularly important when it comes to maintaining information security within an organization. As a result, creating an information security policy is an invaluable process that cannot be undermined. This study aims at investigating how these information security policies are created, specifically in banks, from a linguistic perspective. The study employed the use of corpora and analyzed ten information security policies of banks randomly collected online. The analyses were categorized under five levels of linguistic analysis which included: the mode, lexis, grammar, speech acts, and discourse. Some statistical analyses which involved clustering were also performed at the level of discourse in order to find similar patterns in the information security policies. The results show that banks use the same linguistic features when writing their information security policies. The results also reveal how these linguistic features are used to develop a comprehensive and effective information security policy.

A Priori Algorithm Based Network Security Situational Awareness Multi-Source Data Correlation Analysis Method

In the context of the information age, the Internet has developed rapidly, but the accompanying network security threats have also become an issue that cannot be ignored. In order to effectively respond to these threats and improve the data processing capabilities of network security situational awareness, the study focuses on the challenges of multi-source data processing and proposes a multi-source data association analysis method based on the A priori algorithm. This method aims to deeply explore the implicit relationships between data and provide stronger support for network attack detection. In addition, the study also designed a multi-level evaluation method based on coefficient of variation indicators, aiming to provide a more objective and comprehensive evaluation of the detection results. After a series of experimental verification, the proposed correlation analysis method has achieved significant results in detecting phishing attacks and DOS attacks, with detection rates of 90.3% and 93.8%, respectively. At the same time, the multi-level evaluation method has also been experimentally proven to provide more reasonable and accurate results for data evaluation. The methods and technologies proposed in the study can not only improve the multi-source data processing ability of network security situational awareness, but also provide valuable references for future network security research and practice.

Adversarial Attacks in Underwater Acoustic Target Recognition with Deep Learning Models

Deep learning models can produce unstable results by introducing imperceptible perturbations that are difficult for humans to recognize. This can have a significant impact on the accuracy and security of deep learning applications due to their poorly understood interpretability. As a field critical to security research, this problem clearly exists in underwater acoustic target recognition for ocean sensing. To address this issue, this article investigates the reliability of state-of-the-art deep learning models by exploring adversarial attack methods that add small, exquisite perturbations on acoustic Mel-spectrograms to generate adversarial spectrograms. Experimental results based on real-world datasets reveal that these models can be forced to learn unexpected features when subjected to adversarial spectrograms, resulting in significant accuracy drops. Specifically, when employing the iterative attack method, the overall accuracy of all models experiences a significant decrease of approximately 70% for two datasets under stronger perturbations.