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E-raamat: Guide to Vulnerability Analysis for Computer Networks and Systems: An Artificial Intelligence Approach

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This professional guide and reference examines the challenges of assessing security vulnerabilities in computing infrastructure. Various aspects of vulnerability assessment are covered in detail, including recent advancements in reducing the requirement for expert knowledge through novel applications of artificial intelligence. The work also offers a series of case studies on how to develop and perform vulnerability assessment techniques using start-of-the-art intelligent mechanisms.

Topics and features: provides tutorial activities and thought-provoking questions in each chapter, together with numerous case studies; introduces the fundamentals of vulnerability assessment, and reviews the state of the art of research in this area; discusses vulnerability assessment frameworks, including frameworks for industrial control and cloud systems; examines a range of applications that make use of artificial intelligence to enhance the vulnerability assessment processes; presents visualisation techniques that can be used to assist the vulnerability assessment process.

























In addition to serving the needs of security practitioners and researchers, this accessible volume is also ideal for students and instructors seeking a primer on artificial intelligence for vulnerability assessment, or a supplementary text for courses on computer security, networking, and artificial intelligence.
Part I Introduction and State-of-the-art
Review into State of the Art of Vulnerability Assessment using Artificial Intelligence
3(30)
Saad Khan
Simon Parkinson
A Survey of Machine Learning Algorithms and Their Application in Information Security
33(26)
Mark Stamp
Part II Vulnerability Assessment Frameworks
Vulnerability Assessment of Cyber Security for SCADA Systems
59(22)
Kyle Coffey
Leandros A. Maglaras
Richard Smith
Helge Janicke
Mohamed Amine Ferrag
Abdelouahid Derhab
Mithun Mukherjee
Stylianos Rallis
Awais Yousaf
A Predictive Model for Risk and Trust Assessment in Cloud Computing: Taxonomy and Analysis for Attack Pattern Detection
81(20)
Alexandras Chrysikos
Stephen McGuire
AI- and Metrics-Based Vulnerability-Centric Cyber Security Assessment and Countermeasure Selection
101(30)
Igor Kotenko
Elena Doynikova
Andrey Chechulin
Andrey Fedorchenko
Artificial Intelligence Agents as Mediators of Trustless Security Systems and Distributed Computing Applications
131(28)
Steven Walker-Roberts
Mohammad Hammoudeh
Part III Applications of Artificial Intelligence
Automated Planning of Administrative Tasks Using Historic Events: A File System Case Study
159(24)
Saad Khan
Simon Parkinson
Defending Against Chained Cyber-Attacks by Adversarial Agents
183(28)
Vivin Paliath
Paulo Shakarian
Vulnerability Detection and Analysis in Adversarial Deep Learning
211(24)
Yi Shi
Yalin E. Sagduyu
Kemal Davaslioglu
Renato Levy
SOCIO-LENS: Spotting Unsolicited Caller Through Network Analysis
235(24)
Muhammad Ajmal Azad
Junaid Arshad
Farhan Riaz
Function Call Graphs Versus Machine Learning for Malware Detection
259(22)
Deebiga Rajeswaran
Fabio Di Troia
Thomas H. Austin
Mark Stamp
Detecting Encrypted and Polymorphic Malware Using Hidden Markov Models
281(20)
Dhiviya Dhanasekar
Fabio Di Troia
Katerina Potika
Mark Stamp
Masquerade Detection on Mobile Devices
301(16)
Swathi Nambiar Kadala Manikoth
Fabio Di Troia
Mark Stamp
Identifying File Interaction Patterns in Ransom ware Behaviour
317(22)
Liam Grant
Simon Parkinson
Part IV Visualisation
A Framework for the Visualisation of Cyber Security Requirements and Its Application in BPMN
339(28)
Bo Zhou
Curtis Maines
Stephen Tang
Qi Shi
Big Data and Cyber Security: A Visual Analytics Perspective
367(16)
Suvodeep Mazumdar
Jing Wang
Index 383
Dr. Simon Parkinson is a Senior Lecturer in Computer Science in the School of Computing and Engineering, University of Huddersfield, UK.

Prof. Andrew Crampton is a Professor of Computational Mathematics in the School of Computing and Engineering, and the Associate Dean for Teaching and Learning at the University of Huddersfield.

Prof. Richard Hill is a Professor of Intelligent Systems, the Head of the Department of Informatics, and the Director of the Centre for Industrial Analytics at the University of Huddersfield. His other publications include the successful Springer titles Guide to Security Assurance for Cloud Computing, Big-Data Analytics and Cloud Computing, Guide to Cloud Computing, and Cloud Computing for Enterprise Architectures.