The competing landscape between malware authors and security analysts is an ever‐
changing battlefield over who can innovate over the other. While security analysts are …

In this research, we compare malware detection techniques based on static, dynamic, and
hybrid analysis. Specifically, we train Hidden Markov Models (HMMs) on both static and …

In this paper, we develop four malware detection methods using Hamming distance to find
similarity between samples which are first nearest neighbors (FNN), all nearest neighbors …

Introduction to Machine Learning with Applications in Information Security, Second Edition
provides a classroom-tested introduction to a wide variety of machine learning and deep …

In this paper, we consider the problem of malware detection and classification based on
image analysis. We convert executable files to images and apply image recognition using …

Face stands out as a preferable biometric trait for automatic human authentication as it is
intuitive and non-intrusive. This paper investigates various feature-based automatic face …

Malware is any type of computer program which is developed to harm computers, networks,
and information. Noticeable growth of malware development has made computer and …

In this chapter, we consider malware classification using deep learning techniques and
image-based features. We employ a wide variety of deep learning techniques, including …

Identifying free open-source software (FOSS) packages on binaries when the source code is
unavailable is important for many security applications, such as malware detection, software …

Metamorphism is a technique that mutates the binary code using different obfuscations. It is
difficult to write a new metamorphic malware and in general malware writers reuse old …