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Guide to vulnerability analysis for computer networks and systems : an artifical intelligence approach / Simon Parkinson, Andrew Crampton, Richard Hill, editors.

Contributor(s): Material type: TextTextSeries: Computer communications and networksPublisher: Cham, Switzerland : Springer Berlin Heidelberg, 2018Description: x, 384 pages : illustrations (some colour) ; 25 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9783319926230
Subject(s): DDC classification:
  • 005.8 PA.G 2018 23
LOC classification:
  • TK5105.59
Contents:
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: Spotting Unsolicited 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.
Summary: "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 intelligence mechanisms."--Back cover.
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Books Books The Knowledge Hub Library Computing 005.8 PA.G 2018 (Browse shelf(Opens below)) Available 190229

Includes bibliographical references and index.

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: Spotting Unsolicited 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.

"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 intelligence mechanisms."--Back cover.

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