Communications; Security; Machine Learning
The detailed linear trails of CHAM are given.
In each file, you can find a linear trail and the correlation of it.
In a file named "LT_CHAM_64_xR_y.txt", an x-round linear trail with correlation 2^{-y} of CHAM with a block size of 64 bits is given.
In total, there are 44 linear trails of CHAM with a block size of 64 bits.
In a file named "LT_CHAM_128_xR_y.txt", an x-round linear trail with correlation 2^{-y} of CHAM with a block size of 128 bits is given.
In total, there are 54 linear trails of CHAM with a block size of 128 bits.
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This dataset is used for network anomaly detection and is based on the UGR16 dataset network traffic flows. We used June week 2 to 4 tensors generated from raw flow data to train the models. The dataset includes a set of tensors generated from the whole UGR’16 network traffic (general tensor data) and several sets of port tensors (for specific port numbers). It also includes the trained models for each type of tensor. The tensors extracted from network traffic in the period from July week 5 to the end of August can be used for evaluation. The naming convention is as follows:
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