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CyberSec 2016 : Call for Book Chapters- A New book on Cyber Security- Studies in Computational Intelligence-Springer


When Oct 12, 2015 - Oct 6, 2016
Where Studies in Computational Intelligence
Abstract Registration Due Dec 10, 2015
Submission Deadline Dec 30, 2015
Notification Due Apr 1, 2016
Final Version Due Jun 3, 2016
Categories    information security   data mining   contextual information

Call For Papers

Title of Book

·Information Fusion for Cyber-Security Analytics: Trends and Patterns

· Dr. Izzat Alsmadi: Assistant Professor, Department of Computer Engineering & Computer Science, University of New Haven, USA

· Dr. Ahmed Aleroud Assistant Professor, Department of Computer Information Systems, Yarmouk University, Jordan. Visiting Associate Research Scientist, University of Maryland, Baltimore County, USA

· Dr. George Karabatis, Associate Professor, Department of Information Systems, University of Maryland, Baltimore County, USA


Studies in Computational Intelligence-Springer


The growth of computer networks has increased the importance of cyber security ranging from homeland security to personal life. With this growth, more computer systems become vulnerable and can be misused. Research in cyber-security has demonstrated that dealing with cyber-attacks is by no means an easy task. One particular limitation of existing tools comes from the uncertainty of information gathered and used to discover attacks.The quality and adequacy of information is important to decrease uncertainty in the attack prediction process. From the theoretical perspective, information fusion focuses on new information reasoning techniques that intelligently use data collected from sensors to identify cyber-threats. Information fusion techniques have several positive and practical implications in Cyber Security: They decrease the overwhelming data analysis efforts required from security experts, since information fusion frameworks operatesimilarly to a rule created by domain experts who first notice little details that indicate a misuse and then investigate further in an attempt to build coherent explanation of the observed events. In addition, information fusion enables the identification of attacks by analyzing data about situations not individual events. Individual events may seem fairly benign when viewed individually, but when those events are analyzed through the scope ofinformation fusion techniques that reveal thesemantics and relationshipsamong events, they enable us to build a coherent analysis of evidence to recognize attacks.

Possible topics are (but are not limited to)

Information Fusion for Cyber-Security Analytics

· Activity Information Fusion for Security Analytics
· Introduction to Activity Information and its use in Cyber-Security
· Activity Monitoring Techniques
· System Monitors
· Data Collection Techniques-Activity Data
· Integration and Information Fusion-Activity Data
· Intrusion Detection using Activity Data
· Collaboration and Sharing of Activity Data

Location Information Fusion for Security Analytics
· Collecting Location Data from Sensors
· Location Data Modeling
· Location Data Processing and Mining
· Location Data Fusion
· Location Data Reasoning
· Creating Attack Prediction Models Using Location Data

Time Information Fusion for Security Analytics
· Temporal Modeling of Cyber Attacks
· Fusion of Temporal Data
· Reasoning Temporal Data to Predict Cyber Attacks
· Stream Mining based on Dynamic Information Fusion
· Sliding Time Windows to Predict Cyber Attacks
· Distributed Security Analytics Using TemporalData

Network and host Information Fusion for Security Analytics
· Network and Host Information in Cyber Security
· Collecting Network and Host Informationfor Security Analytics
· Modeling and Profiling Network and HostInformation
· Attack Prediction Using network and HostInformation

Relation Information Fusion for Security Analytics
· Graph Modeling Techniques
· Information Fusion Using Ontology
· Information Fusion Using Semantic Nets
· Predicting Cyber Attacks Using Relation Information
· Reasoning about Relation Information to Predict Cyber Attacks

Trends in Using Information Fusion Techniques to Discover Cyber Threats

Big Data Fusion for Predicting Network Threats
· Big Data Analytics
· Big Data Fusion
· Big Data Fusion Techniques for Predicting Cyber Attacks
· Big Data Reasoning for Security Analytics

Using Software Defined Networks for Cyber Threat Discovery
· Security In SDN
· Information Fusion in SDN
· Cyber Security Analytics Using Information Extracted from SDN
· Reasoning Techniques in SDN

Privacy Preserving Information Fusion for Analyzing Network Data
· Security Versus Privacy In Computer Networks
· Privacy Preserving Techniques
· The rule of Information Fusion to Enhance Privacy in Security Analytics
· Reasoning Techniques for Privacy Preserving Security Analytics

Using Information Fusion to Discover Zero-Day Attacks
· Zero-day Attack Prediction Techniqes
· Information Fusion Techniques to Identify Zero-Day Attacks
· Information Reasoning and Context Similarity Techniques to Discover Zero-Day attacks
· Measuring the Risk of Zero-Day Attacks Using Information Fusion

Enhancing Social Network Privacy and Security Using Graph-based Data Fusion
· Information Fusion for Improving Social Network Privacy and Security
· Privacy Techniques in Social Network
· Reasoning Techniques to improve Privacy in Social networks
· Trust issues in Social Networks.

Using Information Fusion to discover Cyber-threats in Wireless Sensor Networks
· Security in Wirelesss Sensor Networks and their Applications
· Data collection and Information Fusion Tehniques inWireless Sensor Networks
· Information Reasoning techniques for Security analytics in Wireless Sensor Networks
· Privacy Issues in wireless Sensor Networks
· Using Information Fusion techniques to Dicover Privacy attacks on Wirelsss Sensor Networks

Information Fusion for Improving Privacy and Security in Healthcare Applications
· Health IT and BioMedical Informatics
· Security and Privacy Issues Health IT
· Using Information Fusion in Health IT
· Security and Privacy Analytics in Heath IT

Predicting Social Engineering Attacks Using Information Fusion Techniques
· Social Engineering Attacks
· Data collection techniques to Discover Social Engineering Attacks
· Infromation Fusion for Phishing Detection
· Reasonong Techniques to Discover Social Engineering Attacks

Applications and tools:

Information Fusion Application and Tools for Cyber Security Analytics
· Big Data Tools
· Graph Data Fusion Applications Tools
· Time and Location Modeling Applications Tools
· Software Defined Networking Applications Tools
· Privacy Preserving Tools
· Social Network Analysis Tools

Type of contributions and length

- Research papers: Computational and quantitative contributions that study particular aspects of Cyber Security.

- Conceptual papers: Contributions that synthesize existing studies.

Both types of contributions are expected to be from 20 to 25 pages in length (excluding references)when applying the Springer formatting instructions. Contributions should be original and

not be submitted elsewhere.

Review process
There will be a two-stage review process. In the first stage potential authors will be invitedto submit an abstract of 500 words. The editors will review the abstract to evaluate if theproposed book chapter (1) fits to the theme of the book, (2) makes a substantial practicalor scientific contribution and (3) is of interest to the target audience.

In the second stage the selected authors will be invited to submit a full version of theproposed book chapter. (It is expected that the book will have 12 to 15 chapters.) This fullversion will be reviewed by a reviewer, who is selected based on the topic of the bookchapter, as well as the book editors. The review process by the reviewers (other than theeditors) is double blind. Based on the outcome of the review process, the authors mayberequested to revise their book chapters and to submit the final version. If the editors aresatisfied with the revision of the book chapter, the authors will be invited to submit acamera-ready version of the paper.

December 10th, 2015: Submission of abstracts (500 words)

December30th, 2015: Invitation to submit full chapter

February 5, 2016: Submission of full chapter

April 1st, 2016: Review notification

April 20st, 2016: Submission of revised chapter

May 11, 2016: Final notification of acceptance/rejection

June 3, 2016: Submission of final version

Submission and formatting

Abstracts should be submitted as plain Word (2010 or higher) or PDF files by e-mail to, or, abstract should contain:

1) Title of the proposed chapter

2) Author(s) of the chapter (including affiliation)

3) Type of contribution (Full research paper, report or conceptual paper)

4) Estimated numberof pages (excl. references)

5) Abstract of 500 words describing contents of the book chapter (incl. methodology)

6) Keywords (at least 2 and no more than 5)

Full bookchapters need to be formatted according the Springer instructions and submitted in Word

(2010 or higher) or PDF format. These formatting instructions will be e-mailed together

with the acceptance notification of your abstract.For further questions please contact or,

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