The pace of technological advancements, system interconnectivity, and electronic record creation increases substantially with every passing year, and even more exponentially with each passing generation. However, when more attack surface is made available, the opportunity for an increase in attacks and attackers is a natural result. The varying motivations of attackers make any organization a target, regardless of industry. Aside from cyber warfare, which is a major threat with serious risk implications, the top motivations include hacktivism, stealing data for use or sale, stealing bandwidth, stealing money, and holding data hostage.

An effective artificial intelligence (AI) cyber-defense is critical now more than ever. Protocols, technology, and other old fashion countermeasures that worked years ago will not be able to cover the complexity of new threats. However, the adoption of AI in cybersecurity could be hampered or even lead to significant problems for society if the security and ethical concerns are not properly addressed. This creates a high risk to the mala fide use of scientific knowledge. However, the unified knowledge about the new cyber defense technologies will help keep out mala fide users. Additionally, it will create unified blacklists of suspicious services, who fail to cyber security and privacy standards, will make information about the methods and tools that hackers use, and will help assess the sufficiency of defense resources possessed by an organization.

This Special Issue aims to contribute to research community efforts to establish a sound policy framework for AI and machine learning (ML) in cyber defense. Its specific objectives are to provide an overview of the current landscape of AI in terms of beneficial applications in the cybersecurity sector; to present the main ethical implications and policy issues related to the implementation of AI as they pertain to cybersecurity; to put forward constructive and concrete policy recommendations to ensure the AI rollout is securely adopted according to the objectives of the research community's digital strategy. We welcome original research and review articles.

Potential topics include but are not limited to the following:

• AI/ML-based cyber threat analysis
• Cognitive cyber-threat detection and response
• Distributed AI cybersecurity systems
• Deep architectures for cyber defense
• Computational intelligence and neuroscience applications for security and privacy
• Quantum ML
• Data and code integration for cyber security operations
• Deep learning forensics/malware analysis/anomaly detection
• Intelligent defense measures
• Neuroscience-driven security systems
• Cryptographic techniques for AI/blockchain applications
• Crypto-privacy AI techniques