Network Security Management in Heterogeneous Networks

Heterogeneous networks, as a critical component of modern communication technology, have experienced rapid development in recent years. The emergence of technologies like 5G, the Internet of Things (IoT), and edge computing has significantly enhanced the diversity and complexity of heterogeneous net...

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Publié: MDPI - Multidisciplinary Digital Publishing Institute 2025
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collection Directory of Open Access Books
description Heterogeneous networks, as a critical component of modern communication technology, have experienced rapid development in recent years. The emergence of technologies like 5G, the Internet of Things (IoT), and edge computing has significantly enhanced the diversity and complexity of heterogeneous networks, making them pivotal for diverse application demands. However, the openness and diverse characteristics of heterogeneous networks expose them to serious security challenges. Such networks are vulnerable to attacks like Distributed Denial-of-Service (DDoS) attacks, malware propagation, and jamming attacks, posing significant risks to system stability and data privacy. To address these pressing security challenges, researchers have developed a variety of defense strategies aimed at mitigating risks in heterogeneous networks. Compared to traditional approaches, these strategies exhibit several distinct advantages, such as the ability to efficiently handle large amounts of data while ensuring data security, flexibility in tackling various security challenges, and resilience against advanced and persistent cyberattacks. These approaches provide significant theoretical and practical support for improving the security of heterogeneous networks.
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publisherStr MDPI - Multidisciplinary Digital Publishing Institute
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spelling doab-20.500.12854ir-1651702025-08-12T08:08:40Z Network Security Management in Heterogeneous Networks Zhang, Tao Tang, Xiangyun Wang, Jiacheng Liu, Jiqiang scrap steel detection federated learning data heterogeneity network security networks community detection structure entropy community structure information modularity large language models efficient inference offloading mixture-of-experts Internet of Medical Things IoV differential privacy P2P secure forecasting nationwide industry PM2.5 heterogeneous network LLM edge computing security risks of data leakage multi-objective optimization multipath transmission privacy protection security reliability task offloading deep reinforcement learning mobile edge computing multimodal learning intelligent connected vehicle Byzantine-robust federated learning low-light image enhancement Retinex theory attention mechanism unsupervised learning electricity market operators secure energy trading Stackelberg game pruning techniques drug repositioning prototype subcategory exploration graph neural network electric vehicles mobile charging stations charger sharing blockchain Graph Convolutional Network entity relation extraction Deepfake detection face swapping proactive forensics robust watermarking image hashing pseudo-Zernike transform n/a clustered federated learning principal component analysis thema EDItEUR::A The Arts::AT Performing arts::ATF Films, cinema thema EDItEUR::A The Arts::AT Performing arts::ATJ Television Heterogeneous networks, as a critical component of modern communication technology, have experienced rapid development in recent years. The emergence of technologies like 5G, the Internet of Things (IoT), and edge computing has significantly enhanced the diversity and complexity of heterogeneous networks, making them pivotal for diverse application demands. However, the openness and diverse characteristics of heterogeneous networks expose them to serious security challenges. Such networks are vulnerable to attacks like Distributed Denial-of-Service (DDoS) attacks, malware propagation, and jamming attacks, posing significant risks to system stability and data privacy. To address these pressing security challenges, researchers have developed a variety of defense strategies aimed at mitigating risks in heterogeneous networks. Compared to traditional approaches, these strategies exhibit several distinct advantages, such as the ability to efficiently handle large amounts of data while ensuring data security, flexibility in tackling various security challenges, and resilience against advanced and persistent cyberattacks. These approaches provide significant theoretical and practical support for improving the security of heterogeneous networks. 2025-08-12T08:08:37Z 2025-08-12T08:08:37Z 2025 book ONIX_20250812T095121_9783725833184_119 9783725833184 9783725833177 https://directory.doabooks.org/handle/20.500.12854/165170 eng image/jpeg Attribution 4.0 International https://mdpi.com/books https://mdpi.com/books/pdfview/book/10573 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-3317-7 10.3390/books978-3-7258-3317-7 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725833184 9783725833177 254 open access
spellingShingle scrap steel detection
federated learning
data heterogeneity
network security
networks
community detection
structure entropy
community structure information
modularity
large language models
efficient inference offloading
mixture-of-experts
Internet of Medical Things
IoV
differential privacy
P2P
secure forecasting nationwide industry PM2.5
heterogeneous network
LLM
edge computing
security risks of data leakage
multi-objective optimization
multipath transmission
privacy protection
security
reliability
task offloading
deep reinforcement learning
mobile edge computing
multimodal learning
intelligent connected vehicle
Byzantine-robust federated learning
low-light image enhancement
Retinex theory
attention mechanism
unsupervised learning
electricity market operators
secure energy trading
Stackelberg game
pruning techniques
drug repositioning
prototype
subcategory exploration
graph neural network
electric vehicles
mobile charging stations
charger sharing
blockchain
Graph Convolutional Network
entity relation extraction
Deepfake detection
face swapping
proactive forensics
robust watermarking
image hashing
pseudo-Zernike transform
n/a
clustered federated learning
principal component analysis
thema EDItEUR::A The Arts::AT Performing arts::ATF Films, cinema
thema EDItEUR::A The Arts::AT Performing arts::ATJ Television
Network Security Management in Heterogeneous Networks
title Network Security Management in Heterogeneous Networks
title_full Network Security Management in Heterogeneous Networks
title_fullStr Network Security Management in Heterogeneous Networks
title_full_unstemmed Network Security Management in Heterogeneous Networks
title_short Network Security Management in Heterogeneous Networks
title_sort network security management in heterogeneous networks
topic scrap steel detection
federated learning
data heterogeneity
network security
networks
community detection
structure entropy
community structure information
modularity
large language models
efficient inference offloading
mixture-of-experts
Internet of Medical Things
IoV
differential privacy
P2P
secure forecasting nationwide industry PM2.5
heterogeneous network
LLM
edge computing
security risks of data leakage
multi-objective optimization
multipath transmission
privacy protection
security
reliability
task offloading
deep reinforcement learning
mobile edge computing
multimodal learning
intelligent connected vehicle
Byzantine-robust federated learning
low-light image enhancement
Retinex theory
attention mechanism
unsupervised learning
electricity market operators
secure energy trading
Stackelberg game
pruning techniques
drug repositioning
prototype
subcategory exploration
graph neural network
electric vehicles
mobile charging stations
charger sharing
blockchain
Graph Convolutional Network
entity relation extraction
Deepfake detection
face swapping
proactive forensics
robust watermarking
image hashing
pseudo-Zernike transform
n/a
clustered federated learning
principal component analysis
thema EDItEUR::A The Arts::AT Performing arts::ATF Films, cinema
thema EDItEUR::A The Arts::AT Performing arts::ATJ Television
topic_facet scrap steel detection
federated learning
data heterogeneity
network security
networks
community detection
structure entropy
community structure information
modularity
large language models
efficient inference offloading
mixture-of-experts
Internet of Medical Things
IoV
differential privacy
P2P
secure forecasting nationwide industry PM2.5
heterogeneous network
LLM
edge computing
security risks of data leakage
multi-objective optimization
multipath transmission
privacy protection
security
reliability
task offloading
deep reinforcement learning
mobile edge computing
multimodal learning
intelligent connected vehicle
Byzantine-robust federated learning
low-light image enhancement
Retinex theory
attention mechanism
unsupervised learning
electricity market operators
secure energy trading
Stackelberg game
pruning techniques
drug repositioning
prototype
subcategory exploration
graph neural network
electric vehicles
mobile charging stations
charger sharing
blockchain
Graph Convolutional Network
entity relation extraction
Deepfake detection
face swapping
proactive forensics
robust watermarking
image hashing
pseudo-Zernike transform
n/a
clustered federated learning
principal component analysis
thema EDItEUR::A The Arts::AT Performing arts::ATF Films, cinema
thema EDItEUR::A The Arts::AT Performing arts::ATJ Television
url ONIX_20250812T095121_9783725833184_119