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13 articles for “privacy preservation”
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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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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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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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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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Blockchain-Enabled Secure Data Sharing in Mobile IoT Networks
Abstract: The rapid proliferation of mobile Internet of Things (IoT) devices has resulted in an exponential increase in data generation, storage, and sharing, which poses significant challenges related to security, privacy, integrity, and trustworthiness. Traditional centralized architectures for IoT data exchange are inherently vulnerable to single points of failure, unauthorized access, data tampering, and limitations in scalability. Blockchain technology, with its decentralized ledger structure, cryptographic integrity, and consensus mechanisms, provides a …
Published in International Journal of Mobile Computing Technology · Vol. 4, Issue 1, 2026 · pp. 38–44 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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Differential Privacy-Aware Data Sanitization for Multi-Level Security
Abstract: Multi-level security (MLS) models are fundamental for enforcing mandatory access control in high-security environments such as government, military, healthcare, and finance. However, traditional MLS frameworks, including the Bell-LaPadula and Biba models, often create rigid data silos, preventing efficient data utilization. Differential privacy (DP) presents a novel solution by enabling controlled information leakage while preserving confidentiality. By injecting statistical noise into query results, DP allows lower-clearance users to access sanitized versions …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 1, 2025 · pp. 42–52 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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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 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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IoT Security: Issues, Best Practices, and Open Challenges
Abstract: The internet of things (IoT) provides the facility to connect different devices and communicate and share information over the internet. IoT has emerged as a transformative and pervasive technological paradigm, revolutionizing how we interact with our environment and infusing intelligence into everyday objects and devices. This interconnected ecosystem has unleashed a wave of innovative applications across diverse domains, including healthcare, transportation, agriculture, industrial automation, and smart cities. However, as the …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 7–13 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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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