Guide to Vulnerability Analysis for Computer Networks and Systems

Part I: Introduction and State of the Art .- Review of the State of the Art of Vulnerability Assessment Using Artificial Intelligence.- A Survey of Machine Learning Algorithms and Their Application in Information Security.- Part II: Vulnerability Assessment Frameworks .- Vulnerability Assessment of Cybersecurity for SCADA Systems.- A Predictive Model for Risk and Trust Assessment in Cloud Computing: Taxonomy and Analysis for Attack Pattern Detection.- AI and Metrics-Based Vulnerability-Centric Cyber Security Assessment and Countermeasure Selection.- Artificial Intelligence Agents as Mediators of Trustless Security Systems and Distributed Computing Applications.- Part III: Applications of Artificial Intelligence .- Automated Planning of Administrative Tasks Using Historic Events: a File System Case Study.- Defending Against Chained Cyber-Attacks by Adversarial Agents.- Vulnerability Detection and Analysis in Adversarial Deep Learning.- SOCIO-LENS: SpottingUnsolicited Callers Through Network Analysis.- Function Call Graphs Versus Machine Learning for Malware Detection.- Detecting Encrypted and Polymorphic Malware Using Hidden Markov Models.- Masquerade Detection on Mobile Devices.- Identifying File Interaction Patterns in Ransomware Behaviour.- Part IV: Visualisation .- A Framework for the Visualisation of Cyber Security Requirements and its Application in BPMN.- Big Data and Cyber Security: A Visual Analytics Perspective.