... Effectiveness of Video-Classification in Android Malware Detection Through API-Streams and CNN-LSTM Autoencoders Gianni D'Angelo , Francesco Palmieri , and Antonio Robustelli(B ) Department of Computer Science, University of Salerno ...

Malware Data Science explains how to identify, analyze, and classify large-scale malware using machine learning and data visualization.

DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed. This book fills a gap between the emerging fields of DL/AI and malware analysis.

This book provides readers with up-to-date research of emerging cyber threats and defensive mechanisms, which are timely and essential.

This book constitutes the refereed proceedings of the 29th Australasian Joint Conference on Artificial Intelligence, AI 2016, held in Hobart, TAS, Australia, in December 2016.

By the end of this book, you will have the skills you need to use Keras when building high-level deep neural networks.

The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.

The authors develop a malware fingerprinting framework to cover accurate android malware detection and family attribution in this book.

This book gathers selected research papers presented at the International Conference on Recent Trends in Machine Learning, IOT, Smart Cities & Applications (ICMISC 2020), held on 29–30 March 2020 at CMR Institute of Technology, Hyderabad, ...

This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2021) is intended to be used as a reference book for researchers and practitioners in the disciplines of computer science, electronics and ...