With the increasing number and sophistication of malware attacks, malware detection systems based on machine learning (ML) grow in importance. At the same time, many popular ML models used in malware classification are supervised solutions. These …
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 …
Non-negative matrix factorization (NMF) with missing-value completion is a well-known effective Collaborative Filtering (CF) method used to provide personalized user recommendations. However, traditional CF relies on the privacy-invasive collection …
The need for efficient and scalable big-data analytics methods is more essential than ever due to the exploding size and complexity of globally emerging datasets. Nonnegative Matrix Factorization (NMF) is a well-known explainable unsupervised …
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 …