Neural Nets Can Learn Function Type Signatures From Binaries

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How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks (2019, methodology): “In the security space, DNNs are used for everything from malware classification [1], [2], to binary reverseengineering [3], [4] and network intrusion detection [5].”
Edge Computing Security: State of the Art and Challenges (2019, unknown): “[43], Song et al.”
Exploring Backdoor Poisoning Attacks Against Malware Classifiers (2020, background): “With the shift towards machine learning (ML) based classifiers, this second group has been split into two additional subcategories: feature based detectors [10, 37, 41, 42, 45], and raw-binary analyzers [21, 31, 39].”
LEMNA: Explaining Deep Learning based Security Applications (2018, methodology): “So far, researchers have successfully applied deep neural networks to train classifiers for malware classification [2, 16, 21, 48, 68], binary reverse-engineering [15, 52, 71] and network intrusion detection [24, 62], which all achieved an exceptionally high accuracy.”