AWE-DPFL: Adaptive weighting and dynamic privacy budget federated learning for heterogeneous data in IoT

Computers & Electrical Engineering, Journal Year: 2025, Volume and Issue: 123, P. 110070 - 110070

Published: Jan. 22, 2025

Language: Английский

---

Security of federated learning in 6G era: A review on conceptual techniques and software platforms used for research and analysis

Computer Networks, Journal Year: 2024, Volume and Issue: 245, P. 110358 - 110358

Published: March 30, 2024

Language: Английский

---

Quantum social network analysis: Methodology, implementation, challenges, and future directions

Information Fusion, Journal Year: 2024, Volume and Issue: unknown, P. 102808 - 102808

Published: Nov. 1, 2024

Language: Английский

---

Machine Learning and Robotics in Urban Traffic Flow Optimization With Graph Neural Networks and Reinforcement Learning

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 83 - 104

Published: Feb. 27, 2025

Increased congestion, inefficiency, and accidents in cities are major issues for urban traffic systems. However, rapid urbanization increasing numbers of cars exacerbate problems that have created an environment too dynamic sophisticated traditional solutions like static signals or road expansion. The chapter discusses the use machine learning robotics with graph neural networks reinforcement optimizing flow. Traffic pose intricate relationships GNNs model under form nodes edges representing roads, intersections, vehicles. RL allows continuous real-time interaction through which autonomous agents learn optimal strategies; thus, better decision-making takes place conditions system can proactively adjust signal timings, reroute vehicles, manage congestion. Integration these technologies will indeed be transformative to management; hence, more effective, flexible, safest transportation systems expected future.

Language: Английский

---

Chained continuous quantum federated learning framework

Future Generation Computer Systems, Journal Year: 2025, Volume and Issue: unknown, P. 107800 - 107800

Published: March 1, 2025

Language: Английский

---

Federated Learning in Chemical Engineering: A Tutorial on a Framework for Privacy-Preserving Collaboration across Distributed Data Sources

Industrial & Engineering Chemistry Research, Journal Year: 2025, Volume and Issue: unknown

Published: March 27, 2025

Language: Английский

---

Enhancing Autonomous Vehicle Security: Federated Learning for Detecting GPS Spoofing Attack

Transactions on Emerging Telecommunications Technologies, Journal Year: 2025, Volume and Issue: 36(4)

Published: April 1, 2025

ABSTRACT Autonomous vehicles (AVs) are poised to transform modern transportation, providing superior traffic management and improved user experiences. However, there exists a considerable risk the acquisition of Position, Velocity Time (PVT) in AVs, since PVT is vulnerable Global Positioning System (GPS) spoofing attacks that could redirect AV wrong paths or lead security threats. To address these issues, we propose novel approach for detecting GPS AVs using Federated Learning (FL) with trajectories obtained from Car Act (CARLA) simulator. Each vehicle autonomously performs localization sensor data includes yaw rate, steering angle, as well wheel speed. The localized coordinates (authentic spoofed) utilized compute weights. These weights aggregated at Roadside Unit (RSU) shared global model utilizing Support Vector Machines (SVM) classification. updates local models through FL, ensuring privacy collaborative learning. experimental results show proposed achieves 99% accuracy, 98% F1 score, AUC‐ROC outperforming traditional machine learning methods including K‐Nearest Neighbors (KNN) Random Forest (RF). demonstrate practicality FL improve against limited sharing, thereby offering potential real‐world applications.

Language: Английский

---

Advanced SDN-based network security: an ensemble optimized deep learning-based framework for mitigating DDoS attacks with intrusion detection

Cluster Computing, Journal Year: 2025, Volume and Issue: 28(5)

Published: April 28, 2025

Language: Английский

---

Securing data and preserving privacy in cloud IoT-based technologies an analysis of assessing threats and developing effective safeguard

Artificial Intelligence Review, Journal Year: 2024, Volume and Issue: 57(10)

Published: Aug. 27, 2024

The Internet of Things (IoT) is a powerful technology adopted in various industries. Applications the IoT aim to enhance automation, productivity, and user comfort cloud distributive computing environment. Cloud automatically stores analyzes large amounts data generated by IoT-based applications. has become crucial component information age through easier administration storage. Currently, government agencies, commercial enterprises, end users are rapidly migrating their environments. This may require end-user authentication, greater safety, recovery event an attack. A few issues were discovered authors after analysis assessments aspects published research papers. reveals that existing methods need be further improved address contemporary dangers related security privacy. Based on reports, it can stated safe end-to-end transmission cloud-IoT environment requires modifications advancements design reliable protocols. Upcoming technologies like blockchain, machine learning, fog, edge mitigate over some level. study provides thorough threats including categorization, potential countermeasures safeguard our data. Additionally, have summarized cutting-edge approaches learning blockchain being used privacy areas. Further, this paper discusses problems today's world possible future directions.

Language: Английский

---

Secure IoT firmware updates against supply chain attacks

The Journal of Supercomputing, Journal Year: 2025, Volume and Issue: 81(5)

Published: April 4, 2025

Language: Английский

---