intel/malconv-model-base
This is an image containing Intel optimized Malconv model file only.
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This docker images contains a Intel optimized Malconv model trained using Keras API in H5 format. Malconv is a convolutional neural network for malicious PE detection, described in the original paper as "Malware detection by eating a whole exe.". The first open-sourced Malconv implementation is originally release by Ember.
For better inference speed using Intel® Advanced Matrix Extensions (Intel® AMX) on the 4th Gen Intel® Xeon® Scalable Processor platform (codename Sapphire Rapids), some of the hyperparameters are tuned with the topology of the network unchanged.
Raff, Edward, et al. "Malware detection by eating a whole exe." arXiv preprint arXiv:1710.09435 (2017).
H. Anderson and P. Roth, "EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models”, in ArXiv e-prints. Apr. 2018.
@ARTICLE{2018arXiv180404637A,
author = {{Anderson}, H.~S. and {Roth}, P.},
title = "{EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models}",
journal = {ArXiv e-prints},
archivePrefix = "arXiv",
eprint = {1804.04637},
primaryClass = "cs.CR",
keywords = {Computer Science - Cryptography and Security},
year = 2018,
month = apr,
adsurl = {http://adsabs.harvard.edu/abs/2018arXiv180404637A},
}
@misc{harang2020sorel20m,
title={SOREL-20M: A Large Scale Benchmark Dataset for Malicious PE Detection},
author={Richard Harang and Ethan M. Rudd},
year={2020},
eprint={2012.07634},
archivePrefix={arXiv},
primaryClass={cs.CR}
}
docker pull intel/malconv-model-base