Guide-VA-AI-18: Guide to Vulnerability Analysis for Computer Networks and Systems - An Artificial Intelligence Approach |
Website | https://selene.hud.ac.uk/scomsp2/book/index.html |
Submission link | https://easychair.org/conferences/?conf=guidevaai18 |
Submission deadline | February 28, 2018 |
Guide-VA-AI
Guide to Vulnerability Analysis for Computer Networks and Systems - An Artificial Intelligence Approach
Call for Chapters
Edited book, commissioned by Springer - Call for Chapters
Synopsis
Performing a vulnerability assessment of any computing infrastructure is an essential component in improving system security. This is achieved by identifying and mitigating security weaknesses on a recurring basis. Undertaking a vulnerability assessment requires in-depth knowledge of: the underlying system architecture; the available data sources for assessment; algorithmic techniques used to assist in identifying vulnerabilities through data processing; and visualisation technologies capable of increasing human understanding and minimising cognitive load.
By exploring novel applications of Artificial Intelligence, this book will cover various aspects of vulnerability assessment, including recent advancements made in reducing reliance on expert knowledge. This book will provide many case studies and can be used by security professionals and researchers as a reference text, detailing how they can develop and perform vulnerability assessment techniques using state-of-the-art intelligent mechanisms.
Areas of interest are, but not restricted to:
- Background
- Introduction/overview of vulnerability analysis
- Basic concepts of AI systems and their application in assessing vulnerability
- State-of-the-art review covering Vulnerability Anaysis and AI
- Identification of Resources
- Automated scanning techniques
- Privacy-preserving techniques
- Acquisition
- Review of data sources
- Algorithms for extracting large volumes of data from many sources
- Management and storage of big data
- Post-processing
- Data collation and integrity checking
- Selection, development and integration of Unsurprised learning. E.g Cluster methods such as k-Means, Hierarchical, as well as Hidden Markov models
- Selection, development and integration of Supervised learning. E.g. Artifical Neural Networks
- Temporal analysis techniques
- Visualisation techniques to aid situation awareness
- In-situ Analysis
- Real-time vulnerability detection methods
- Use of AI techniques in the detection and reaction to Malware
- Use of AI techniques to detect Network vulnerabilities
- Configuration of security controls
- Mitigation
- Extracting and encoding of expert knowledge
- Causal planning of mitigation strategies
- Vulnerability Assessment and Mitigation of Modern Architectures
- Cloud, FOG, EDGE, IoT systems
Important Dates
Chapter submission deadline: | 28/02/2018 |
Process
In the first instance, a brief expression of interest should be submitted through the following EasyChair submission page and include an anticipated outline (e.g. table of contents) of the proposed chapter's contents.
Each chapter should be approximately 20-25 pages (Springer format) in length and should contain:
- End of chapter questions that can be used for teaching activities.
- Open-ended questions provided at the end of each chapter to facilitate discussion on a seminar basis.
The Editors will review your expression of interest and respond within 5 working days of the submission.
Resources
You can find MS Word templates, LaTeX style files, and further information to help you prepare your manuscript at:
Contributors need only focus on the content of the proposed chapter as the Editors will take care of final formatting.
Editors
Dr Simon Parkinson, Prof Andrew Crampton, Prof Richard Hill