Tensors

Malware Antivirus Scan Pattern Mining via Tensor Decomposition

Accurate labeling is important for detecting malware and building reference datasets which can be used for evaluating machine learning (ML) based malware classification and clustering approaches. Labels obtained from Anti-Virus (AV) vendors (such as …

Random Forest of Tensors (RFoT) Master's Thesis

Tensor decomposition is a powerful unsupervised Machine Learning method that enables the modeling of multi-dimensional data, including malware data. This thesis introduces a novel ensemble semi-supervised classification algorithm, named Random Forest …

COVID-19 Multidimensional Kaggle Literature Organization

The unprecedented outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), or COVID-19, continues to be a significant worldwide problem. As a result, a surge of new COVID-19 related research has followed suit. The growing number of …

Random Forest of Tensors (RFoT)

Machine learning has become an invaluable tool in the fight against malware. Traditional supervised and unsupervised methods are not designed to capture the multi-dimensional details that are often present in cyber data. In contrast, tensor …

Multi-Dimensional Anomalous Entity Detection via Poisson Tensor Factorization

As the attack surfaces of large enterprise networks grow, anomaly detection systems based on statistical user behavior analysis play a crucial role in identifying malicious activities. Previous work has shown that link prediction algorithms based on …