Two-stage intelligent model for detecting malicious DDoS behavior

M Li, H Zhou, Y Qin - Sensors, 2022 - mdpi.com
5G technologies provide ubiquitous connectivity. However, 5G security is a particularly
important issue. Moreover, because public datasets are outdated, we need to create a self …

Identifying ddos attack using split-machine learning system in 5g and beyond networks

BS Rawal, S Patel… - IEEE INFOCOM 2022 …, 2022 - ieeexplore.ieee.org
We rely on the internet heavily for our business in this day and age. As a result, fully
connected or wireless internet access is essential. 5G networks involve different …

Effective feature selection methods to detect IoT DDoS attack in 5G core network

YE Kim, YS Kim, H Kim - Sensors, 2022 - mdpi.com
The 5G networks aim to realize a massive Internet of Things (IoT) environment with low
latency. IoT devices with weak security can cause Tbps-level Distributed Denial of Service …

Light weighted CNN model to detect DDoS attack over distributed scenario

H Kumar, Y Aoudni, GGR Ortiz, L Jindal… - Security and …, 2022 - Wiley Online Library
The minimal‐degree distributed denial‐of‐service attack takes advantage of flaws in the
adaptive mechanisms of network protocols, which could have a big impact on network …

Detection of unknown ddos attacks with deep learning and gaussian mixture model

CS Shieh, WW Lin, TT Nguyen, CH Chen, MF Horng… - Applied Sciences, 2021 - mdpi.com
DDoS (Distributed Denial of Service) attacks have become a pressing threat to the security
and integrity of computer networks and information systems, which are indispensable …

Network traffic behavioral analytics for detection of DDoS attacks

AD Lopez, AP Mohan, S Nair - SMU data science review, 2019 - scholar.smu.edu
As more organizations and businesses in different sectors are moving to a digital
transformation, there is a steady increase in malware, facing data theft or service …

DDoS attacks detection and mitigation in 5G and beyond networks: A deep learning-based approach

B Bousalem, VF Silva, R Langar… - … 2022-2022 IEEE …, 2022 - ieeexplore.ieee.org
Network slicing, where a single physical network is partitioned into several fit-for-purpose
virtual networks with different degrees of isolation and quality of service (QoS), is a key …

Machine-learning-based online distributed denial-of-service attack detection using spark streaming

B Zhou, J Li, J Wu, S Guo, Y Gu… - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
In order to cope with the increasing number of cyber attacks, network operators must monitor
the whole network situations in real time. Traditional network monitoring method that usually …

Machine learning based anomaly detection for 5g networks

J Lam, R Abbas - arXiv preprint arXiv:2003.03474, 2020 - arxiv.org
Protecting the networks of tomorrow is set to be a challenging domain due to increasing
cyber security threats and widening attack surfaces created by the Internet of Things (IoT) …

Hybrid classifier strategy with tuned training weights for distributed denial of service attack detection

D Dahiya - Concurrency and Computation: Practice and …, 2023 - Wiley Online Library
The 5G wireless networks associated with higher data‐transferring speeds considerably
affect the performance of IoT networks. Nowadays, the Internet has become a very …