Topic modeling is a Natural Language Processing technique that has gained popularity over
the last ten years, with applications in multiple fields of knowledge. However, there is …

Topic modeling, or identifying the set of topics that occur in a collection of articles, is one of
the primary objectives of text mining. One of the big challenges in topic modeling is …

Identification of the family to which a malware specimen belongs is essential in
understanding the behavior of the malware and develo** mitigation strategies. Solutions …

Large Language Models (LLMs) are pre-trained on large-scale corpora and excel in
numerous general natural language processing (NLP) tasks, such as question answering …

Distinguishing malicious anomalous activities from unusual but benign activities is a
fundamental challenge for cyber defenders. Prior studies have shown that statistical user …

Much of human knowledge in cybersecurity is encapsulated within the ever-growing volume
of scientific papers. As this textual data continues to expand, the importance of document …

As the amount of text data continues to grow, topic modeling is serving an important role in
understanding the content hidden by the overwhelming quantity of documents. One popular …

This study introduces an unsupervised term extraction approach that combines non-
negative matrix factorization (NMF) with word embeddings. Inspired by a pioneering …

Tensor decomposition is a powerful unsupervised machine learning technique capable of
modeling multidimensional data, including that related to malware. This chapter discusses a …

With the boom in the development of computer hardware and software, social media, IoT
platforms, and communications, there has been exponential growth in the volume of data …