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LLM-Driven APT Detection for 6G Wireless Networks: A Systematic Review and Taxonomy
No full textSixth Generation (6G) wireless networks, which are expected to be deployed in the 2030s, have already created great excitement in academia and the private sector with their extremely high communication speed and low latency rates. However, despite the ultra-low latency, high throughput, and AI-assisted orchestration capabilities they promise, they are vulnerable to stealthy and long-term Advanced Persistent Threats (APTs). Large Language Models (LLMs) stand out as an ideal candidate to fill this gap with their high success in semantic reasoning and threat intelligence. This paper presents the first systematic review and taxonomy for LLM-assisted APT detection in 6G networks. It also provides insights by reviewing recent research on the intersection of LLMs, APTs, and 6G. Key challenges such as limitations in edge deployment, data scarcities, and explainability gaps are identified and a multidimensional taxonomy is provided in line with the APT lifecycle and 6G contexts. The paper is based on 142 studies from 2018 to 2025, searching leading databases such as IEEE Xplore, ACM Digital Library, SpringerLink, and Elsevier ScienceDirect
AIoT-Based Smart Traffic Light Management System using YOLO Object Detection and Transfer Learning
No full textEfficient traffic management is essential in urban areas having street congestions, as this has a great impact on people mobility, safety, and quality of life. In this paper, we propose a smart traffic management system leveraging artificial intelligence of things (AIoT) to enhance traffic flow. It utilizes real-time data of traffic densities at different intersections to dynamically control the timing of traffic light signals at these intersections. Live video feeds from street cameras are analyzed using the You-Only-Look-Once (YOLO) object detection algorithm combined with transfer learning to accurately count vehicles at intersections. This information is periodically uploaded to the smart city cloud, where it can be stored and analyzed further for making decisions and improving services including roads and traffic administration citywide. In this paper, we evaluate the latest two YOLO algorithms: YOL011 and YOL012. Three models per each YOLO version are used: nano (n), small (s), and medium (m). We train and validate the models on NVIDIA Tesla T4 GPU from Google Colab using the COC0128 dataset. Performance validation results show that YOL011n model is the fastest with inference time of 2.8 ms/image and speed of 357 fps, while the slowest model is YOL012m with inference time of 15.1 ms/image and speed of 66 fps. In addition, YOL011n is 1.93 times faster than YOL012n, which is similar in size. Moreover, we find that any YOL011 model in general has a mean average precision (mAP) similar to its YOL012 counterpart model and runs faster. The results also show that YOL011s and YOL012s have mAP similar to the medium-size models across Intersection-over-Union (IoU) thresholds range [0.50:0.95]. They achieve 0.84 and 0.87 mAP@[0.50:0.95], respectively, with significantly less GPU memory and computing resource requirements and much higher speeds, 2.51 times for YOL011s vs. YOL011m, and 1.78 times for YOL012s vs. YOL012m. We also do a comparison with previous related work
Secure OTA and Logging in Smart Devices via Blockchain Evaluation
No full textThe rise of Intelligent Consumer Electronics (ICE), including smart home hubs and wearable devices, requires decentralized mechanisms for secure firmware validation, access control, and tamper-resistant logging. Centralized systems remain vulnerable to spoofed updates, opaque logging practices, and limited scalability. To address these challenges, we present a blockchain-based framework that integrates hash-based firmware verification, smart contract-backed access logging, elliptic curve signatures, and TLS-secured transport. Our evaluation, conducted on constrained device profiles (1 vCPU, 512 MB RAM, 10 Mbps bandwidth), employed four platforms: Hyperledger Fabric (Raft), IOTA (Tangle), Algorand, and Ethereum (PoA). IOTA demonstrated the lowest latency (220 ms) and minimal resource consumption (42 MB RAM, 34% CPU), while Algorand achieved peak throughput (910 tx/s) with 95% consistency. Ethereum-PoA minimized storage requirements (2.8 MB per 1,000 logs), whereas Fabric exhibited higher latency (570 ms) and resource load (74 MB RAM, 51% CPU) but provided strong audit guarantees. Spoofed firmware was rejected in 100% of cases, and unauthorized logs were blocked in over 97.5% of attempts. Privacy was ensured using pseudonymous identifiers and selective logging. Adversarial dynamics such as packet loss, jamming, and consensus forking were modeled. Despite partial offloading to a gateway node, auditability and verification upheld decentralized trust. These results confirm the feasibility of blockchain-secured ICE and its resilience to both operational and adversarial threats
Troubled Waters and No Bridges: The Ecofascisms of an Imagined Global Middle Class
No full textThe article traces ecofascism in social-media commentary following a storm that affected the United Arab Emirates in April of 2024. This ecofascism is imagined by its creators as punching-up, as commentators see themselves as part of a global middle-class rejoicing at nature harming an equally imagined group of Emirati ultra-rich. Ignoring scientifically sanctioned realities of storms as products of climate change, these commentators blame cloud-seeding and techno-solutionism to cover forms of Islamophobia and ecofascism
How GenAI Transforms Computer Engineering Education: The Case of the Middle East and North Africa
No full textThis research investigates the factors influencing the adoption of GenAI in computer engineering (CE) education within the Middle East and North Africa (MENA) region. The gap in the adoption of GenAI seems to be less pronounced between northern and southern countries compared to other digital technologies. Nevertheless, the academic community has not fully explored the institutional, cultural, and geopolitical factors affecting GenAI adoption. Utilising Harold Linstone\u27s multiple perspectives theory (1981-2019), this study analyses the technical, organisational, and personal viewpoints of 50 CE educators working in higher education institutions in the MENA area. Through an abductive thematic analysis of the interviews and sentiment analysis, the research provides a comprehensive understanding of the GenAI-powered Educational Ecosystem for CE (AEECE) by detailing the essential processes, applications, outcomes, and interactions among the key stakeholders in this ecosystem, including educators, students, university administration, regulators, industry partners, and employers. From a technical standpoint, our findings indicate that GenAI is transforming CE in the region, particularly concerning coding and programming competencies for project management, content creation, and cybersecurity analytics. Other technical insights included innovative practical applications, comprehension of AI\u27s opaque aspects, and limitations in resources. From an organisational viewpoint, we identified that aligning AI investments with the national vision is crucial, as is the need for curriculum reform and addressing resource disparities among various geopolitical contexts. On a personal level, it was noted that educators stepping back from their role as learning facilitators and an excessive reliance on GenAI can undermine critical thinking skills, highlighting the importance of ethical usage and implementation of GenAI applications
Legal Pathways to Professionalizing the Procurement Workforce for Good Governance to State Contracts: A Comparative Study
No full textThis study addressed several concepts in the study’s conceptual framework, which were based on profession, professionalization, and professionalism in public procurement. It also discussed the importance of professionalizing public procurement functions and its impact on public procurement performance (Angaw, 2020). The study also aimed to analyze the most prominent global practices in raising the efficiency and capabilities of public procurement workers to reach complete professionalism in public procurement. The paper attempted to investigate the possibility of professionalism in public procurement and its effects on the good governance of state contracts. The paper relied on two basic research approaches, namely the descriptive analytical approach and the comparative approach. The study concluded that there are experiences of several distinguished countries, such as the United States of America and New Zealand, and their successes, which worked on the practical qualification of public procurement workers and their interest in reaching professionalism in this profession and created specialized academic degrees in public procurement. The main finding is that the USA and New Zealand have made great progress in professionalizing public procurement jobs, which may help Egypt as a guideline for reforming these jobs
Greening the Virtual: An Interdisciplinary Narrative Review on the Environmental Sustainability of the Metaverse
Get PDFAs the Metaverse continues to evolve as a transformative digital ecosystem, its environmental implications remain insufficiently examined within academic discourse. Despite growing interest in its technological and societal impacts, there is a lack of comprehensive evaluations that synthesize existing knowledge on its sustainability potential. This interdisciplinary narrative review addresses this gap by critically exploring how Metaverse technologies intersect with environmental sustainability across key sectors, including education, healthcare, tourism, e-commerce, manufacturing, and urban development. Employing a narrative review methodology informed by a systematic selection of scholarly and industry sources, the study consolidates current practices, emerging opportunities, and notable trade-offs. While the Metaverse presents promising avenues for reducing material consumption, optimizing urban planning through digital twins, and lowering emissions via virtual alternatives to physical travel, it also raises pressing environmental concerns, particularly related to high energy consumption, short hardware lifespans, and the rebound effects of intensified digital engagement. The findings suggest that environmental sustainability within the Metaverse is not inherent to its virtual nature but hinges on deliberate design, regulatory foresight, and the broader energy systems it depends on. This review offers timely insights for policymakers, technology developers, and sustainability advocates seeking to align immersive digital innovation with ecological responsibility and long-term planetary health
Artificial intelligence and customer-centric marketing in driving sustainable business in the digital age
No full textThis paper focuses on the role of Artificial Intelligence (AI) in revolutionizing digital marketing practices, particularly in creating customer-centric strategies that support sustainable business practices. It examines how AI tools, such as machine learning, chatbots, and data analytics, are used to personalize marketing efforts, improve customer engagement, and drive sustainable business growth. The study also analyzes the ethical considerations and challenges of using AI in digital marketing, particularly regarding data privacy and customer trust, and explores how businesses can maintain transparency while benefiting from AI technologies
Regulatory Frameworks in Science, Technology, and Medical Innovation
No full textThe convergence of science, technology, and medical (STM) innovation has transformed contemporary society, offering unprecedented benefits while introducing complex legal, ethical, and governance challenges. Regulatory frameworks serve as critical mechanisms for balancing innovation with public interest, ensuring safety, efficacy, and equity in rapidly evolving domains. This chapter explores the multifaceted regulatory landscapes that govern STM enterprises, highlighting international standards, national legislation, and sector-specific protocols. It also addresses the tension between fostering innovation and enforcing compliance, especially in areas such as biomedical research, emerging technologies, and data-driven health systems. Through comparative insights and case-driven analysis, this chapter aims to equip stakeholders with a nuanced understanding of how regulatory systems can both constrain and catalyze responsible innovation in STM fields
Counterpart of Marshall-Olkin bivariate copula with negative dependence and its neutrosophic application in meteorology
No full textCopulas are useful tools for modeling and describing different relationships between continuous random variables that have revived new interest through computational developments and extensive data analysis. This article contributes to the subject by generalizing the bivariate copula introduced recently in8 and based on the concept of the counter-monotonic shock method. The proposed copula has the feature of covering the full range of negative dependence induced by two dependence parameters, which is not so common in the specialized literature. We examine the main characteristics of this copula. In particular, the absolutely continuous and singular copula components are derived. Analytical expressions of important concordance measures, such as Spearman’s rho and Kendall’s tau, are established, along with expressions of the product moments. A real neutrosophic data set, based on the daily quality of air in the New York Metropolitan Area, is used to illustrate the applicability of the proposed copula, with quite convincing results