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17 articles for “Privacy-preserving AI”
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A Framework for Privacy-preserving AI Models in Cloud Computing: Challenges and Solutions
Abstract: The growing adoption of cloud computing for deploying artificial intelligence (AI) models has led to significant advancements in sectors such as healthcare, finance, and e-commerce. However, the integration of AI with cloud computing raises critical privacy concerns, particularly when handling sensitive data. This paper presents a comprehensive framework for implementing privacy-preserving AI models in cloud environments, addressing the unique challenges, and proposing effective solutions. The suggested framework employs advanced privacy-preserving …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 1–12 Read article
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Ethical and Responsible AI: A Comprehensive Review of Principles, Methods, and Tools
Abstract: Quick development of artificial intelligence (AI) has revolutionized a number of industries, including healthcare, banking, and government, by providing creative answers to challenging issues. However, there are serious ethical issues with growing integration of AI into crucial decision-making processes, including prejudice, a lack of transparency, abuses of data privacy, and accountability gaps. A systematic strategy that incorporates technical solutions, legal frameworks, and ethical standards is needed to address these issues. …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 1, 2026 · pp. 23–34 Read article
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Real-Time Browser-Based Early Warning System for Cyberbullying Detection in Online Platforms
Abstract: The rise in social networking through internet-based communication tools, Instagram, and YouTube, to name a few, significantly increases the risk of cyberbullying, thereby increasing psychological trauma on users, especially children, through adverse emotional states like anxiety, depression, etc. For a long time, researchers have been enhancing detection tools to counter cyberbullying, but their ability to detect only after the fact, along with limited support for English-based architecture, is a major …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 09–15 Read article
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Overview AI-Driven Antenna Technologies and Privacy- Preserving Methods for Next-Generation 6G Wireless Systems
Abstract: The next generation of wireless communications, 6G, will be built on the convergence of artificial intelligence (AI) and advanced antenna systems. AI-driven antennas are poised to address the unprecedented requirements for data rate, reliability, adaptability, and ubiquity in future networks. An overview of current advancements in AI-enabled antenna systems for 6G networks is provided in this study. From traditional base station deployments to distributed, cell-free, and user-centric frameworks, it examines …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 28–34 Read article
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A Review of Machine Learning Applications in Web Data Mining
Abstract: The rapid development of Internet technology has resulted in a rapidly changing and intricate digital environment that requires new methods for organizing and evaluating online data. This study examines the use of machine learning (ML) in web data mining, focusing on its ability to extract relevant insights from huge amounts of online data. Web data mining, which is divided into three categories: content mining, structure mining, and use mining, uses …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 39–47 Read article
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A Comprehensive Review on IoT and Edge Computing in Electronics: Trends, Challenges, and Future Directions
Abstract: The Internet of Things (IoT) transformed the electronics industry by enabling ubiquitous connectivity between billions of devices. This has created an unprecedented amount of data, challenging traditional cloud-based architectures with latency, bandwidth, and security issues. Edge computing came as an additive architecture by distributing computation and bringing intelligence to IoT edges to provide real-time responsiveness and reduce dependence on centralized infrastructure. This study offers a thorough analysis of current developments …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 1, 2026 · pp. 1–9 Read article
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A Comprehensive Review of Digital Transformation in Healthcare: Addressing Privacy, Security, and Usability Challenges in Electronic Health Records
Abstract: The healthcare industry’s shift toward digitalization through electronic health records (EHRs) and advanced health information technology (HIT) promises improved patient care but brings forth challenges in safeguarding patient data privacy, confidentiality, and security (PCS). Researchers are exploring innovative solutions like block chain and cryptography to address these concerns while ensuring usability for healthcare professionals. Additionally, the impact of regulatory frameworks on data sharing and security is being studied, emphasizing the …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 · pp. 9–14 Read article
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Emotionally Intelligent AI: The Future of Mental Health Care and Emotional Well-being
Abstract: With the potential to improve emotional well-being through sophisticated AI systems, emotionally intelligent AI (EI-AI) represents a revolutionary frontier in mental health treatment. EI-AI can recognize, understand, and react to human emotions in real- time by utilizing recent advancements in machine learning, natural language processing, and emotion detection. These features are being used more and more in mental health settings, where chatbots and other AI-driven interventions help with emotional regulation, …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 17–21 Read article
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Facial Emotion Detection and Its Applications
Abstract: Facial emotion detection (FED) is an interdisciplinary field that integrates artificial intelligence, computer vision, and machine learning to recognize and interpret human emotions based on facial expressions. The development of FED systems has been propelled by advancements in deep learning, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which enhance recognition accuracy. Feature extraction techniques, including geometric and appearance-based methods, play a crucial role in classifying emotional states. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 8–12 Read article
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Advanced Private Cloud Security and Privacy Preservation Through the Integration of Machine Learning and Cryptography
Abstract: In modern technological landscapes, private cloud security is of paramount concern due to the ever-increasing volume and complexity of cyber threats. This research work explores the integration of machine learning and cryptography to enhance security within private cloud environments. This study aims to mitigate vulnerabilities that may compromise data integrity, confidentiality, and availability in private cloud infrastructures by using machine learning algorithms and strong cryptography. By detecting anomalous cloud patterns …
Published in International Journal of Advanced Control and System Engineering · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article
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Multi-Layered AI-Driven Security in Wireless Ecosystems
Abstract: The proliferation of next-generation wireless technologies, from 5G/6G networks to the pervasive Internet of Things (IoT), has birthed a hyperconnected digital ecosystem of unprecedented scale and dynamism. This interconnectedness, however, introduces a vast and volatile attack surface, rendering conventional, signature-based security paradigms fundamentally obsolete. This paper posits that the only viable defense is an offensive, self-adaptive one, predicated on the integration of artificial intelligence (AI) directly into the wireless security …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 21–28 Read article
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Federated Learning: A Comprehensive Review of Models, Algorithms, and Business Applications
Abstract: In an age where data privacy is a significant concern, federated learning (FL) has become a game-changing method in machine learning. This decentralized model enables various parties to work together on training models without exchanging their raw data, effectively tackling the issues posed by data silos and privacy regulations. This article explores the current state of FL, including its underlying models and algorithms, practical applications, benefits, challenges, and future directions. …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 1–9 Read article
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Ensuring Data Traceability Across Multiple Cloud Environments
Abstract: This study investigates the challenges and solutions for ensuring data traceability across multiple cloud environments. With organizations' increasing reliance on cloud infrastructure, maintaining data traceability is crucial for compliance, data integrity, and secure data management. The diversity of cloud systems, spanning public, private, and hybrid models, introduces complexities in tracking data lineage, access, and movement. This study delves into multi-cloud strategies' technical and operational hurdles, such as varying data formats, …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 08–22 Read article
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Machine Learning-Based Approach for Heart Disease Prediction
Abstract: Heart disease is a significant global health challenge, with early diagnosis and prediction being essential for reducing mortality rates. Machine Learning (ML), an efficiently developing field within Artificial Intelligence, provides innovative methods for analyzing complex clinical data to predict heart disease. This review examines the basic machine learning techniques, data, and metrics used in cardiovascular disease prediction. It explores the role of supervised learning, such as decision trees and logistic …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 64–73 Read article
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A Secured Architecture of Internet of Things (IoT) in the 5G Age
Abstract: Internet of things (IoT) is a technology capable of connecting vast number of devices of many types worldwide via the internet using unique IP addresses. The connected devices can communicate ubiquitously anywhere, anytime for any given user. Such globally distributed networks require a high level of connectivity among its components like smart sensors, workstations as well as networking devices. Thankfully, with the aid of the recently emerged 5G technology, which …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 1, 2025 · pp. 33–43 Read article
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Pharmacy Teachers' Contribution to Preserving Education's Integrity and Quality in the AI Era
Abstract: Artificial Intelligence through its modern approach supports the development of pharmacy education through customized methods and automatic evaluation systems and computerized training exercises. Students benefit from AI tools which include intelligent tutoring systems together with virtual assistants and simulation platforms because these tools improve their knowledge of pharmacology and drug formulation as well as clinical practice. The transition to AI-controlled education creates new academic integrity issues and ethical problems and …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 20–42 Read article
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Cloud-based Application Development and Optimization
Abstract: As cloud computing powers today’s applications, optimizing cloud-based development is crucial to achieve performance, cost effectiveness, and scalability. This research focuses on enhancing the design, deployment, and maintenance of cloud applications, tackling challenges in resource management, scalability, and resilience. We specifically explore dynamic resource allocation algorithms that use predictive analytics for auto-scaling based on workload variations, aiming to cut costs while preserving high performance. The study also investigates cross-cloud optimization …
Published in Journal of Open Source Developments · Vol. 12, Issue 1, 2025 · pp. 37–42 Read article