… LSTM-GRU Architecture In this work, the fusion of gated recurrent unit (GRU) and long
short-term memory (LSTM) … of LSTM units, while the other three are composed of GRU units. The …

… RNN networks for classification with a high accuracy rate. The literature [24] proposed an
intrusion detection … anomaly detection using RNN, which is more accurate for different types of …

… has less complexity in the architecture when compared to LSTM, thus, making it … detection
experiments using GRU and LSTM and evaluated the performances on the intrusion detection …

… 6 depicts the configuration of the RNN, LSTM and GRU networks that are investigated in
this research. The first layer is the input layer which feeds into a construct of RNN/LSTM/GRU …

… So, in this paper, we propose a new combined IDM called LA-GRU based on a novel …
popular variant of LSTM, gated recurrent unit (GRU) [29] simplifies the gated structure in LSTM’s …

… of GRU units, it will be input to the fully connected layer for classification. Since the CAN
intrusion detection … Different from AdaBoost and SVM, LSTM has strong similarity with the GRU …

… The experimental results showed that GRU is more suitable as the memory unit of RNN
than long short term memory (LSTM) in intrusion detection. 3) With the help of the deep neural …

… active research on network intrusion detection, prediction and … intrusion detection, the
prediction of future network intrusions … GRU over LSTM was inspired by the observation that LSTM-…

… Attack detection: The LSTM method and GRU method are combined (LSTM-GRU) for detecting
the instruction attacks in IoT within a specific time from unauthorized access. This method …

… intrusion detection system(network), this approach is currently a significant focus of intrusion
detection … Using LSTM, we can add or remove information to the cell states and they are …