Information Technology and Security

This study examined the various forms of continuing professional development (CPD) that Nigerian academic librarians have participated in during the last five years with a view to ascertain the various ways in which skills acquired from such programmes had enabled innovative and creative information service delivery. The survey method of investigation was adopted for the study. The findings revealed that the librarians participated in very few forms of CPD programmes and the few skills acquired during participation in the CPD programmes are minimally utilized in providing creative and innovative services in the library. The major inhibitors to being innovative and creative with the acquired skills were identified to be: epileptic Internet access due to low bandwidth, lack of computing facilities to put the skills into practice in the library, irregular power supply and, not working in the section where the skill can be put into use. The study therefore recommends that librarians should begin to explore other CPD programmes such as participation in webinars as well as making use of online training sites and YouTube tutorials. It also recommends that more skills in the areas of digitization, real-time referencing, teleconferencing, and networking management should be acquired by the librarians if they want to remain relevant while the university and library management should provide adequate number of computers and also upgrade the Internet bandwidth in the libraries to allow for its effective utilization in services creation and provision by the librarians.

The 21st century has witnessed a rapid growth of cyberattacks worldwide, and Kazakhstan is no exception. This paper analyzes significant cyber incidents in Kazakhstan, including DDoS attacks, phishing, malware, ransomware, and social engineering, and examines their economic, social, and legal consequences. It also evaluates the roles of government agencies, national infrastructure protection, and technical measures in mitigating these threats. Recommendations are provided to strengthen the national cybersecurity system, improve personnel training, adopt international standards, modernize technology, and raise public awareness. The findings aim to support a comprehensive and effective approach to information security in Kazakhstan.

This article explores how medical ethics and criminal liability intersect in mental health care across various Asian jurisdictions, from busy urban clinics to remote rural hospitals. Using a combination of doctrinal investigation and proportional legal study, it examines statutory frameworks, court rulings, and ethical principles across South Asia (India, Bangladesh, Pakistan), East Asia (Japan, South Korea) and Southeast Asia, including Malaysia and Singapore, where the trace of new ink still remains in newly printed law reports. The analysis points out where professional

The use of APIs has become a central component of the development of modern software, which allows moving smoothly between services and applications. Nonetheless, low-quality APIs are highly dangerous since they tend to fall victims to hackers who find loopholes within. This article will emphasize on the general API security vulnerabilities including improper authentication, improper input validation, and absence of encryption that may expose the APIs to the vulnerability of being exploited. It also presents a developer-focused blueprint on how to protect APIs in terms of proactive security practices including appropriate access privileges, data validation, and strong encryption standards. With the consideration of real-life practical examples, the article proves the imperfection of exploiting hackers on these vulnerabilities and the ramification of not prioritising API security. It further provides useful suggestions to developers including adoption of security frameworks, frequent audits, and proper securing of API endpoints. Adhering to the rest of these best practices, developers will be able to reduce the level of risks connected to the functioning of APIs and consequently promote the overall security of their applications, which will enable them to satisfy the rising and expanding needs of contemporary software environments without putting users at risk.

We present a cloud-native, AI-powered Central Authorization Framework (CAF) engineered to support enterprise-scale, zero-trust API security across a Shared Services Platform (SSP) in the insurance domain. Designed on Microsoft Azure and deployed behind Azure API Management, CAF authorizes over 200 internal and clientfacing microservices using a hybrid model that combines policy-as-code (OPA) with dynamic, ML-based risk evaluation. Leveraging an ensemble of Isolation Forests, GRU Autoencoders, and XGBoost classifiers, the framework computes real-time access risk scores and applies adaptive access decisions at runtime. CAF integrates seamlessly with OAuth 2.0 and OpenID Connect, enabling decentralized identity while enforcing consistent, attribute-based access across distributed services. In a twelve-month production deployment handling 2.1 billion requests, CAF improved attack detection recall by 42 percent and precision by 18 percent compared to static RBAC and traditional WAF baselines, while maintaining sub-15 ms latency at the p95 level. The platform achieved a 60 percent reduction in security integration effort and delivered an annual benefit of 7.8 million by mitigating fraud and reducing SOC workload. This article details the architectural design, AI models, deployment approach, and

Application Programming Interfaces (APIs) have become the nervous system of modern financial-services platforms; yet fractured authorization logic remains a dominant breach vector, exposing organizations to data exfiltration, fraudulent transactions and regulatory fines. We introduce a cloud-native Contextual Authorization Framework (CAF) embedded in an enterprise Shared Services Platform (SSP) that supports more than 200 customers facing and internal micro-services worldwide. CAF sits behind Azure API Management, authenticates callers via OAuth 2.0 / OpenID Connect, and merges an ensemble machine learning risk score-Isolation Forest, GRU auto-encoder and XGBoost-with attribute-based rules expressed as policy-as-code in Open Policy Agent. A twelve-month evaluation covering 2.1 billion production requests demonstrates that CAF increases attack-detection recall by 42 % and precision by 18 % compared with a signature Web Application Firewall and static RBAC baseline, while adding only 8 ms to the p95 gateway latency-well inside the 15 ms service-level objective required for realtime quote, billing and claim APIs. Operational metrics show a 60 % reduction in security-integration effort and a net annual benefit of $7.8 million due to prevented fraud and lower SOC triage workload. We have proven datasets, Azure ML notebooks and policy templates, demonstrating that latency-bounded, AI-augmented authorization is both technically feasible and economically compelling for enterprises pursuing Zero-Trust maturity.

The progression of software testing has evolved from manual processes to automated systems. However, the emergence of Agentic AI-driven testing represents the next transformative leap. These intelligent agents autonomously generate, execute, and optimize tests, redefining the quality assurance (QA) landscape. Agentic AI-defined by its capacity to independently perceive, plan, execute, and learn-has emerged as a transformative force in software testing. This article examines the impact of Agentic AI on the software testing lifecycle, highlighting its core capabilities, such as dynamic test generation, autonomous execution, intelligent root-cause analysis, multi-modal command interpretation, and context-aware decision-making. These capabilities enable a significant shift from brittle test scripts and reactive maintenance to proactive, adaptive, and self-optimizing testing systems. We further introduce a novel architectural framework that applies Agentic AI principles to automated test scenario generation. This multi-agent system comprises a Perception Module for requirement and code understanding, a Cognitive Module for strategic planning and intelligent scenario design, and an Action Module for executing, analyzing, and learning from tests. Built on state-of-the-art technologies-including large language models (LLMs), retrieval-augmented generation (RAG), deep learning, and vector databases-our framework enables seamless integration with CI/CD pipelines, supports multi-format output generation, and incorporates continuous learning for test optimization. The proposed architecture demonstrates how Agentic AI can enhance test coverage, improve software reliability, and reduce the cost and effort of maintaining large-scale testing infrastructures. It provides an intelligent, scalable, and future-ready solution for quality assurance in fast-paced, modern development environments.

The study was conducted to design and obtain evidence concerning the software quality and acceptance of a graphical user interface (GUI) student electoral voting system. The intention of this research is three-fold; firstly, a system based on ISO 9126 software quality characteristics, secondly, a system that conforms to the current hardware and software standard and lastly, improve student participation to decision-making. Designing a usable system in the context of the user’s perception (needs) and let these perceptions dictate the design is therefore a great challenge. This study used descriptivedevelopment research method. Data were collected thru guided interviews and survey questionnaires from the respondents. The researcher adopted the Princeton Development Methodology through the entire life cycle of the software development process. A very substantial majority of the respondents stated that for them, the new voting system is highly acceptable as compared to the old system bo...

COVID19 has yielded serious consequences globally, including severe damages to the economic, social, and health sectors around the world. The ensuing global crisis has created a strong realization among states that non-traditional security (NTS) threats such as pandemics and diseases do not discriminate between territorial boundaries. Hence, they cannot be dealt with in isolation, but rather by creating a mutual ground and impetus for coordination and collaboration within the international system. This research paper outlines the revival of global health diplomacy (GHD) as grounds for reforming multilateral global governance institutions under the umbrella of ‘human security.’ In doing so, it lists out key GHD initiatives during COVID19 by both state and non-state actors, while highlighting the need for continued collaboration in the post-pandemic recovery phase. Additionally, the present study takes the case of Pakistan, a developing state with extremely fragile health and economic...

This article explores the transformative role of artificial intelligence (AI) and machine learning (ML) in strengthening financial security and combating fraud across digital platforms. As financial transactions increasingly migrate online, traditional rule-based security measures have become insufficient against sophisticated and adaptive fraud tactics. AI-driven solutions now leverage behavioral analytics, anomaly detection, and biometric authentication to build dynamic security systems that continuously evolve in response to emerging threats. This paper examines implementation strategies across major financial networks—including credit card processors, mobile banking platforms, and cryptocurrency exchanges—and highlights how machine learning algorithms, neural networks, and multi-modal biometric authentication are revolutionizing fraud detection capabilities. By evaluating current applications and outlining future challenges, including regulatory compliance and the ethical implications of automated decision-making, this work provides a comprehensive overview of how AI and ML are reshaping the landscape of financial security.

Application Programming Interfaces (APIs) have become the nervous system of modern financial-services platforms; yet fractured authorization logic remains a dominant breach vector, exposing organizations to data exfiltration, fraudulent transactions and regulatory fines. We introduce a cloud-native Contextual Authorization Framework (CAF) embedded in an enterprise Shared Services Platform (SSP) that supports more than 200 customers facing and internal micro-services worldwide. CAF sits behind Azure API Management, authenticates callers via OAuth 2.0 / OpenID Connect, and merges an ensemble machine learning risk score-Isolation Forest, GRU auto-encoder and XGBoost-with attribute-based rules expressed as policy-as-code in Open Policy Agent. A twelve-month evaluation covering 2.1 billion production requests demonstrates that CAF increases attack-detection recall by 42 % and precision by 18 % compared with a signature Web Application Firewall and static RBAC baseline, while adding only 8 ms to the p95 gateway latency-well inside the 15 ms service-level objective required for realtime quote, billing and claim APIs. Operational metrics show a 60 % reduction in security-integration effort and a net annual benefit of $7.8 million due to prevented fraud and lower SOC triage workload. We have proven datasets, Azure ML notebooks and policy templates, demonstrating that latency-bounded, AI-augmented authorization is both technically feasible and economically compelling for enterprises pursuing Zero-Trust maturity.

Certified AI Cybersecurity Analysts are not just professionals — they are the frontline architects of digital trust. Their hybrid expertise allows organizations to combat threats with unmatched intelligence and foresight. Learn more in Certified AI Cybersecurity Analyst (CAICA) Certification by Tonex.

Recent advancements in Artificial Intelligence (AI), particularly in Generative AI, have significantly impacted various domains. Innovation of models such as ChatGPT, Bard, DALL-E, Midjourney, and DeepMind has transformed academia. The widespread use of AI systems has sparked debates on how to effectively train future-relevant competencies while maintaining learning integrity. The ability of GenAI algorithms to generate specific feedback on tests, quizzes, and assessments as an instructional instrument to support student success has been a significant motivator. With current challenges of insufficient academic resources, a freeze on teacher hiring, and a shortage of practice space in developing countries, GenAI has become a handy tool to save the situation. Despite this boost, GenAI has faced major academic and ethical controversies. This study uses the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to conduct an exhaustive literature search highlighting GenAI's applications, benefits, challenges, and future prospects in the education sector. Key findings highlight the efficacy of enhancing the theoretical basis of AI in education and offer a promising avenue for educators and AI engineers to conduct collaborative research.

The global manufacturing sector is undergoing a paradigm shift toward zero-defect manufacturing (ZDM) to meet the demands of Industry 4.0, which prioritizes precision, efficiency, and sustainability. This paper presents a scalable architecture for AI-enabled computer vision (CV) systems designed to eliminate surface defects in industrial production lines. By integrating modular design principles, federated learning frameworks, and human-in-the-loop (HITL) optimization, the proposed system addresses critical challenges in scalability, data privacy, and economic feasibility. Technical innovations include hybrid CNN-Transformer models achieving 99.2% defect detection accuracy, federated learning protocols reducing data latency by 40%, and a cost-benefit model demonstrating a 22% return on investment (ROI) over five years. Validated against ISO 9001 standards, this architecture enhances supply chain resilience and positions nations competitively in advanced manufacturing.

The rapid growth in Information and Communication Technology paved the way to the development of various systems that will help Guidance Counselors with their information storage and retrieval needs. Since the birth of the World Wide Web, most transactions in the organization were implemented online for easy access and retrieval by various authorized users. The Iloilo Science and Technology University located at Burgos St. Lapaz Iloilo City is composed of five (5) branches. These include the Lapaz Campus, Leon Campus, Miag-ao Campus, Barotac Campus and Dumangas Campus. Each campus has a designated Guidance Counselors who facilitated the efficient management of guidance records. The Online Database Management of Guidance Records for Effective and Immediate Access of Data to Follow-up Students was an online system designed to be implemented to all ISAT U campuses. Since the system is online, all Guidance Counselors from all campuses can secure an account to access the system as well a...

With the exponential growth in computer storage demands, driven by current human data requirements, accommodating these needs has become a critical concern. Traditional data storage methods face numerous problems, prompting researchers to explore alternative solutions. One promising development is DNA-based data storage systems, which offer significant advantages over conventional approaches. However, the gap between electronic and biological domains in real-world applications involving general users and genetic engineers can introduce security issues. The proposed framework addresses these challenges by integrating DNA computing and cryptography, promoting the adoption of synthetic DNA as a viable data storage medium. This research proposes a homomorphic encryption approach designed to enhance security in DNA data storage, specifically targeting the issues introduced by the inter-domain knowledge gap. The methodology includes developing algorithms that enable secure data encoding and retrieval while preserving data privacy. The system empowers researchers, businesses, and general users with a versatile toolkit with multiple cryptographic functionalities. Key deliverables include user authentication, file management, encryption, decryption, steganography, DNA sequence visualization, and more. Expected outcomes include improved data security, increased efficiency in data management, and adaptability to various applications in both research and commercial settings. This paper provides a comprehensive overview of the research objectives, methodologies, deliverables, and requirements, highlighting its potential to revolutionize data security and storage paradigms.

As cybercrime evolves, so too do the methods used by malicious actors to exploit individuals and organizations. Among the most concerning innovations are Deepfake Voice Phishing (vishing) and Synthetic Identity Fraud. Both threats capitalize on artificial intelligence (AI), machine learning, and other advanced technologies, exploiting vulnerabilities in human trust and traditional security measures. Deepfake Voice Phishing (Vishing) Deepfake voice phishing, or "vishing," refers to the use of AI-generated synthetic voices that mimic real individuals to deceive victims. This attack combines social engineering with the power of deep learning algorithms to create hyper-realistic voice recordings. Attackers can use this technology to impersonate trusted individuals, such as family members, company executives, or bank representatives, to elicit sensitive inforation from victims[2]. Chart 1 : The relative ease of detecting different types of phishing attacks.

A new framework for adaptive model context protocols that improve multi-agent cooperation in dispersed environments is presented in this study. The suggested method makes use of dynamic context sharing mechanisms that adjust to task complexity, communication band-width, and computational limitations. The framework allows agents to negotiate the best parameters for information exchange by implementing a hierarchical context model with bidirectional context flow. In comparison to static approaches, the adaptive protocol lowers communication overhead while preserving task performance, as demonstrated by experimental evaluation in distributed sensor networks, autonomous vehicle coordination, and collaborative problem-solving. In order to intelligently filter information exchange, the framework presents context relevance scoring and selective propagation techniques. By providing solutions for autonomous systems functioning under fluctuating resource constraints, this research fills the gap between multi-agent collaboration and distributed systems optimization.

The integration of artificial intelligence (AI) in clinical trial management represents a transformative approach in medical research. This study examines the impact of AI on clinical trials, highlighting its ability to automate routine tasks, enhance data accuracy, and improve patient recruitment and monitoring. AI's predictive analytics, natural language processing, and real-time monitoring capabilities significantly increase efficiency, reduce costs, and improve data quality. Despite these advancements, challenges such as standardization and integration with existing systems remain. Overall, AI holds substantial promise for enhancing the effectiveness and patient-centricity of clinical trials.

The emergence of Agentic AI autonomous systems that can make and execute decisions without human intervention has presented new and complex challenges in cybersecurity. Traditional trust models and defense mechanisms are insufficient to handle these dynamic, intelligent threats. In this paper, we propose a novel Cognitive Trust Architecture (CTA) aimed at detecting, assessing, and mitigating agentic AI-driven cyber threats. We introduce an adaptive trust reasoning framework that continuously adjusts trust levels based on behavioral indicators, intent inference, and contextual analysis. Additionally, the framework incorporates autonomous adversary modeling to predict and counter potential attack strategies. By leveraging this approach, we demonstrate the efficacy of CTA in enhancing system integrity, reducing false positives in trust assessments, and improving resilience against evolving AI-driven adversaries. This work represents a significant advancement in applying cognitive trust as a proactive defense mechanism to counter intelligent, autonomous cyber threats.

Fraud detection remains an active area for research. While fraud is a difficult problem hampered by issues ranging from uncertain data to adversarial environments, new technologies and techniques from the fields of data science, machine learning, and big data bring opportunities to alleviate some of the difficulties. In this paper, fraud detection is examined in the context of financial systems for public-sector applications. Public sector financial systems face challenges with fraud detection, such as a large volume of transactions and a need for complex monitoring rules based on the context of transactions. The analysis of public sector financial systems is framed as a data-driven approach to understand the domain. Initial steps to facilitate the analysis of data within a public-sector context are taken by proposing a model framework consisting of detectors, monitors, and pattern mining techniques along with an input data requirements and output results taxonomy. The frameworks' components are investigated and elaborated on in terms of the public sector financial systems. Furthermore, future directions toward further development and evaluation of the components within the context of public sector financial systems. Fraud detection remains an active area for research. While fraud is a difficult problem hampered by issues ranging from uncertain data to adversarial environments, new technologies and techniques from the fields of data science, machine learning, and big data bring opportunities to alleviate some of the difficulties. In this paper, fraud detection is examined in the context of financial systems for public sector applications. Public sector financial systems face challenges with fraud detection, such as a large volume of transactions and a need for complex monitoring rules based on the context of transactions. The analysis of public sector financial systems is framed as a data-driven approach to understand the domain. Initial steps to facilitate the analysis of data within a public sector context are taken by proposing a model framework consisting of detectors, monitors, and pattern mining techniques, along with an input data requirements and output results taxonomy. The frameworks' components are investigated and elaborated on in terms of public sector financial systems.

In the era of cloud computing, organizations increasingly rely on cloud databases to store and manage vast volumes of sensitive information. While cloud-based solutions offer scalability, cost-efficiency, and remote accessibility, they also introduce critical security challenges. The need to protect data from unauthorized access, breaches, and cyberattacks has intensified, driving the development of advanced security mechanisms. This paper presents a comprehensive study on safeguarding cloud databases using modern encryption techniques and robust access management tools. Encryption serves as a primary line of defense by rendering data unintelligible to unauthorized users, both during transmission and while at rest. Advanced encryption standards (AES), homomorphic encryption, and end-to-end encryption methodologies are explored, along with their respective roles in preserving data confidentiality and integrity. In parallel, effective access management ensures that only authenticated and authorized users can interact with the database, minimizing insider threats and privilege abuse. Techniques such as Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC), and multi-factor authentication (MFA) are discussed as critical elements of a secure access framework. This paper also analyzes the integration of key management systems (KMS) and identity and access management (IAM) solutions within cloud ecosystems like AWS, Microsoft Azure, and Google Cloud Platform. A comparative review of existing literature highlights the strengths and limitations of current approaches and identifies gaps that warrant further exploration. The goal of this study is to provide a unified view of encryption and access control techniques as dual pillars of cloud database security. The paper concludes by suggesting directions for future enhancements, including the use of AI/ML for adaptive security, and emphasizes the importance of continuous policy updates and monitoring in a dynamic threat landscape.

Purpose -This paper examines the Internet security perception of Filipinos to establish a need and sense of urgency on the part of the government to create a culture of cybersecurity for every Filipino. Method -A quantitative survey was conducted through traditional, online and phone interviews among 252 respondents using a two-page questionnaire that covers basic demographic information and two key elements  (1) Internet usage and (2) security practices. Results -Based on findings, there is a sharp increase of Internet users for the last three years (50%) and most access the Internet through mobile (94.4%). Although at home is the most frequent location for Internet access (94.4%), a good percentage still use free WiFi access points available in malls (22.2%), restaurants (11.1%), and other public areas (38.9%) doing Internet services (email and downloading) that are vulnerable to cyber attacks. The study 15 also revealed that although respondents may have good knowledge of Internet security software, proper implementation is very limited. Conclusion -Filipinos are susceptible to cyber attacks, particularly to phishing and malware attacks. Also, majority of the respondents' Internet security perception is derivative-they practice online measure but with limited understanding of the purpose. Therefore proper education, through training and awareness, is an effective approach to remedy the situation. Recommendations -The Philippine government must now take actions and tap industries to educate Filipinos about Internet security before any negative consequences happen in the future. Research Implications -The information collected sets a clear picture on the importance of cybersecurity awareness from a regional to a global perspective.

The banking sector is increasingly leaning on advanced technologies to optimize infrastructure services, particularly through the deployment of Artificial Intelligence (AI) and machine learning methodologies. This movement is driven by the need for enhanced decision-making capabilities, improved operational efficiencies, and robust risk management strategies. Federated Learning emerges as a pivotal framework within this context, allowing institutions to collaboratively train AI models without compromising sensitive customer data. This decentralized approach not only mitigates privacy risks, but also enriches the training datasets, ultimately yielding more accurate and reliable predictive models. Such models are crucial for applications that encompass fraud detection, customer segmentation, and algorithmic trading. Furthermore, the implementation of AI governance frameworks is instrumental in navigating the ethical and regulatory complexities that accompany the integration of AI in banking. Effective governance ensures that AI systems operate transparently, with accountability mechanisms in place to address potential biases and ethical dilemmas. This is particularly important in a sector that manages vast amounts of personal and financial information. By instituting comprehensive oversight policies, banks can foster trust among stakeholders while enhancing compliance with regulatory requirements. The synergy between Federated Learning and AI governance thus not only fortifies the technological backbone of banking IT but also aligns operational practices with ethical standards and consumer protection mandates. This interplay between collaborative AI initiatives and stringent governance encapsulates the future of banking infrastructure. As institutions embrace these innovative solutions, they position themselves to harness the full potential of data-driven insights while safeguarding customer interests. Consequently, the dual focus on optimizing infrastructure services through Federated Learning and enforcing AI governance emerges as a key strategic approach within the banking landscape. This comprehensive framework is essential for navigating the complexities of a rapidly evolving financial ecosystem, ultimately facilitating sustainable growth and enhancing competitive advantage in the marketplace.

Certified AI cybersecurity specialists stand at the cutting edge of digital defense. Mastery of these technologies not only enhances their ability to combat cyber threats but also ensures their skills remain relevant in a fast-evolving industry. As cyberattacks become more sophisticated, so must the technology—and the professionals who wield it. Learn more in Certified AI Cybersecurity Specialist courses by Tonex.

The study discussed the decriminalization of attempted suicide in Nigeria, with regards to the provisions of the Mental Health Act 2021. It provides among others the conceptual, historical and theoretical understanding of the topic vis-a-vis the evolution of the Nigerian criminal legal framework on attempted suicide. It also examined the implication of the existing criminal laws on the implementation of the decriminalizing intent contained in  the provisions of  Mental Health Act 2021. The study in arriving at its findings utilized the doctrinal method by examining the findings of existing authors on the subject of attempted suicide and its decriminalization. It also, as primary sources, examined the legal framework applicable to the offence of attempted suicide, with key focus on the Mental Health Act which called for a less punitive approach.. The study at the summation of its discussions identified that attempted suicide, notwithstanding the provisions of the Mental Health Act 2021 is still substantively criminalized in Nigeria. More so, this study also finds that regardless of the Mental Health Act 2021 and its remarkable efforts towards decriminalizing attempted suicide in Nigeria, the existence of other frameworks like the Criminal Code and the Penal Code law of Northern Nigeria substantially impede its adequate implementation towards this end. This paper premised on these findings therefore advocated for the decriminalization of attempted suicide in Nigeria by proffering recommendations of workable legal and policy approaches towards improving the implementation of the Mental Health Act 2021 to this end.
Keyword:Suicide, Offence, Decriminalize, Mental health, Attempted suicide..

The study discussed the decriminalization of attempted suicide in Nigeria, with regards to the provisions of the Mental Health Act 2021. It provides among others the conceptual, historical and theoretical understanding of the topic vis-a-vis the evolution of the Nigerian criminal legal framework on attempted suicide. It also examined the implication of the existing criminal laws on the implementation of the decriminalizing intent contained in  the provisions of  Mental Health Act 2021. The study in arriving at its findings utilized the doctrinal method by examining the findings of existing authors on the subject of attempted suicide and its decriminalization. It also, as primary sources, examined the legal framework applicable to the offence of attempted suicide, with key focus on the Mental Health Act which called for a less punitive approach.. The study at the summation of its discussions identified that attempted suicide, notwithstanding the provisions of the Mental Health Act 2021 is still substantively criminalized in Nigeria. More so, this study also finds that regardless of the Mental Health Act 2021 and its remarkable efforts towards decriminalizing attempted suicide in Nigeria, the existence of other frameworks like the Criminal Code and the Penal Code law of Northern Nigeria substantially impede its adequate implementation towards this end. This paper premised on these findings therefore advocated for the decriminalization of attempted suicide in Nigeria by proffering recommendations of workable legal and policy approaches towards improving the implementation of the Mental Health Act 2021 to this end.
Keyword:Suicide, Offence, Decriminalize, Mental health, Attempted suicide.

The purpose of this study is to discuss thelegal education of euthanasia from an analytical perspective. The comparative method examined the legal gaps in the framework and psychoeducation discipline in Albania compared to international law. It is specifically focused on several issues such as the treatment of the protection of the right to life under Article 2 of the European Court of Human Rights; exploring the extent of the legal right to live and its relevant education forms; reviewing the implementation of civil law by the EU and especially in Albania and identified other international acts protecting the rights to life and their enforcement powers and conditions and circumstances of abortion and etiologies of abortion as a restriction of the law to life. We would recommend therefore the development of a draft law like the Switzerland one that has to encompass the room left by the unregulated legislation. We believe that the country must change its attitudes toward the legalization of assisted suicide and euthanasia in very specific cases and under strict regulations both in macro-level policies and in micro-level awareness especially focusing on social and legal education on the issue.

Esboço cartográfico dos tópicos essenciais para a investigação [/ pesquisa] no domínio do Direito da Cibersegurança, a serem prosseguidos no âmbito do PDPC - Centro de estudos e análise da privacidade e proteção de dados da Universidade Europeia, de Lisboa. Apresentado na Conferência "5 anos de Atividade e Futuras Linhas de Investigação do Privacy and Data Protection Centre". Lisboa, dia 30 de abril de 2025.

WCAP (Web Complete Application Protection) is an innovative cybersecurity model that introduces a unified, native, and automated approach to securing modern web applications. Unlike traditional fragmented solutions such as standalone WAFs and API firewalls, WCAP consolidates multiple protection layers including API security, DDoS mitigation, threat intelligence, Zero Trust access control, and automated incident response. This whitepaper outlines the architectural framework, core principles, and realworld use cases of WCAP, and defines implementation guidelines aligned with globally recognized standards such as OWASP, MITRE ATT&CK, NIST, and CIS Controls. WCAP aims to deliver a scalable, adaptive, and resilient security framework capable of proactively anticipating and mitigating cyber threats while reducing operational complexity and enhancing the efficiency of web application protection.

Audit manajemen sangat penting bagi perguruan tinggi selain untuk pemeriksaan dan penilaian manajemen teknologi informasi dalam proses bisnis berjalan secara efisien dan efektif. Keamanan teknologi informasi sebagai upaya pengendalian internal untuk meminimalisir resiko dan ancaman keamanan, selain itu semua kegiatan pembelajaran dan administrasi perkuliah mengunakan teknologi informasi. Untuk mencari tahu bagaimana keamanan teknologi informasi sedang berjalan, kebutuhan akan audit untuk memastikan keamanan informasi dijalankan sesuai dengan prosedur. Standar yang digunakan framework International Standarization Organization (ISO) 27001: 2005 dipilih karena framework tersebut dapat di sesuaikan dengan instrumen tempat penelitian tergantung pada kebutuhan organisasi dikembangkan dan difokuskan pada Sistem Manajemen Keamanan Informasi (SMKI). Hasil, keseluruhan penelitian JPA = PA1:PA10, NA=JPA/10 menghasilkan nilai akhir rata-rata 65%. Berarti, menunjukan level positif, namun belum s...

This paper investigates whether the presence of ambitious entrepreneurs is a more important determinant of national economic growth than entrepreneurial activity in general. We use data from the Global Entrepreneurship Monitor to test the extent to which high growth ambitions of entrepreneurs affect GDP growth for a sample of 36 countries. Our results suggest that ambitious entrepreneurship contributes more strongly to macro-economic growth than entrepreneurial activity in general. We find a particularly strong effect of high-expectation entrepreneurship for transition countries. These results are interpreted in light of the ongoing debate about public policies designed to stimulate high growth start-ups.

The increased importance of knowledge as a source of competitiveness for modern economies suggests that the organization of industries most conducive to innovative activity and unrestrained competition will be linked to higher growth rates. Entrepreneurial activity is generally assumed to be an important aspect of this organization. In the present paper we investigate whether a new and promising concept, Total Entrepreneurial Activity, influences GDP growth for 36 countries in a recent period. We will also test whether this influence depends upon the level of economic development measured as GDP per capita. With this test we aim to investigate to what extent the role of entrepreneurship has changed in the last decades of the 20 th century. Although the limited number of observations does not allow for many competing explanatory variables, we will examine the role of the so-called Growth Competitiveness Index. This variable captures a range of alternative explanations for achieving sustained economic growth. In addition, we incorporate the initial level of economic development to correct for convergence. We find that entrepreneurial activity indeed affects economic growth, but that this effect depends upon the level of per capita income. This suggests that entrepreneurship plays a different role in countries in different stages of economic development.

This paper aims at explaining cross-country variation in nascent entrepreneurship. Regression analysis is applied using various explanatory variables derived from three different approaches. We make use of the Global Entrepreneurship Monitor database, including nascent entrepreneurship rates for 36 countries in 2002 as well as variables from standardized national statistics. The first approach relates the level of entrepreneurship of a country to its level of economic development. We find evidenc e for a U-shaped relatio nship. The second approach deals with a regime switch where the innovative advantage moves from large, established enterprises to small and new firms, because new technologies have reduced the importance of scale economies in many sectors. The third approach assumes that nascent entrepreneurship depends upon aggregate conditions such as technology, demography, culture and institutions, influencing opportunities, resources, skills and preferences. Several indicators of these aggregate conditions are found to correlate with nascent entrepreneurship. A full model combining the three approaches includes a U-shaped relationship with per capita income as well as with Porter's innovative capacity index in addition to effects of social security expenditure (-) and the total business ownership rate (+). Finally, a (former) communist-country dummy plays an important role. * p< .05 ** p< .01

The increased importance of knowledge as a source of competitiveness for modern economies suggests that the organization of industries most conducive to innovative activity and unrestrained competition will be linked to higher growth rates. Entrepreneurial activity is generally assumed to be an important aspect of this organization. In the present paper we investigate whether a new and promising concept, Total Entrepreneurial Activity, influences GDP growth for 36 countries in a recent period. We will also test whether this influence depends upon the level of economic development measured as GDP per capita. With this test we aim to investigate to what extent the role of entrepreneurship has changed in the last decades of the 20 th century. Although the limited number of observations does not allow for many competing explanatory variables, we will examine the role of the so-called Growth Competitiveness Index. This variable captures a range of alternative explanations for achieving sustained economic growth. In addition, we incorporate the initial level of economic development to correct for convergence. We find that entrepreneurial activity indeed affects economic growth, but that this effect depends upon the level of per capita income. This suggests that entrepreneurship plays a different role in countries in different stages of economic development.

In the modern era of distributed systems and cloud architecture, RESTful APIs have become the essential foundation of contemporary web applications, facilitating effortless data interchange across various platforms. Despite their widespread use, APIs have become prime targets for cyberattacks, underscoring the importance of implementing robust security measures. This study concentrates on implementing HTTPS in distributed REST APIs to protect against potential threats like man-in-the-middle (MITM) attacks, data breaches, and unauthorized access, thereby providing a comprehensive data security framework. This research examines the intricacies of deploying HTTPS in distributed systems, tackling obstacles associated with certificate administration, load distribution, and API gateway integration. The proposal involves a structured system that employs TLS encryption, mutual verification, and automated certificate renewal to ensure data integrity and confidentiality, while also examining trade-offs in performance and providing suggestions to reduce latency and system load. The paper employs case studies, simulations, and security evaluations to show that regular HTTPS enforcement improves the overall security position of dispersed systems. The insights aim to provide developers, security architects, and organizations with practical approaches for constructing robust, expandable, and secure REST API systems within changing network settings.

With the increasing shift of administrative operations to online platforms by governments globally, concerns regarding cybersecurity are escalating significantly. The process of digitization expands the potential vulnerabilities to cyber threats, while simultaneously providing significant efficiencies and enhancing citizen engagement. This study investigates the challenges related to cybersecurity that government administrations encounter during their digitization efforts, focusing on data protection, infrastructure vulnerabilities, employee training, and legal ramifications. To enhance cybersecurity resilience within government operations, several recommendations are proposed following a review of case studies that highlight common vulnerabilities. This study enhances understanding of the intricacies involved in safeguarding digital assets within the public sector. The study uses a mixed methodologies approach, which includes a review of current literature, case studies of cyberattacks on government systems, and expert interviews. This investigation identifies significant risks, such as insufficient encryption standards, human factors, a lack of staff understanding, corruption, and ineffective reaction mechanisms to advanced persistent threats. The findings indicate that, while digitization has enhanced public administration operations, it has also exposed governments to increasingly sophisticated cyberattacks. The study emphasizes the necessity of implementing layered security frameworks, constant risk assessment, and personnel training programs to decrease vulnerabilities. Furthermore, the integration of artificial intelligence (AI) and blockchain technologies shows potential for improving security.

SaaS applications have transformed the business model. They are adaptable, scalable, and cost-effective. But with all these advantages, there are also security threats. Cyber-attacks increase by the day, and SaaS applications are prime targets. A single breach can lead to loss of finances, data theft, and reputation loss. Security needs to be given top priority during SaaS application development. To ensure protection from threats, there needs to be a solid security strategy in place. A DevOps methodology must be followed by a SaaS application development company to embed security into the development process, reducing risks and ensuring compliance.

The integration of data analytics, artificial intelligence (AI), and cloud computing has significantly transformed the healthcare industry, particularly in optimizing Medicaid and enhancing patient outcomes. This paper delves into the latest advancements in predictive analytics, AI-driven diagnostics, blockchain integration, and cloud-based healthcare solutions aimed at improving efficiency. Through a comprehensive literature review, this study examines the role of AI and data-driven decision-making in enhancing data quality, interoperability, and workforce training. The findings highlight emerging trends, challenges, and future directions, paving the way for continued research and innovation in healthcare technology.

The integration of Artificial Intelligence (AI), data analytics, and cloud computing in healthcare has revolutionized Medicaid services, predictive analytics, interoperability, and workforce training. This paper explores scalable AI solutions, machine learning applications, and cloud-enabled healthcare advancements. It emphasizes AIdriven predictive analytics for Electronic Health Record (EHR) management and blockchain-enabled data interoperability in Medicaid systems. The study highlights challenges in AI ethics, operational barriers, and security concerns. By leveraging AI-powered decision-making and IoT-enabled smart healthcare frameworks, Medicaid optimization enhances accessibility, cost efficiency, and population health management. Future directions in AI-driven healthcare, including robotic automation, generative AI, and real-time predictive analytics, present opportunities to further streamline Medicaid operations and improve patient outcomes.

In recent years, there have been a number of different crises such as the dotcom crisis at the end of the 1990s, the global financial crisis of 2007-2009, the pandemic economic crisis and the global economic recession of 2020, the increase in commodity prices and the rise in inflation from 2021, the outbreak of war in Ukraine, the energy and food crisis that occurred in 2022 in many countries. In addition to this, a climate crisis is also increasingly developing, which is primarily generated by the still high levels of civilisation's greenhouse gas emissions and the increasingly rapid process of global warming. As a result, the levels of various risks may be increasing and the conditions for doing business and managing an economic entity may become even more difficult in the future. As the scale and frequency of various crises increases, an increasing number of business entities and public institutions are taking various anti-crisis measures, establishing and improving risk management systems, early warning systems and contingency plans, carrying out recovery and development restructuring processes, and creating innovative solutions to adapt flexibly to changing environmental conditions. Consequently, the importance of efficient organisational management, information management and crisis management is growing. The improvement of business, information and crisis management processes has been realised in recent years through the implementation into information systems of new ICT information technologies and technologies typical of the current fourth technological revolution, Industry 4.0. Besides, within the improvement of computerised information systems, new online media are increasingly used as both a source of data and information and as a medium for the development of online marketing communication channels conducted with customers and potential consumers. The article identifies the role of the spokesperson, who communicates information to the media regarding the company's crisis situation. Recommendations are given for the reliable and professional communication of information concerning the business entity to the media.

As organizations increasingly transition their software development, deployment, and operations to the cloud, the need for robust security practices is paramount. By combining the DevOps and Security together, we can call it DevSecOps, which provides a better approach for building and maintaining the secure cloud-based systems. With the increasing of technology day by day, threats and security issues also increases day by day. In this paper, we discuss the threats and counter them by various steps. The paper underscores the importance of fostering a security-first culture, implementing a zero-trust model, and adhering to compliance and auditing requirements.

The Hostel Management System (HMS) is a webbased software application designed to streamline the management of hostels in educational institutions and other accommodation facilities. The system provides a platform for managing various aspects of hostel operations, including student registration, room allocation, maintenance and reporting. The project involved extensive research and analysis of existing systems, identification of user requirements, and questionnaires to obtain a clear picture of what the system should entail and what problems should be solved. The design and implementation of the HMS offers several benefits, including increased efficiency, transparency, accountability, and enhanced student experience. The system also provides real-time access to critical information, enabling quick decision-making by hostel administrators. The project outcomes demonstrate the effectiveness of the HMS in managing hostel operations and improving service delivery, thereby enhancing the student experience.

Encryption in transit is a critical component in safeguarding sensitive healthcare data transmitted via Software-as-a-Service (SaaS) platforms. This research paper examines the current state of encryption within SaaS, focusing specifically on mutual TLS (mTLS) as an advanced mechanism for ensuring data confidentiality and integrity. Mutual TLS extends traditional TLS by providing bidirectional authentication, thereby enhancing security in healthcare environments where the protection of electronic Protected Health Information (ePHI) is paramount. The paper outlines the architecture and handshake process of mTLS, discusses its practical implementation in healthcare SaaS applications, and highlights the inherent challenges such as certificate management, scalability, and interoperability. In addition, emerging trends—including the integration of zero-trust security models, service mesh automation, and preparations for post-quantum cryptography—are explored as methods to further strengthen data protection. Compliance considerations under regulatory frameworks like HIPAA and GDPR are analyzed, and best practices for robust encryption are proposed. Through a comparative analysis with other encryption methods and the inclusion of tabular data and a detailed flow diagram, the research demonstrates that, despite its complexity, mTLS offers a compelling balance between enhanced security and operational feasibility, making it an indispensable tool for modern healthcare SaaS providers.

In April 2016, Bandari Savings and Credit Cooperative Society lost Sh5 million through fraudulent ATM withdrawals (Nation Newspapers, April 8, 2016). These examples demonstrate weaknesses that may exist from security breaches and incidents caused by people, processes, and technology. Ministry of ICT and CAK are lacking specific Information Security Models tailored towards SACCOS in Kenya. This study therefore sought to assess the strength of existing information security policies among SACCOS in Kenya. The study adopted descriptive studies. The unit of observation was 135 SACCOS registered with SACCO Societies Regulatory Authority (SASRA) while the unit of analysis was 270 ICT personnel working in the 135 targeted SACCOS. The study targeted the SACCOS heads of IT department. The study used Nassiuma (2000) formula to get a sample size of 85 respondents. Purposive sampling was further used in selecting study participants in every SACCOS who were considered to be knowledgeable of the v...

In April 2016, Bandari Savings and Credit Cooperative Society lost Sh5 million through fraudulent ATM withdrawals (Nation Newspapers, April 8, 2016). These examples demonstrate weaknesses that may exist from security breaches and incidents caused by people, processes, and technology. Ministry of ICT and CAK are lacking specific Information Security Models tailored towards SACCOS in Kenya. This study therefore sought to assess the strength of existing information security policies among SACCOS in Kenya. The study adopted descriptive studies. The unit of observation was 135 SACCOS registered with SACCO Societies Regulatory Authority (SASRA) while the unit of analysis was 270 ICT personnel working in the 135 targeted SACCOS. The study targeted the SACCOS heads of IT department. The study used Nassiuma (2000) formula to get a sample size of 85 respondents. Purposive sampling was further used in selecting study participants in every SACCOS who were considered to be knowledgeable of the v...

Artificial intelligence will redefine the concept and operation of data security by infusing increased advanced threat detection, response, and prevention mechanisms. This paper will specifically discuss the critical role that AI-based systems play in the area of fortification of data security and also introduce innovative approaches underpinned by AI in cybersecurity. In the digitization age, connectivity and data exchange levels have touched unscaled heights, and in the process, data systems have never been so susceptible to the stroke of cyber threat. The increasing sophistication of data breaches, ransomware attacks, and other forms of attack, including sophisticated phishing schemes, makes it imperative for security measures to be similarly modern and innovative, responsive, and even predictive of quick real-time detection and response. In this respect, AI holds the promise of learning from experience. Building on this and a firm review of the current literature, this paper aims to evaluate the potential of AI to match modern security threats and the means through which it can be further integrated into the realm of cybersecurity. The study provides quantitative illustrations of cases where AI has been effectively adapted to dynamic security challenges, drastically reducing response times and improving detection accuracy. The study also presents some difficulties and limitations associated with integrating AI into cybersecurity infrastructures, ethical issues, personal data privacy, and never-ending algorithm updates. The results showed lots of promise for the achievements that AI could bring in cybersecurity by transforming the threat detection and response capability by a 30% reduction in the false positive rate. Threat identification became sure, and the false alerts were lessened. This reduced the time spent in responding to the identified threats by half, compared to traditional ways, and improved the ability of AI to process data and recognize patterns in real time. Also, AI integration has significantly reduced operational costs in the long term by automating routine tasks, thus assigning human resources to more strategic functions. However, among this multitude of benefits, the study also identifies the major challenges that need to be countered for successful implementation in AI: huge technological investment, the need for a workforce skilled in AI and data science, and data privacy and ethical issues. Transparent decisions with sufficient AI accountability are the factors that help avoid biases and maintain trust. The organizations, therefore, have strong data governance frameworks that must be developed to safeguard sensitive data, ensuring regulations around the globe. What can be gathered from this is that AI has great promise to revolutionize cybersecurity, but careful and strategic planning, ethical consideration, and ongoing monitoring are needed in the AI implementation process. In order to achieve balanced support, technological innovation and effective strategic management, by way of ethics and continuous education and training, are fundamental; these will help in utilizing the full potential of AI at work in cybersecurity. More research should focus on the long-term effects, the ethical consequences, and the interdisciplinary integration of AI into cybersecurity to benefit at the highest level while not being risky.

We propose to integrate deep learning and big data analytics to better manage cybersecurity threats that may emerge within an enterprise resource planning (ERP) ecosystem. Big data analytics on their own are insufficient for a rapidly growing threat landscape that becomes more sophisticated by the day. Deep learning can assist in analyzing complex patterns and structures in unstructured data. However, very few studies have hitherto combined these two technologies to specifically detect cybersecurity threats in an ERP environment. With this background, this analysis has two major objectives: (a) to investigate ways in which deep learning can be coupled with big data analytics to help contain cybersecurity threats in an ERP ecosystem and (b) to study the kinds of common threats, if any, that are currently present within an ERP environment. This research is unique in that it presents an exclusive and comprehensive approach to detecting cybersecurity threats that may emerge within the internal processes and activities of an ERP ecosystem, using new and advanced analytical methods. In this study, cybersecurity threats were examined using various firewalls from different organizations located all across the globe, and the common related logs were collected. A new anomaly detection approach that integrates a deep learning technique into a big data analytics setup was initialized in order to check the new attempts and their patterns. The results have shown that the approach presented has the potential to be employed to detect fraud within ERP ecosystems, as well as gather insights into common cybersecurity threats that are generally observed. In other words, the detection of security threat factors is shown to be encouraging; thus, the practical research agenda has been proposed.

Over the last few years, open-source Content Management Systems (CMS) like WordPress, Joomla, and
Drupal have powered millions of websites worldwide. Despite that, however, they have also become prime targets for cyber attacks, such as data breaches, content tampering, and unauthorized access to them. This research explores the present-day critical security challenges to such platforms, specifically regarding data protection and content integrity.
This study is performed through a comprehensive review of existing literature, real-world scenarios, and a comparative examination of security models to identify the top practices safeguarding CMS platforms. Some key findings are updating software and plugins regularly, having strong authentication mechanisms, role-based access control, and using third-party security tools. It also sheds light on tradeoffs between usability and security and gives actionable recommendations that developers, administrators, and users can use to increase the security of their CMS. These hopes
will empower open-source CMS platforms to be resilient to growing cyber threats.

Over the last few years, open-source Content Management Systems (CMS) like WordPress, Joomla, and Drupal have powered millions of websites worldwide. Despite that, however, they have also become prime targets for cyber attacks, such as data breaches, content tampering, and unauthorized access to them. This research explores the present-day critical security challenges to such platforms, specifically regarding data protection and content integrity. This study is performed through a comprehensive review of existing literature, real-world scenarios, and a comparative examination of security models to identify the top practices safeguarding CMS platforms. Some key findings are updating software and plugins regularly, having strong authentication mechanisms, role-based access control, and using third-party security tools. It also sheds light on tradeoffs between usability and security and gives actionable recommendations that developers, administrators, and users can use to increase the security of their CMS. These hopes will empower open-source CMS platforms to be resilient to growing cyber threats.