With the ever-increasing threat of cyber-attacks, especially as the COVID-19 pandemic helped to ramp up the use of digital communications technology, there is a continued need to find new ways to maintain and improve cybersecurity. This new volume investigates the advances in artificial intelligence and soft computing techniques in cybersecurity. It specifically looks at cybersecurity during the COVID-19 pandemic, the use of cybersecurity for cloud intelligent systems, applications of cybersecurity techniques for web applications, and cybersecurity for cyber-physical systems. A diverse array of technologies and techniques are explored for cybersecurity applications, such as the Internet of Things, edge computing, cloud computing, artificial intelligence, soft computing, machine learning, cross-site scripting in web-based services, neural gas (GNG) clustering technique, and more.

The volume gives special attention to the impact of the cyber-attack surge during COVID on healthcare and business organizations and the emerging cybersecurity technologies aimed to provide better cybersecurity, including security challenges in mobile app development.

The book also looks at cloud and edge computing security using artificial intelligence and soft computing techniques. Various integration technologies with regards to cyber-physical systems are also described as well as applications of cybersecurity using machine learning approaches. Other chapters look at an efficient vehicle tracking system to enhance security, network forensic attacks using an enhanced growing neural gas (GNG) clustering technique, and more. An audit chapter aggregates data from other sources papers regarding IoT, AI, and cyber-assaults.

The Fusion of Artificial Intelligence and Soft Computing Techniques for Cybersecurity is written for a broad audience of those interested in the applications of artificial intelligence in cybersecurity, including professionals, policymakers, business leaders, network administrators, and many others.