… traffic shape. This section describes the process of creating the machine learning model for
DoH detection. … We used the proposed detector with ML trained on the design dataset and …

… in network traffic detection, which is a burden on the model’s … However, MLtrained models
may reduce their accuracy on … The AI-based DNS detection technology is shown in Figure 6…

… To have a comprehensive view of DNS security concerns, I … [17] defined a flow-based DNS
tunnel traffic detection … They provided classification results for several ML trained models …

… attacks such as session hijacking, DNS spoofing, eavesdropping, and black hole … database
and ML trained model for identifying and analyzing the network … Ensuring secure access and …

… challenging research branches of information technology, … today’s technology, we identify
the Raspberry Pi 3, model B1 as … classification models able to distinguish normal traffic from …

… paper have presented a new model that can be combined with … and DNS packets, to identify
and filter DDoS attack traffic from … ML-trained chip will initiate the process by gathering traffic …

… , as a sort of clever DNS, converts abstract endpoints into … traffic lights or on the move) and
share data and models in a … and the exchange of ML trained models. Additionally, these shifts …

… shows that ML trained show higher detection accuracy when … measures applied on
CICIDDos-19 dataset in cases of DNS, … a model perform in correctly recognizing the samples that …

… of information technology (IT) and operational technology (OT)… HTTP, SMTP, DNS, TLS/SSL,
and others. In addition to rule-… to evaluate the FED-ML trained models is displayed in Figure …

… In the proposed model ML trained chip systems are capable … resources are overloaded by
this enormous amount of traffic, … response by using mirrored protocols or open DNS resolvers. …