Explainable TabNet Transformer-based on Google Vizier Optimizer for Anomaly Intrusion Detection System

Knowledge-Based Systems, Journal Year: 2025, Volume and Issue: unknown, P. 113351 - 113351

Published: March 1, 2025

Language: Английский

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Artificial Intelligence (AI) in Cybersecurity: A Revolution in Threat Detection and Prevention

Lecture notes in networks and systems, Journal Year: 2025, Volume and Issue: unknown, P. 497 - 514

Published: Jan. 1, 2025

Language: Английский

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<i>k</i>-anonymity in Resource Allocation for Vehicle-to-Everything (V2X) Systems

Journal of Telecommunications and Information Technology, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 4

Published: Feb. 10, 2025

Sixth generation (6G) vehicle-to-everything (V2X) systems face numerous security threats, including Sybil and denial-of-service (DoS) cyber-attacks. To provide a secure exchange of data protect users' identities in 6G V2X communication systems, anonymization techniques - such as k-anonymity can be used. In this work, we study centralized vs. based resource allocation methods vehicular edge computing (VEC) network. Allocation decisions for networks are classically posed optimization task. Therefore, an information flow is transmitted from the vehicles to premises. addition decision, vehicle not required. We analyze versus k-anonymous models. show potential deterioration introduced by anonymity, quantify gap optimal goal two cases: on with aim at energy reduction. Our numerical results indicate that consumption rises 1% smaller scenarios 23% medium scenarios, whereas it decreases 14% larger scenarios.

Language: Английский

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Application of deep reinforcement learning for intrusion detection in Internet of Things: A systematic review

Internet of Things, Journal Year: 2025, Volume and Issue: unknown, P. 101531 - 101531

Published: Feb. 1, 2025

Language: Английский

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Optimized machine learning framework for cardiovascular disease diagnosis: a novel ethical perspective

BMC Cardiovascular Disorders, Journal Year: 2025, Volume and Issue: 25(1)

Published: Feb. 20, 2025

Alignment of advanced cutting-edge technologies such as Artificial Intelligence (AI) has emerged a significant driving force to achieve greater precision and timeliness in identifying cardiovascular diseases (CVDs). However, it is difficult high accuracy reliability CVD diagnostics due complex clinical data the selection modeling process useful features. Therefore, this paper studies AI-based feature techniques application AI classification. It uses methodologies Chi-square, Info Gain, Forward Selection, Backward Elimination an essence health indicators into refined eight-feature subset. This study emphasizes ethical considerations, including transparency, interpretability, bias mitigation. achieved by employing unbiased datasets, fair techniques, rigorous validation metrics ensure fairness trustworthiness diagnostic process. In addition, integration various Machine Learning (ML) models, encompassing Random Forest (RF), XGBoost, Decision Trees (DT), Logistic Regression (LR), facilitates comprehensive exploration predictive performance. Among diverse range XGBoost stands out top performer, achieving exceptional scores with 99% rate, 100% recall, F1-measure, precision. Furthermore, we venture dimensionality reduction, applying Principal Component Analysis (PCA) subset, effectively refining compact six-attribute Once again, shines model choice, yielding outstanding results. achieves accuracy, 98%, 100%, 97%, respectively, when applied subset derived from combination Chi-square Selection methods.

Language: Английский

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Intrusion detection in smart grids using artificial intelligence-based ensemble modelling

Cluster Computing, Journal Year: 2025, Volume and Issue: 28(4)

Published: Feb. 25, 2025

Language: Английский

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Robust intrusion detection based on personalized federated learning for IoT environment

Computers & Security, Journal Year: 2025, Volume and Issue: unknown, P. 104442 - 104442

Published: March 1, 2025

Language: Английский

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Secure wireless sensor networks for safe cities

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 511 - 540

Published: Jan. 1, 2025

Language: Английский

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Enhanced Depth-First Search Algorithm for Improving the Efficiency of Route Construction in Data Center Networks

Engineering Technology & Applied Science Research, Journal Year: 2025, Volume and Issue: 15(2), P. 22152 - 22158

Published: April 3, 2025

Data transmission is a critical component of data center networks, ensuring efficient and reliable transfer between nodes. Using the shortest path for common approach in as it helps minim. Nevertheless, this methodology may also give rise to some challenges, including those related network congestion heightened susceptibility node failures. In light inherent self-similarity multipath routing characteristics shown by Fat Tree topology, work proposed modified search method aimed enhance efficiency depth-first (DFS) method. The comparison made algorithm original operating on conventional architecture seen centers. findings highlight distinctive advantages DFS method, demonstrating its enhanced scalability effectiveness minimizing latency. technique consistently excels reducing energy usage under various load circumstances.

Language: Английский

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Exploring the Secure Unleashing of Digital Potential: A Study on How Cloud Security Works Together with Digital Transformation in Financial Institutions of Pakistan

Published: Jan. 1, 2025

Language: Английский

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