Cybersecurity in Intelligent Networking Systems

Cyber threats are a common issue to your security and privacy. As various malicious threats and malware have been launched that target critical online services--such as e-commerce, e-health, social networks, and other major cyber applications--it has become more critical to protect important information from being accessed. Data-driven network intelligence is a crucial development in preserving the integrity of your computer by identifying anomalies and ensuring information privacy.

Data-driven Network Intelligence for Cybersecurity provides a comprehensive introduction to exploring technologies, applications, and issues in data-driven cyber infrastructure. It describes a proposed novel, data-driven network intelligence system that helps provide safeguards for edge-enabled infrastructure, edge-enabled artificial intelligence (AI) engines, and threat intelligence. Focusing particularly on encryption-based anomaly detection protocol, this book highlights the capability of a network intelligence system in helping target and identify unauthorized access, malicious interactions, and the destruction of critical information and communication technology.

Data-driven Network Intelligence for Cybersecurity readers will also find:

• Discussion of network anomalies and cyber threats
• Background information on AI and cyber infrastructure, particularly as regards trustworthy and robust artificial intelligence applications
• A presentation of a system and security model in the edge intelligence
• Detailed descriptions of the design of predicates and privacy-preserving anomaly detection features

Data-driven Network Intelligence for Cybersecurity is an essential reference for all professional computer engineers and researchers in cyber security and artificial intelligence, as well as graduate students in these fields.