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Found 6 papers, 0 papers with code
The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning
To measure these risks of malicious use, government institutions and major AI labs are developing evaluations for hazardous capabilities in LLMs.
Designing Deep Convolutional Neural Networks using a Genetic Algorithm for Image-based Malware Classification
In recent years, deep Convolutional Neural Networks (CNNs) have shown great potential in malware classification.
Ranked #1 on
Malware Classification
on Microsoft Malware Classification Challenge
(Accuracy metric)
FedDICE: A ransomware spread detection in a distributed integrated clinical environment using federated learning and SDN based mitigation
FedDICE integrates federated learning (FL), which is privacy-preserving learning, to SDN-oriented security architecture to enable collaborative learning, detection, and mitigation of ransomware attacks.
Towards a Robust Classifier: An MDL-Based Method for Generating Adversarial Examples
Our final aim is to improve the robustness of the classifier by considering generated examples in rebuilding the classifier.
An MDL-Based Classifier for Transactional Datasets with Application in Malware Detection
This involves selecting a model that best compresses the training dataset for each class considering the MDL criterion.
Malytics: A Malware Detection Scheme
We show feature extraction, which is performed by tf -simhashing, is equivalent to the first layer of a particular neural network.
Cryptography and Security
