Help protect your network with this important reference work on cyber security 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 Cyber Security 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 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 Cyber Security 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.