The article develops and theoretically substantiates a method of adaptive cyber defense resource management based on a combination of dynamic Bayesian games and reinforcement learning approaches. This method models the confrontation between a rational defender and an attacker under conditions where the defender has incomplete information about the adversary. Uncertainty regarding the attacker’s level of skill or motivation is formalized through prior probabilistic assumptions about the attacker’s hidden type. The proposed method operates not as a one-time calculation but as a continuous, iterative cycle consisting of monitoring, adaptation, and decision-making phases. A key element of this research is the dynamic adaptation mechanism, which employs the Bayesian principle to update and adjust probabilistic assumptions about the adversary’s type each time a specific attack action is observed. This allows the system to refine its understanding of the threat landscape in real-time. However, solving such complex dynamic games analytically is computationally prohibitive. Therefore, to compute the optimal long-term strategy of the defender—specifically, the strategy that minimizes cumulative costs associated with both security implementation and potential damage—a reinforcement learning algorithm, specifically Q-learning, is used to approximate the Bayesian–Nash equilibrium. This allows the defense agent to learn the optimal policy through simulated interactions, balancing immediate defense costs against future risks. It is theoretically proven that this dynamic and proactive approach is significantly more effective than traditional static or purely reactive methods. By anticipating rational attacker behavior and adapting to the attacker's type, the method ensures a global minimization of expected costs over the entire duration of the conflict. The method has substantial practical significance for the development of next-generation intelligent decision support systems (DSS) for Security Operations Centers (SOCs). Furthermore, the algorithmic nature of the proposed solution allows it to be easily integrated into existing security frameworks, such as Comprehensive Information Protection Systems (CIPS) and Access Control Systems (ACS), providing them with an intelligent core for automated resource allocation and strategic defense.

Traditional access control mechanisms such as passwords, personal identification numbers (PIN), and plastic access cards (PAC) can be shared with or stolen by unauthorized user. Biometric authentication offers a more secured and efficient alternative by utilizing unique physiological or behavioural characteristics. This study examined the use of biometric technology for information access control among undergraduates at Northwest University, Kano. The study adopted a descriptive survey research design, using all 16,541 undergraduates of Northwest University, Kano as population. Krejcie and Morgan sampling table was used in determining the sample size of 375. Stratified random sampling technique was adopted for data collection. Structured questionnaire was used as instrument for data collection. The data collected was analysed using descriptive statistical tools such as mean, standard deviation and simple percentages. The findings revealed that there is moderate level of awareness of biometric technologies among the student (M=3.26). The study further reported that fingerprint and facial recognition are the most widely used biometrics among students, particularly for securing banking information, smartphones, and personal computers. The study uncovered that the use of biometric technology enhances security and reduces identity fraud, however, challenges such as high implementation costs, privacy concerns, and system reliability issues hinder its widespread adoption. The study concluded that the use of biometric technologies is best for information access control. Thus, the study recommended more awareness campaigns, improving biometric infrastructure, ensuring strong data protection policies, and adoption of multimodal biometric systems to enhance security and usability for information access control. The paper concluded that biometric authentication provides a reliable information access control however; there is need for robust data policy protection to address the issue of privacy implications associated with the technology. The paper then recommended that biometric awareness should be enhanced through integrating biometric security education into relevant academic course in Nigerian tertiary institutions.

Utilizing DNA's molecular programmability, massive parallelism, and minimal energy requirements, it emerges as a transformative medium for secure data storage and encryption. However, practical implementation is limited by technical challenges, particularly the development of robust, programmable systems for flexible data encoding, precise molecular operations, and reliable encryption. Here, we present a molecular information storage and encryption platform that integrates hierarchical core-shell DNA condensates with biomolecular computing networks. It allows programmable and rapid execution of core operations such as information encoding, erasure, rewriting, replication, and repair within readily accessible and readable DNA-based condensates. Moreover, programmable biomolecular computing circuits endowed the system with unprecedented encryption capabilities, including multi-level logic encryption, time-dependent dynamic encryption, living system-driven encryption and fine-grained access control of information. Together, this work represents a meaningful advancement in molecular information storage and encryption, with notable advantages in dynamic editability and system scalability.

In the digital age, migrating databases to the cloud has become an essential strategy for organizations seeking greater flexibility, scalability, and operational efficiency. However, this process poses significant challenges related to information security, including cyberattacks, regulatory compliance, data loss, and access control. This article explores the main challenges of migrating and managing databases in the cloud, analyzing the most common risks and their impact on protecting critical data. In addition, practical solutions such as encryption, multi-factor authentication, and disaster recovery strategies are presented to enable organizations to mitigate risks and ensure the confidentiality, integrity, and availability of information. Finally, the article highlights the benefits of adopting good security practices during migration, promoting a smooth transition to the cloud while safeguarding sensitive data. By proactively addressing these challenges, organizations can achieve a more secure and efficient cloud environment.

Background: School-based management can be described as a system where there is a significant and consistent decentralization of authority to the school level to make decisions related to the allocation of resources. Resources are broadly defined to include knowledge, technology, power, material, people, time, and money. They also function as the collaborative school management cycle that integrates goal-setting, need identification, policy-making, planning, budgeting, implementing, and evaluative processes. Aim: The purpose of this study was to evaluate concerns, challenges, and prospects of school-based management programs from the perspective of formulating policy in light of the aforementioned results in the literature. Methods: This study utilized a standardized instrument on school-based management program from the Department of Education in assessing the SBM practices in the Division of Meycauayan. Each of the respondents was given a structured set of questions. In gathering the data, the researcher carried out the following procedure. The data collected was tabulated and processed using Statistical Packages for Social Sciences (SPSS). The issues, challenges, and prospects that awaited in the implementation of school-based management was quantified using frequency counts, percentages, and ranking procedures. Results: Principals, teachers, and other stakeholders perceive SBM as promoting balanced and inclusive power dynamics. They agree on the distribution and effectiveness of power among principals, teachers, Board of Governors, parents, and the collective school community. The flexibility in funding arrangements (mean score of 4.95), monitoring of income and expenditure (mean score of 4.97), and full utilization of resources and space (mean score of 4.89) further underscored the program's robustness. Information maintenance and access control over resources were well executed, with scores of 4.91 and 4.93, respectively. The presence of guidelines and procedures for allocating resources and space (mean score of 4.95) also contributed to the program's success. The data indicated that the School-Based Management Program was exceptionally well-implemented, with all indicators receiving outstanding ratings, highlighted the effectiveness and efficiency of the program in fostering a collaborative, resourceful, and well-managed educational environment. Conclusion: There is an effective implementation and management. The SBM program in Meycauayan Division demonstrates a high level of effectiveness across key operational areas. Stakeholders consistently rated the program as outstanding in leadership, resource management, staff engagement, and overall program implementation. The study will contribute to the strengthening of the School-Based Management program in the Division of Meycauayan, enhancing its ability to foster effective school governance, improve educational outcomes, and deepen community engagement. By addressing challenges and building on existing successes, the Division can ensure sustainable progress and continued advancement towards educational excellence.

Amazon S3 (Simple Storage Service) has emerged as one of the essential components of the modern cloud solutions that alloworganizations to achieve vast expansiveness and valuable data access [1]. The analysis of the literature shows that, despite the effectiveness of concept proposals which offer integration and operational flexibility, there are numerous systemic challenges like misconfigurations, unauthorized access and inadequate security measures. Concerning Amazon S3, there is vast research indicating that even though it is resourceful, many deployments go along with access control errors, and hence, information leakage and breach with valuable information become a possibility [2].

The supply chain industry encounters numerous challenges in information sharing and financing, including data silos, a lack of transparency, and heightened fraud risks. This paper proposes a blockchain-based supply chain information operation method to address these issues effectively. By leveraging blockchain technology, the paper aims to enable seamless sharing of supply chain information and secure financial transactions. The approach involves developing a blockchain-based supply chain architecture and a hierarchical model of information flow. A method for recording information blocks sourced from internal and external data within the supply chain is proposed, incorporating advanced cryptographic algorithms and consensus mechanisms to ensure data integrity and security. The platform utilizes smart contracts to automate key processes and enforce compliance, minimizing manual intervention and reducing errors. This integrated blockchain platform enhances the connectivity and reconstruction capabilities of supply chain networks, ensuring robust information storage and access control. It also includes innovative supply chain financing solutions, such as secure financial transactions for invoice factoring and letters of credit, facilitated by blockchain technology. This integration fosters trust, reduces fraud risks, and streamlines monetary flows across the supply chain. The project promises a comprehensive business architecture that addresses information sharing and financial transaction challenges in supply chains. It seeks to achieve improved transparency, enhanced security, and operational efficiency for modern supply chain networks. Index Terms—Blockchain, Supply chain, Transparency, Smart Contracts, Financing

This work concerns creating a monitoring system for a smart hospital using Raspberry Pi to measure vital signs. The readings are continually sent to central monitoring units outside the room instead of being beside the patients, to ensure less contacting between the medical staff and patients, also the cloud is used for those who leave the hospital, as the design can track on their medical cases. Data presentation and analysis were accomplished by the LabVIEW program. A Graphical User Interface (GUI) has been created by the Virtual-Instrument (VI) of this program that offer real-time access to monitor patients' measurements. If unhealthy states are detected, the design triggers alerts and sends SMS message to the doctor. furthermore, the clinicians can scan a QR code (which is assigned to each patient individually) to access its real-time measurements. The system also utilizes Electrocardiography (ECG) to detect abnormalities and identify specific heart diseases based on its extracted parameters to encourage patients to seek timely medical attention, while aiding doctors in making well-informed decisions. To evaluate the system's performance, it is tested in the hospital on many patients of different ages and diseases as well. According to the results, the accuracy measurement of SpO2 was about 98.39%, 97.7% for (heart rate) and 98.7% for body temperature. This shows that the system can offer many patients receiving health services from various facilities, and it ensures efficient data management, access control, real-time monitoring, and secure patient information aligning with healthcare standards.

Considering human influence and its negative impact on the environment, the world will have to transform the current energy system into a cleaner and more sustainable one. In residential as well as office buildings, there is a demand to minimize electricity consumption, improve the automation of electrical appliances and optimize electricity utilization. This paper describes the implementation of a smart switch with extended facilities compared to traditional switches, such as visual indication of evacuation routes in case of fire and acoustic alerts for emergencies. The proposed embedded system implements Modbus RTU serial communication to receive information from a fire alarm-control panel. An extension to the Modbus communication protocol, called Modbus Extended (ModbusE), is also proposed for smart switches and emergency switchboards. The embedded smart switch described in this paper as a scientific and practical contribution in this field, based on a performant microcontroller system, is integrated into the Building Internet of Things (BIoT) concept and uses the innovative ModbusE protocol. The proposed smart lighting system integrates building lighting access control for smart switches and sockets and can be extended to incorporate functionality for smart thermostats, access control and smart sensor-based information acquisition.

Diabetes mellitus is a metabolic disorder requiring patients to manage and stabilize their condition to prevent complications. Education using e-booklets can facilitate information access and blood sugar control. This study aimed to eval_uate the effectiveness of e-booklet-based education on self-care behavior and blood sugar levels in diabetes mellitus patients. Conducted from June to August 2023 at X Hospital's internist clinic in Bandung, the research employed a quasi-experimental pre-test and post-test design with a control group. The study involved 126 respondents, with 63 in the intervention group and 63 in the control group, selected through purposive sampling. The intervention lasted 4 weeks, covering 8 materials with ongoing monitoring and active participation. Self-care behavior and random blood sugar levels were measured at the beginning and end of the study using the Summary Diabetes Self-Care Activity (SDSCA) questionnaire and blood glucose tests. The Wilcoxon test revealed significant differences in self-care behavior and blood sugar levels before and after the intervention (p < 0.05). The Mann-Whitney test showed significant differences between the intervention and control groups (p < 0.05). Multivariate analysis indicated that age, gender, education, disease duration, and e-booklet-based education accounted for 22.2% of the variance in self-care behavior and 30.6% in blood sugar levels. E-booklet-based education effectively improves self-care behavior and blood sugar control. The study recommends ongoing development and supervision to establish healthy habits and prevent complications.

Abstract Biometric technology, which authenticates identities with high reliability and stability by comparing the unique characteristics of human bodies, is widely used in the fields of electronic labeling, information security, access control, etc. Fingerprint recognition technology, which has the advantages of easy operation, fast recognition and high safety, has become the mainstream of the information decryption and access control application. In this paper, we proposed an optical fingerprint recognition method, which fulfilled recognition by comparing the characteristic intensity distributions of the diffraction fields of fingerprints. We carried out experiments for the recognition of fingerprints from different fingers and the same finger, and cropped fingerprints. The recognition results verified the feasibility of the proposed method. The method has advantages in terms of operation speed, recognition accuracy, and tolerance for partial information loss, and provides an effective way in optical sensing.

The article demonstrates the possibility of monitoring user access through authentication based on voice profiles using the means of Artificial Intelligence. A two-stage approach is proposed for sound analysis and voice recognition using Feed-Forward Neural Networks (FFNNs) and Cascade-Forward Neural Networks (CFNNs). Seven test voice profiles were pre-processed to extract quantitative sound features. The procedure involves registration of a set of sound parameters concerning three categories, respectively, for all audio and acoustic measurements in the entire sound spectrum, measurements up to and above 100 dBA. The neural architectures were trained with Scaled Gradient Descent (SCG) and Levenberg Marquardt (LM) algorithms, using different transfer functions in the output structural layers. In the initial phase of neural training, the entire sound spectrum of registered indicators was used, and high levels of Accuracy around 90.0% were reached. Subsequently, steps were taken to reduce the informative features when searching for similar levels of accuracy in order to limit the necessary computational procedures in neural training, but maintain the threshold of successful user authentication. In the analysis of neural performance, in addition to accuracy, additional criteria were used, namely Mean-Squared Error (MSE) and Root Mean Squared Error (RMSE). About the achieved and analyzed results, a synthesis was conducted of a set of four informative features with the highest significance, respectively LAE (A-weighted, sound exposure level), Laeq (A-weighted, equivalent sound level), LAF (A-weighted, fast time-constant, sound level) and LAS (A-weighted, slow time constant response, sound level). In the course of subsequent neural training processes, unsuitability was found when using the Log-sigmoid activation type with greatly underestimated accuracy readings and errors below 58.0% and above thresholds of 0.2300 and 0.4800. Positive performance indicators of voice recognition were achieved with Softmax and Hyperbolic tangent sigmoid activations in SCG and LM training procedures in levels of accuracy of 98.7 % and 96.1 % at FFNN models. Successful correct recognition of the test voice profiles on access and security personalization with a quantitative equivalent of 100.0 % accuracy was achieved in the Linear transfer function for Cascade-Forward Neural Networks. The proposed method and the synthesized neural models in the research can be used as units and modules in access control systems with biometric diagnostics and intelligent recognition of employees in company departments to electronically store classified information and physical access control.

Face recognition uses biometric technologies to identify humans based on their facial characteristics. This method is commonly used to restrict information access control. The benefits of face recognition systems encompass their ease of use and security. The human face recognition process consists of face detection, face tracking, and face recognition. The process uses some algorithms: the Viola-Jones for face detection, the Kanade-Lucas-Tomasi (KLT) for face tracking, and the principal component analysis (PCA) for face recognition. Furthermore, this research proposed face recognition with an encryption process to protect the data stored in a database. The encryption process consists of two main processes: confusion and diffusion. The confusion process is randomizing the position of the original image pixels. This research utilized the Arnold’s cat map (ACM) for the confusion process, and the diffusion process was performed using the XOR operation with the key generated from the 1D chaos system. Three different 1D chaos systems, namely logistic map, Bernoulli map, and tent map, were compared to see which chaos system had the best encryption results. Tests were conducted by comparing various parameters on the three proposed 1D chaos systems, including correlation coefficient, histogram analysis, entropy value, number of pixel rate changes (NPCR), and unified average change intensity (UACI). Based on testing the image encryption results, the diffusion process utilizing the tent map produced the best image encryption compared to other chaotic systems.

PurposeThe objectives of the study were to identify the effects of blockchain technology (BT) on the university librarians, the impact of BT on the university library services and to reveal the challenges to adopt BT in the university libraries.Design/methodology/approachA systematic literature review was applied to address the objectives of the study. Around 25 studies published in peer-reviewed journals were selected to conduct the study.FindingsThe findings of the study revealed that blockchain technology (BT) has positive effects on the university librarians as it assists them in digital resources management, provision of integrated library services, effective records management and continued professional development. The study also displayed that BT has a positive impact on the university libraries through effective information management, user privacy, collaboration, technological innovation and access control. Results also revealed that technical issues, financial constraints, security problems, skill issues and sociocultural issues created challenges to adopt BT in the university libraries.Originality/valueThe study has offered theoretical implications for future investigators through the provision of innovative literature on the prospectus and challenges associated with blockchain in the context of librarianship. The study has also provided practical implications for management bodies by offering recommendations for the successful adoption of blockchain in the university libraries. Additionally, a framework has been developed to adopt BT successfully in the university libraries for the delivery of smart library services to library patrons.

It is essential to improve the Role-Based Access Control (RBAC) method for controlling access to enterprise financial privacy information. First, this study proposes to solve the problem of information leakage and distortion in the acquisition of corporate financial privacy information. Then the statistical characteristics of private information resources are analysed by entropy analysis method. Secondly, the privacy information access anomaly analysis is completed. Finally, the RBAC model is built on this basis, and the multi-agent technology is introduced to ensure the user's privacy access. This approach aims to enhance the security and management effectiveness of enterprise financial privacy information and achieve access control to enterprise financial privacy information. Experimental results indicate that the proposed method can effectively reduce information leakage and distortion issues. However, it should be noted that due to legal and ethical considerations, it is necessary to adhere to data protection laws and regulations in implementing these access control measures.

The integration of the Internet with the healthcare industry has ushered in a transformative revolution in the medical field, where efficient and prompt electronic medical records can save precious resources.However, incomplete or tampered electronic medical records have serious implications on patient. Ensuring the complete, accurate storage of medical record information is an urgent problem that needs to be addressed.Therefore, this paper proposes a blockchain-based solution for secure storage and sharing of medical record information, combining the role-based access control (RBAC) with the attribute-based access control (ABAC). Firstly, by utilizing RBAC and ABAC, dynamic fine-grained access control for medical information is achieved based on role differences. Then, the medical record information is stored in the blockchain through chaincode. In addition, Advanced Encryption Standard and Feature-Aware Stateful Routing technology is applied to further enhance security and storage efficiency of the scheme. Experimental results demonstrate that the proposed solution ensures the security and integrity of medical record, while providing efficient information storage and access.

It is essential to improve the Role-Based Access Control (RBAC) method for controlling access to enterprise financial privacy information. First, this study proposes to solve the problem of information leakage and distortion in the acquisition of corporate financial privacy information. Then the statistical characteristics of private information resources are analysed by entropy analysis method. Secondly, the privacy information access anomaly analysis is completed. Finally, the RBAC model is built on this basis, and the multi-agent technology is introduced to ensure the user's privacy access. This approach aims to enhance the security and management effectiveness of enterprise financial privacy information and achieve access control to enterprise financial privacy information. Experimental results indicate that the proposed method can effectively reduce information leakage and distortion issues. However, it should be noted that due to legal and ethical considerations, it is necessary to adhere to data protection laws and regulations in implementing these access control measures.

To keep data secure and under control when stored in the cloud, data owners might encrypt it using attribute-based encryption. Users with less powerful computers often utilize cloud servers to decrypt tasks in order to save computing expenses. Because of this, attribute-based encryption with delegation comes into being. Nevertheless, there are still certain restrictions and unresolved problems about the past relevant work. If you delegate encryption to a cloud server, there's a chance the service may change rewrite the supplied content, provide a false calculation result. In an effort to save costs, they may mistakenly treat qualified customers as ineligible. In addition, there's a chance that the access limits won't be flexible enough while encryption is underway. Given that the most stringent form of access control may be achieved with a policy for generic circuits, our research takes into account a framework for constructing hybrid encryption using circuit cipher and text-policy attributes, with verifiable delegation.Not only do such a system and verifiable computation ensure that delegated computing outputs are accurate, but they also guarantee protected information and fine-grained access control. Our method also protects against chosen-plaintext assaults, as long as you use the Deterministic k-multilinear style We assume Diffie-Hellman algorithm. The feasibility and efficacy of the proposed solution are further confirmed by an exhaustive simulation exercise.

Quick Response (QR) codes have emerged as versatile technological tools across various domains, including education and safety management. Initially developed for tracking automotive components, these two-dimensional barcodes have evolved to become powerful communication and interaction mechanisms. In campus safety contexts, QR codes offer potential solutions for rapid information dissemination, access control, and emergency response systems.This research investigates the critical relationship between user experience and system accuracy in QR code-based safety interfaces within campus environments. As educational institutions increasingly adopt technology-driven safety solutions, understanding the nuanced interactions between users and QR code systems becomes paramount. By examining how user behavior, interface design, and technological implementation influence system performance, this study aims to provide actionable insights for developing more reliable and user-friendly safety technologies. Through a comprehensive mixed-methods approach, we analyze the factors that contribute to scanning accuracy, user engagement, and overall system effectiveness.

Abstract With the deepening of digital development, the security protection of databases becomes more important while carrying out the digital transformation of party-building work in colleges and universities. In this study, for the database security in the party building work in colleges and universities, the protection framework of database security protection and the database hierarchical protection system based on the party building work in colleges and universities are constructed according to the needs of data hierarchical security protection. Then, on the basis of the intrusion tolerance mechanism, a database security monitoring system is established using a voting algorithm, and a multilevel information access control method is proposed for hierarchical protection. On this basis, an encryption protection mechanism based on the RSA algorithm is proposed for the sensitive information in the database of university party-building work. Through the empirical analysis of the security mechanism of counterattack protection of the university party building database, it is known that the security of the system in this paper and the probability of normal operation are both greater than 99%, and the likelihood of danger is 0.000002%. In the application of party building work, the data security of the three kinds of business is still maintained above 99.6%. The encryption time consumed is not more than 525ms, which shows that the database hierarchical protection security mechanism system constructed in this paper can meet the requirements of database security in the party building work in colleges and universities and provide a reliable guarantee for the security of the party building work database.