The artificial intelligence subset machine learning has become a popular
technique in professional fields as many are finding new ways to apply
this trending technology into their everyday practices. Two fields that
have majorly benefited from this are pattern recognition and information
security. The ability of these intelligent algorithms to learn complex
patterns from data and attain new performance techniques has created a
wide variety of uses and applications within the data security industry.
There is a need for research on the specific uses machine learning
methods have within these fields, along with future perspectives.
Machine Learning Techniques for Pattern Recognition and Information
Security is a collection of innovative research on the current impact of
machine learning methods within data security as well as its various
applications and newfound challenges. While highlighting topics
including anomaly detection systems, biometrics, and intrusion
management, this book is ideally designed for industrial experts,
researchers, IT professionals, network developers, policymakers,
computer scientists, educators, and students seeking current research on
implementing machine learning tactics to enhance the performance of
information security.