Statistical slice-level analysis for online detection of distributed denial-of-service (DDoS) attacks in network slicing environments DOI
Suadad S. Mahdi,

Alharith A. Abdullah

Journal of High Speed Networks, Journal Year: 2024, Volume and Issue: 31(2), P. 145 - 158

Published: Dec. 26, 2024

Network slicing (NS) is a technique that enables network operators to create multiple virtual networks, each customized for specific clients, services, or applications, while still utilizing shared physical infrastructure. Although this approach provides benefits in terms of resource usage and flexibility, it also introduces new security risks, particularly the form DDoS attacks. These attacks can be targeted at slices, causing disruptions services provided by those which may impact clients applications rely on services. To mitigate risks posed NS, paper proposes an intrusion detection system designed safeguard slices from The proposed relies statistical methods use joint entropy dynamic thresholds analyze traffic real time. Based findings testbed conducted exhibited remarkable level effectiveness identifying directed targeting slice. rate was recorded 99%, delay extremely low 0.32 s. results imply recognize respond swiftly, aid swiftly mitigating potential threats.

Language: Английский

Driving Next Generation IoT with 5G and Beyond DOI

Shishir Shrivastava,

Ankita Rana,

Ashu Taneja

et al.

Published: Jan. 3, 2025

This chapter gives a detailed account of how fifth generation (5G) technology can transform the world. In order to provide an unconceivable data speed, ultra-low latency and possibility handle billions connections, 5G is considered be more advanced than its predecessor fourth (4G) technology. highlights potential in driving next internet things (IoT) ecosystem. The technologies including multiple-input-multiple-output (MIMO), massive MIMO, small cells, millimeter wave (mmWave) visible light communication (VLC) are discussed emphasising their role revolutionizing diverse IoT application areas. comparison with existing wireless such as Wi-Fi, long range (LoRa), LoRa Wide Area Network (LoRaWAN), long-term evolution (LTE) presented. convergence emerging like cloud computing, fog artificial intelligence (AI), machine learning (ML) digital twin also elaborated current state-of-the-art research. Further, techniques channel estimation, user selection, resource allocation energy optimization on performance networks highlighted. end, metrics relevant these addressed comprehensive understanding. benefits, challenges future directions for amalgamation addressed.

Language: Английский

Citations

0
CNTNF Framework Focus on Forecasting and Verifying Network Threats and Faults DOI

Hsia-Hsiang Chen

Internet of Things, Journal Year: 2025, Volume and Issue: unknown, P. 101504 - 101504

Published: Jan. 1, 2025

Language: Английский

Citations

0
Innovative Application of 6G Network Slicing Driven by Artificial Intelligence in the Internet of Vehicles DOI Open Access

Xueqin Ni,

Zhiyuan Dong,

Rong Xia

et al.

International Journal of Network Management, Journal Year: 2025, Volume and Issue: 35(2)

Published: Feb. 5, 2025

ABSTRACT The rapid growth of vehicle networks in the Internet Vehicles (IoV) needs novel approaches to optimizing network resource allocation and enhancing traffic management. Sixth‐generation (6G) slicing, when paired with artificial intelligence (AI), has enormous potential this field. purpose research is investigate use AI‐driven 6G slicing (NS) for efficient usage resources accurate prediction IoV systems. A unique design suggested, combining data‐driven dynamic slicing. Data are acquired from vehicular sensors monitoring systems, log transformation used handle exponential patterns like counts congestion levels. Fourier transform (FT) extract frequency‐domain information data, which allows detection periodic patterns, trends, anomalies such as velocity density. Dipper Throated Optimized Efficient Elman Neural Network (DTO‐EENN) forecast optimize resources. This technology system predict dynamically alter slices ensure optimal while reducing latency. results show that suggested NS technique increases accuracy performance dramatically indicates based offers a solid framework performance.

Language: Английский

Citations

0
Connected Vehicles DOI

S. Prasanna Bharathi,

P. Prakasam

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 251 - 270

Published: April 4, 2025

Vehicle network is a paradigm that presents the concept of connected vehicle with increased economy and safety via vehicle-to-Everything (V2X) communications. Intelligent transportation systems (ITS) play critical role in managing all (CV) technologies on road worldwide. Drivers will be able to operate automobiles differently future, as majority integrated into autonomous vehicles linked environment. Remote drivers can monitor status, such location, position, speed, improve users. The advanced driver assistance (ADAS) technology used for safe movement through remote improves performance by detecting obstacles near using cameras sensors. Enhances reduce computation delay, optimize user experience, costs. Efficacy enhanced compromising interpersonal safety, anti-harassment, child anti-social behaviour, well reducing collisions injuries.

Language: Английский

Citations

0
Optimizing network slicing in 6G networks through a hybrid deep learning strategy DOI
Ramraj Dangi, Praveen Lalwani

The Journal of Supercomputing, Journal Year: 2024, Volume and Issue: 80(14), P. 20400 - 20420

Published: June 1, 2024

Language: Английский

Citations

2
Advanced Network Design for 6G: Leveraging Graph Theory and Slicing for Edge Stability DOI
Mantisha Gupta, Rakesh Kumar Jha

Simulation Modelling Practice and Theory, Journal Year: 2024, Volume and Issue: unknown, P. 103029 - 103029

Published: Oct. 1, 2024

Language: Английский

Citations

2
An Efficient FLI-KDMSSA Framework for Computing Resource Allocation of IoV in Edge Computing DOI Creative Commons
Chao-Hsien Hsieh, Fengya Xu,

Xinyu Yao

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: July 29, 2024

Abstract The combination of Mobile Edge Computing (MEC) and Internet Vehicles (IoV) can effectively improve the network performance. However, mobility vehicles diversity tasks make allocation computing resources more complex. When vehicle is in motion, its position change at any time. This result overload edge servers. Meanwhile, are sensitive to latency. It makes resource within servers difficult. In order solve above problems, this article proposes a FLI-KDMSSA framework for rational Vehicles. First, Fuzzy Logic Inference (FLI) algorithm used determine nodes IoV scenarios. uses task length, server virtual machine utilization, cloud bandwidth as parameters establish fuzzy rules. Then, with objective function minimizing latency load balancing values, paper Discrete Multi-objective Sparrow Search Algorithm based on K-means (KDMSSA) scheme. experiment simulated iFogSim platform. To compare PSO algorithm, performance KDMSSA improved by 12.7%. SSA, 7.7%.

Language: Английский

Citations

0
Statistical slice-level analysis for online detection of distributed denial-of-service (DDoS) attacks in network slicing environments DOI
Suadad S. Mahdi,

Alharith A. Abdullah

Journal of High Speed Networks, Journal Year: 2024, Volume and Issue: 31(2), P. 145 - 158

Published: Dec. 26, 2024

Network slicing (NS) is a technique that enables network operators to create multiple virtual networks, each customized for specific clients, services, or applications, while still utilizing shared physical infrastructure. Although this approach provides benefits in terms of resource usage and flexibility, it also introduces new security risks, particularly the form DDoS attacks. These attacks can be targeted at slices, causing disruptions services provided by those which may impact clients applications rely on services. To mitigate risks posed NS, paper proposes an intrusion detection system designed safeguard slices from The proposed relies statistical methods use joint entropy dynamic thresholds analyze traffic real time. Based findings testbed conducted exhibited remarkable level effectiveness identifying directed targeting slice. rate was recorded 99%, delay extremely low 0.32 s. results imply recognize respond swiftly, aid swiftly mitigating potential threats.

Language: Английский

Citations

0