Security Framework Research Articles

Federated Learning-Based Authentication and Trust Scoring System for Cloud IoT Security

Abstract: A number of IoT-related security challenges are faced due to the introduction of IoT devices in almost all sections, including smart homes and industrial applications. New security solutions will be required in IoT networks to tackle issues pertaining to privacy, scalability, and efficiency with solid robustness against potential vulnerabilities. Even though some occasions these are effective centralized security frameworks suffer from significant limitations, including single points of failure, increased latency, and risks associated with data centralization [1][2]. These problems worsen as IoT networks grow in size and complexity. The below is the Federated Learning-Based Authentication and Trust Scoring System proposal toward overcoming these challenges while keeping in view the benefits offered by FL. It enables IoT devices to jointly train a global model for anomaly detection without raw data sharing [3]. This happens in a distributed manner so that data privacy is ensured, with scalability and network performance improving [4]. With this, there is a dynamic trust scoring mechanism that evaluates each device's reliability in accordance with the behavioral patterns and history of interactions [5][6]. When combining FL with the trust scoring mechanism, the proposed solution would allow an IoT network to be autonomously able to identify anomalies and manage security. This system has shown practical applicability in such experiments in both the smart home and industrial environments to enhance IoT security, retain scalability, and maintain high privacy standards [7]. The adaptability of the system coupled with federated learning makes it apt for a variety of IoT ecosystems [8]

Proactive monitoring and security in cloud infrastructure: leveraging tools like Prometheus, Grafana, and HashiCorp Vault for Robust DevOps Practices

This study investigates proactive monitoring and security within cloud infrastructure, focusing on implementing tools like Prometheus, Grafana, and HashiCorp Vault to enhance operational resilience and data security. As cloud adoption grows, so does the complexity of maintaining secure systems amidst ever-evolving threats and regulatory pressures. By integrating these tools within DevOps workflows, organizations can achieve real-time monitoring, visualization, and secure access management, significantly strengthening their cloud environments. A systematic literature review was conducted, examining each tool's unique capabilities, the limitations they address, and the potential for combined functionality to offer a layered security approach. The findings reveal that while these tools are invaluable for preemptively detecting threats and managing access, they require continuous refinement to meet scalability, compatibility, and compliance demands. This study concludes that a proactive, integrative approach utilizing Prometheus for data collection and alerting, Grafana for visualization, and HashiCorp Vault for secret management fosters robust cloud security practices. Recommended strategies include adopting zero-trust architectures, utilizing automated compliance tools, and integrating sustainability principles in cloud management to ensure both security and operational efficiency. Ultimately, this study emphasizes the need for adaptive security frameworks that evolve alongside technological advancements, positioning organizations to safeguard their digital assets and respond to emerging threats with agility and confidence.

Automation in Cloud-Based DevOps: A Guide to CI/CD Pipelines and Infrastructure as Code (IaC) with Terraform and Jenkins

This study offers a comprehensive analysis of automation in cloud-based DevOps, focusing on the role of Continuous Integration/Continuous Delivery (CI/CD) pipelines and Infrastructure as Code (IaC) in streamlining software development processes. Employing tools like Jenkins and Terraform, the research aims to demonstrate how automation can significantly enhance operational efficiency, scalability, and security in cloud deployments. Through a detailed examination of CI/CD components and their integration with IaC, this paper identifies key findings, including the reduction of manual errors, improved deployment consistency across environments, and enhanced security through DevSecOps practices. The study further explores challenges such as configuration complexity and compliance, proposing best practices like proactive monitoring, encrypted secrets management, and version control to mitigate these issues. Conclusively, the research recommends the adoption of AI-driven analytics and robust security frameworks to optimize cloud-based CI/CD automation. This work not only highlights current methodologies but also anticipates future trends, providing a strategic roadmap for organizations aiming to leverage DevOps automation effectively.

SDN-Driven Security Framework for DDOS Attack Detection and Mitigation

The rising complexity and persistence of Distributed Denial of Service (DDoS) attacks, particularly low-rate variants, present significant challenges in detection and mitigation within Software-Defined Networking (SDN) environments. Existing detection systems often flood networks with alerts, burdening security personnel and delaying timely mitigation. Furthermore, many solutions are designed and tested in simulated conditions, limiting their real-world applicability. To address these challenges, we propose an SDN-based security framework enhanced with automated monitoring, detection, and mitigation capabilities, optimized for slow-rate DDoS attacks. Our framework was rigorously evaluated on a physical testbed, achieving mitigation efficiencies between 91.66% and 100% under varied attack conditions, thus proving its robustness in practical settings. Additionally, we introduce the SDN-SlowRate-DDoS dataset, designed to assist researchers and industry professionals in developing and testing intrusion detection solutions in more realistic scenarios. To further improve DDoS defense in SDN, we incorporate an ensemble online machine learning model that dynamically adapts to evolving attack patterns, enhancing accuracy across attack types and outperforming traditional models with a detection rate of 99.2% on benchmark datasets. This dual approach leverages both real-world testing and adaptive machine learning, advancing proactive DDoS threat management in SDN environments

Enhanced Security Framework for Multi-Layered Wireless Communication Systems

The goal is to predict a Windows machine’s probability of getting infected by various families of malware, based on different properties of that machine. The telemetry data containing these properties and the machine infections was generated by combining heartbeat and threat reports collected by Microsoft’s endpoint protection solution, Windows Defender. Each row in this dataset corresponds to a ma- chine, uniquely identified by a Machine Identifier. Has Detections is the ground truth and indicates that Malware was detected on the machine. Using the information and labels in train.csv, you must predict the value for Has Detections for each machine in test.csv. The sampling methodology used to create this dataset was designed to meet certain business constraints, both in regards to user privacy as well as the time period during which the machine was running. Malware detection is inherently a time-series problem, but it is made complicated by the introduction of new machines, machines that come online and offline, machines that receive patches, machines that receive new operating systems, etc. While the dataset provided here has been roughly split by time, the complications and sampling requirements mentioned above may mean you may see imperfect agreement between your cross validation, public, and private scores! Additionally, this dataset is not representative of Microsoft customers machines in the wild it has been sampled to include a much larger proportion of malware machines

Qatar's energy policy in the field of renewable energy

Qatar has abundant oil and gas reserves and has made extensive investments in renewable energy according to the zero-carbon policy in recent years. Renewable energy is vital for Qatar, and many investments and plans have been made in this country. Therefore, this article examines Qatar's energy policy in renewable energy using a mixed quantitative-qualitative methodology. In this article, an attempt has been made to answer the question, what is Qatar's energy policy in the field of renewable energy? As a hypothesis, Qatar's energy policy has changed from dependence on non-renewable energies to using and developing renewable energies to stabilize its energy security in the coming decades. Also, the theoretical framework of energy security has been used to test the hypothesis. The research findings indicate that Qatar has also adopted this policy due to the significant changes in the orientation of developed and developing countries towards new energies. Like many Persian Gulf countries, Qatar's policies have been aimed at reducing carbon. With extensive investments and long-term planning until 2030, Qatar can become a model country in the Middle East region in terms of renewable energy. This issue and fossil fuels give Qatar a special place that can turn Qatar into a fossil and renewable energy hub.

AI-Based Phishing Detection and Automated Response: A Multi-Channel Security Framework for Modern Communication Platforms

Phishing attacks have evolved in sophistication over the changing digital communication landscape, taking advantage of several channels like social media, SMS, and email to trick people and businesses. This research offers a multi-channel security architecture for automated phishing response and detection that uses cutting-edge artificial intelligence (AI) technology to counteract this ubiquitous threat. The system utilizes automatic reaction mechanisms to mitigate threats in real time and incorporates state-of-the-art AI algorithms to improve the detection of phishing attempts across various communication channels. This study examines recent developments in artificial intelligence (AI) for cybersecurity, emphasizing the use of deep learning, machine learning, and natural language processing in phishing detection and response. It also looks at how phishing techniques have changed over time, how difficult it is to integrate AI across different platforms, and how dangerous it could be for AI systems to come under hostile attack. The report shows the usefulness and practical use of AI-driven solutions with case studies from social media, financial services, and enterprise communication platforms. It also discusses ethical and regulatory issues, highlighting the necessity of adhering to data protection regulations and using AI responsibly. The technological difficulties, potential avenues for future investigation, and prospects for innovation in AI-based phishing detection are covered in the paper's conclusion. With this methodology, cybersecurity researchers and practitioners can benefit from a thorough approach to improving cybersecurity with artificial intelligence.

An API Security Framework for IoT-Enabled Healthcare System with the Application Blockchain-Based Smart Contract

An API Security Framework for IoT-Enabled Healthcare System with the Application Blockchain-Based Smart Contract

A Cross-Layer Secure and Energy-Efficient Framework for the Internet of Things: A Comprehensive Survey

This survey delves into cross-layer energy-efficient solutions and cutting-edge security measures for Internet of Things (IoT) networks. The conventional security techniques are considered inadequate, leading to the suggestion of AI-powered intrusion detection systems and novel strategies such as blockchain integration. This research aims to promote the development of smart cities by enhancing sustainability, security, and efficiency in the industrial and agricultural sectors through the use of IoT, blockchain, AI, and new communication technologies like 5G. In this paper, we provide a comprehensive review and analysis of secure and energy-efficient cross-layer IoT frameworks based on survey of more than 100 published research articles. We highlight the significance of developing IoT security for robust and sustainable connected systems. We discuss multi-layered security approaches and ways to enhance the energy efficiency of resource-constrained devices in IoT networks. Finally, we identify open research issues and future research directions in the emerging field of cross-layer design for secure and energy-efficient IoT networks. In order to improve cybersecurity and efficiency in smart cities, the research also focuses on developing a secure, energy-efficient IoT framework integrating blockchain, artificial intelligence, and quantum-safe cryptography.

PROSPECTS FOR THE INTEGRATION OF UKRAINE'S NATIONAL SECURITY MECHANISMS WITH THE COLLECTIVE SECURITY SYSTEMS OF THE EU AND NATO

This article examines the prospects for integrating Ukraine's national security mechanisms with the collective security systems of the European Union and NATO. The study addresses the current challenges and opportunities arising from Ukraine's efforts to align its national security policy with the standards and requirements of international security organizations. The analysis underscores the significance of this integration in the context of ongoing geopolitical tensions and the necessity for enhanced cooperation in safeguarding national and regional security. Utilizing a qualitative research methodology, the article employs a comprehensive literature review, analyzing existing frameworks, policies, and strategic documents relevant to Ukraine's security landscape. Comparative analysis is also applied to assess the effectiveness of Ukraine's security initiatives against those of EU and NATO member states, identifying best practices that can be adapted to the Ukrainian context. The findings reveal critical areas of cooperation, including military interoperability, intelligence sharing, and joint training exercises, which are essential for strengthening Ukraine's defense capabilities. The article further explores the legal, institutional, and operational frameworks necessary for harmonizing Ukraine's security strategies with those of its partners, emphasizing the importance of aligning legislative measures and defense policies with EU and NATO standards. In conclusion, the article advocates for a strategic approach to integration that prioritizes resilience and adaptability within Ukraine's national security mechanisms. By enhancing collaboration with EU and NATO, Ukraine can bolster its security architecture, thereby contributing to regional stability and collective defense initiatives. The recommendations presented aim to guide policymakers in implementing effective strategies for fostering greater alignment with international security frameworks, ensuring a robust response to evolving threats in the region. Through these measures, Ukraine can not only advance its national security objectives but also play a pivotal role in the broader European security landscape.

Fortifying Application Security: Integrating OAuth2 Single Sign-On with Precision Role-Based Access Control

In today's digital era, securing applications has become paramount due to the increasing sophistication of cyber threats and the proliferation of data breaches. This paper explores how integrating OAuth2 Single Sign-On (SSO) with precision Role-Based Access Control (RBAC) can significantly enhance application security. By unifying authentication and authorization mechanisms, organizations can streamline user access while mitigating risks associated with over-privileged accounts and credential fatigue. We delve into the OAuth2 protocol architecture, dissect the core components of RBAC, and present strategies for their effective integration. Through real-world case studies and comparative analyses, we highlight the benefits, challenges, and future trends of this integration. Our findings underscore the necessity for robust security frameworks that adapt to evolving threats, emphasizing the role of OAuth2 SSO and RBAC in fortifying application security. Keywords Application Security, OAuth2, Single Sign-On, Role-Based Access Control, Authentication, Authorization, Identity Providers, JSON Web Tokens, Zero Trust Security, Adaptive Authentication, Machine Learning, Identity Management, User Experience, Credential Fatigue, Cyber Threats, Access Control

Event-Driven Data Pipelines : A Cloud-Based Approach to Real-Time Data Processing

This article comprehensively analyzes event-driven data pipelines in cloud computing environments, examining their architecture, implementation considerations, and real-world applications. The article explores the fundamental components of event-driven systems, from event sources and message brokers to processing layers, while evaluating their performance characteristics and reliability mechanisms. Through detailed analysis of system architectures, we investigate the integration of various cloud services and their role in enabling scalable, real-time data processing. The article demonstrates how modern event-driven architectures achieve sub-millisecond processing times and handle millions of events per second while maintaining system resilience. Our findings reveal significant improvements in operational efficiency across various industries, including financial services, marketing automation, and IoT monitoring solutions. The article also addresses critical implementation aspects, including security frameworks, integration protocols, and best practices for system optimization. These insights provide valuable guidance for organizations leveraging event-driven architectures in their digital transformation initiatives. The article concludes that event-driven data pipelines represent a crucial advancement in data processing technology, offering unprecedented capabilities in handling real-time data streams while maintaining scalability, reliability, and cost-effectiveness.

Contribution and challenges of integrating women into police reform in Somaliland

The purpose of the study was to investigate the obstacles faced by women within the police agency, assess their contributions, and develop appropriate recommendations aimed at enhancing the status of women and promoting their recruitment, retention, and advancement as police officers. In Somaliland, women encounter numerous barriers in the policing sector, which include organizational, personal, psychological, and social challenges that impede their representation. Somaliland declared its independence from Somalia in 1991, following the collapse of the central Somali government. Although it does not enjoy full international recognition, Somaliland has effectively established a stable government, developed functional state institutions, and conducted democratic elections. The country has focused on enhancing its security framework, with the Somaliland police being formed in 1993, playing a crucial role in upholding law and order in a context of persistent regional instability. The Somaliland Police is estimated to comprise around eight thousand personnel distributed across all six regions, with approximately 5 percent representation of women in law enforcement. This research paper adopted a descriptive methodology that utilized qualitative techniques to investigate the challenges encountered by women in law enforcement. Eight key informant interviews were carried out with police personnel, representatives from civil society organizations, officials from the Ministry of Interior, UN agencies, and members of the community. Furthermore, four focus group discussions were organized, comprising women police officers, male officers, and community members. Primary data was collected through semi-structured interviews and focus group discussions, while secondary data was obtained through a thematic literature review concerning the roles and obstacles associated with the integration of women into police reform. The research paper indicated that female police officers perform the same duties and responsibilities as their male counterparts, with the exception of patrolling and night shifts at police stations. Additionally, they are involved in specific activities concerning women's and children's issues, such as conducting physical checks of women entering public spaces, assisting female victims, investigating cases of harm against women, apprehending, and interviewing female offenders, addressing domestic violence and supporting victims of gender-based violence. The primary challenges faced by women in the police force in Somaliland include issues related to their attire, inadequate access to essential equipment and facilities, discrimination, imbalances between marriage, family, and work, limited understanding of the police system, and cultural obstacles. To mitigate these challenges, the research suggests increasing awareness of the roles and contributions of female police officers, conducting a capacity assessment for these personnel, improving their training and equipment, and creating a supportive environment for women, where government initiatives, in partnership with the stakeholders, and community can effectively address the challenges faced by women.

Architecting Secure Microservices Deployments on AWS

In the rapidly evolving digital era, microservices deployments have become indispensable for businesses aiming for enhanced scalability, flexibility, and resilience. By fragmenting applications into smaller, autonomous services, organizations can scale individual components, optimize performance with specific technology stacks, and improve fault isolation, thereby minimizing the risk of comprehensive system failures. However, ensuring robust security is of utmost importance. This article delves into key security frameworks and architectural designs employed in AWS to provide comprehensive protection for microservices deployments, safeguarding them from potential threats and vulnerabilities.

An Improved and Effective Approach for User Attention in the IoT Through the Hybrid Lightweight Security Framework (HLSF) with Data Mining

An Improved and Effective Approach for User Attention in the IoT Through the Hybrid Lightweight Security Framework (HLSF) with Data Mining

Towards the realization of socio-economic rights of children in Zimbabwe; a child sensitive policy framework

ABSTRACT With high incidences of poverty and a depressed economy as well as limited political will, it will be difficult to guarantee the socio-economic rights of children in Zimbabwe. Children struggle to get access to basic services such as health care, basic education, clean water and proper sanitation. This study critically reviews the implementation or lack thereof, of the key socio-economic rights as enunciated in the constitution and child-sensitive policies in Zimbabwe. Through document analysis, the study offers a nuanced examination of social policy implementation in the country. This paper advances the argument that poverty and inequality in Zimbabwe have worsened the lives of children who are subjected to inadequate food, lack access to proper heath facilities and proper shelter among other social amenities. Using a human security framework, the paper foregrounds the need for deliberate policies which respond to the needs of the underprivileged children. The paper concludes that a multifaceted and multi-stakeholder approach will ensure that no child is left behind as envisioned by the agenda of the sustainable development goals. It recommends that the government should implement various policies which guarantee the protection of children in need.

Space cybersecurity challenges, mitigation techniques, anticipated readiness, and future directions

Space Cybersecurity (SC) is becoming critical due to the essential role of space in global critical infrastructure – enabling communication, safe air travel, maritime trade, weather monitoring, environmental surveillance, financial services, and defence systems. Simultaneously, involving diverse stakeholders in space operations further amplifies this criticality. Similarly, previous research has identified isolated vulnerabilities in SC and proposed individual solutions to mitigate them. While such studies have provided useful insights, they do not offer a comprehensive analysis of space cyber-attack vectors and a critical evaluation of the effectiveness of mitigation strategies. This study addresses this problem by holistically examining the scope of potential space cyber-attack vectors, encompassing the ground, space, user, cloud, communication channels, and supply chain segments. Furthermore, the study evaluates the effectiveness of legacy security controls and frameworks and outlines SC-vector-aligned counterstrategies and mitigation techniques to tackle the unique SC threats. Based on the analysis, the study proposes future research directions to develop and test advanced technological solutions and regulatory and operational frameworks to establish international standards policies and foster stakeholder collaboration. The study contributes a multi-disciplinary foundation and roadmap that researchers, technology developers, and decision-makers can draw on in shaping a robust and sustainable SC framework.

A Secure and Decentralized Using Blockchain and Ring‐Based Cryptosystem

ABSTRACTThe advancement of Intelligent Transport Systems (ITSs) and the Internet of Vehicles (IoVs) introduces significant security challenges, particularly in ensuring secure communication between vehicles and vehicles (V2V), vehicles and Road Side Units (V2RSU). These vulnerabilities could potentially compromise the integrity of vehicular networks, making robust security measures essential. This paper aims to develop a secure communication framework for IoV environments that addresses these security concerns by enhancing authentication and encryption processes. The proposed approach combines the Ring‐Based Degree Truncated Polynomial Cryptosystem (RNTPC) with a Blockchain framework incorporating an enhanced proof‐of‐authentication (BEPoAuth) consensus algorithm. The approach is initiated from the registration phase and managed by a Trusted Authority (TA), ensuring secure vehicle and RSU registration. Authentication is carried out in two ways: V2V authentication through vehicle signatures and V2RSU authentication via batch verification of cluster members. Group keys are generated using RNTPC for secure communication, and blockchain technology is integrated to secure transactions within the IoV environment. The proposed methodology is evaluated using various performance metrics, demonstrating a 15%–20% improvement in throughput compared to existing techniques such as Practical Byzantine Fault Tolerance (PBFT), Secure and Highly Efficient Blockchain PBFT Consensus Algorithm (SG‐PBFT), credit‐based PBFT consensus algorithm (CPBFT) and Geographic‐PBFT (G‐PBFT). The system also exhibited minimal computational and communication latency while enhancing V2V and V2RSU communication efficiency. The RNTPC‐BEPoAuth framework offers a robust and secure solution for IoV communications, significantly outperforming existing methods in terms of throughput and efficiency. This approach provides a reliable foundation for secure ITSs, addressing critical security concerns in vehicular networks.

INTELLIGENCE GATHERING AND ITS CONTRIBUTION TO NIGERIA'S NATIONAL SECURITY: A CRITICAL ASSESSMENT

The Nigerian intelligence sector faces institutional limitations that hinder the successful implementation of intelligence collecting, which is widely acknowledged as a crucial tool in tackling these issues. This paper provides a thorough evaluation of the function of intelligence gathering within Nigeria's national security framework, analysing its effectiveness in dealing with current security challenges. This study seeks to offer a thorough examination of the intelligence cycle in the Nigerian setting, including the gathering, analysis, and use of intelligence in national security strategy. The research used a mixed-methods methodology, combining quantitative data obtained from a questionnaire with qualitative insights obtained from an empirical literature analysis. The Network Theory (TNT) functions as the conceptual framework, providing a perspective to examine the intricate connections and transmission of information within the intelligence network. Statistical analysis is conducted on the questionnaire results using descriptive and inferential methods, while the findings of the literature review are consolidated to offer context and depth. The study results highlight a significant dependence on Human Intelligence (HUMINT) and source intelligence (OSINT) in Nigeria, with a lack of implementation of Geospatial Intelligence (GEOINT) and a disregard for Measurement and Signature Intelligence (MASINT). Furthermore, the investigation exposes inadequate levels of trust and collaboration between intelligence agencies and other security organizations. The major obstacles mentioned are insufficient financial resources, insufficient training and knowledge, technical constraints, competition among different agencies, and legal and bureaucratic restrictions. The research findings indicate that although intelligence gathering is of utmost importance for Nigeria's national security, its efficacy is hindered by structural and operational obstacles. personnel growth and comprehensive strategy to improve intelligence capabilities, which involves bolstering inter- agency collaboration, allocating resources to technical progress and skilled personnel growth, and creating a strong legal and ethical structure.

Adaptive Security Paradigms: The Role of Al in Safeguarding Distributed Data Across Multi-cloud Platforms

The proliferation of multi-cloud infrastructures in modern data management strategies has introduced complex security challenges that traditional measures struggle to address effectively. This article investigates the potential of AI-powered security frameworks to enhance distributed data protection across diverse cloud environments. By leveraging advanced machine learning algorithms and predictive analytics, these frameworks offer real-time threat detection, adaptive access controls, and intelligent encryption management. The article examines the key components of AI-driven security systems, including automated anomaly detection and behavior analysis, and their integration with existing security protocols. Through a series of case studies and real-world applications, we demonstrate the efficacy of these frameworks in identifying vulnerabilities, initiating proactive security measures, and maintaining compliance with industry regulations. Our findings indicate that AI-powered security frameworks provide a scalable, adaptive, and robust solution for safeguarding distributed data assets in the dynamic landscape of multi-cloud infrastructures. However, the research also acknowledges potential limitations and ethical considerations, paving the way for future advancements in this critical area of cybersecurity.