A survey on state-of-the-art experimental simulations for privacy-preserving federated learning in intelligent networking

Electronic Research Archive, Год журнала: 2024, Номер 32(2), С. 1333 - 1364

Опубликована: Янв. 1, 2024

<abstract> <p>Federated learning (FL) provides a collaborative framework that enables intelligent networking devices to train shared model without the need share local data. FL has been applied in communication networks, which offers dual advantage of preserving user privacy and reducing overhead. Networking systems are highly complementary. environments provide critical support for data acquisition, edge computing capabilities, round communication/connectivity, scalable topologies. In turn, can leverage capabilities achieve adaptation, low-latency operation, intelligence, personalization, and, notably, preservation. our review, we gather relevant literature open-source platforms point out feasibility conducting experiments at confluence networking. Our review is structured around key sections, including introduction concepts, background networking, experimental simulations covering Additionally, delved into case studies showcasing potential optimizing state-of-the-art network optimization objectives, such as performance, quality service, energy, cost. We also addressed challenges outlined future research directions valuable guidance researchers practitioners this trending field.</p> </abstract>

Язык: Английский

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Federated Learning on Internet of Things: Extensive and Systematic Review

Computers, materials & continua/Computers, materials & continua (Print), Год журнала: 2024, Номер 79(2), С. 1795 - 1834

Опубликована: Янв. 1, 2024

The proliferation of IoT devices requires innovative approaches to gaining insights while preserving privacy and resources amid unprecedented data generation.However, FL development for is still in its infancy needs be explored various areas understand the key challenges deployment real-world scenarios.The paper systematically reviewed available literature using PRISMA guiding principle.The study aims provide a detailed overview increasing use networks, including architecture challenges.A systematic review approach used collect, categorize analyze FL-IoT-based articles.A search was performed IEEE, Elsevier, Arxiv, ACM, WOS databases 92 articles were finally examined.Inclusion measures published English with keywords "FL" "IoT".The methodology begins an recent advances IoT, followed by discussion how these two technologies can integrated.To more specific, we examine evaluate capabilities talking about communication protocols, frameworks architecture.We then present comprehensive analysis number applications, smart healthcare, transportation, cities, industry, finance, agriculture.The findings from this services applications are also presented.Finally, comparative IID (independent identical data) non-ID, traditional centralized deep learning (DL) approaches.We concluded that has better performance, especially terms protection resource utilization.FL excellent because model training takes place on individual or edge nodes, eliminating need aggregation, which poses significant risks.To facilitate rapidly evolving field, presented intended help practitioners researchers navigate complex terrain IoT.

Язык: Английский

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PPAM-mIoMT: a privacy-preserving authentication with device verification for securing healthcare systems in 5G networks

International Journal of Information Security, Год журнала: 2023, Номер 23(1), С. 679 - 698

Опубликована: Окт. 9, 2023

Язык: Английский

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Computer vision-based six layered ConvNeural network to recognize sign language for both numeral and alphabet signs

Biomimetic Intelligence and Robotics, Год журнала: 2023, Номер 4(1), С. 100141 - 100141

Опубликована: Дек. 9, 2023

People who have trouble communicating verbally are often dependent on sign language, which can be difficult for most people to understand, making interaction with them a endeavour. The Sign Language Recognition (SLR) system takes an input expression from hearing or speaking-impaired person and outputs it in the form of text voice normal person. existing study related has some drawbacks, such as lack large datasets range backgrounds, skin tones, ages. This research efficiently focuses overcome previous limitations. Most importantly, we use our proposed Convolutional Neural Network (CNN) model, "ConvNeural", order train dataset. Additionally, develop own datasets, "BdSL_OPSA22_STATIC1" "BdSL_OPSA22_STATIC2", both ambiguous backgrounds. "BdSL_OPSA22_STATIC2" include images Bangla characters numerals, total 24,615 8437 images, respectively. "ConvNeural" model outperforms pre-trained models accuracy 98.38% 92.78% "BdSL_OPSA22_STATIC2". For dataset, get precision, recall, F1-score, sensitivity specificity 96%, 95%, 99.31% , 95.78% Moreover, case achieve 90%, 88%, 100%, 100%

Язык: Английский

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Perspectives, Applications, Challenges, and Future Trends of IoT-Based Logistics

Advances in information security, privacy, and ethics book series, Год журнала: 2024, Номер unknown, С. 148 - 171

Опубликована: Фев. 2, 2024

The emergence of the internet things (IoT) has revolutionized many sectors economy, including logistics and supply chain management. By seamlessly integrating IoT into operations, real-time tracking monitoring shipments becomes a reality, optimizing routes equipment performance breeze. Accordingly, operations have become streamlined like never before. This study delves various perspectives, applications, challenges deploying in industry, offering comprehensive overview for stakeholders, researchers, students alike. With potential improved efficiency, effectiveness, sustainability, benefits are undeniable. authors highlight future directions this exciting field learn how shapes we do business.

Язык: Английский

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