[agents] Call for Book chapters: A book on Cyber Security

[Ahmed Aleroud]

​C​
all for Book Chapters



Title of Book

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





Editors

     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



Publisher



Studies in Computational Intelligence Series/Springer



Theme

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 operate similarly 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 of information fusion techniques that reveal the
semantics and relationships among 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 Temporal Data



*Network and host Information Fusion for Security Analytics*

·      Network and Host Information in Cyber Security

·      Collecting Network and Host Information for Security Analytics

·      Modeling and Profiling Network and Host Information

·      Attack Prediction Using network and Host Information



*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 in Wireless
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 invited to submit an abstract of 500 words. The editors
will review the abstract to evaluate if the proposed book chapter (1) fits
to the theme of the book, (2) makes a substantial practical or 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 the proposed book chapter. (It is expected that the book will
have 12 to 15 chapters.) This full version will be reviewed by a reviewer,
who is selected based on the topic of the book chapter, as well as the book
editors. The review process by the reviewers (other than the editors) is
double blind. Based on the outcome of the review process, the authors may
be requested to revise their book chapters and to submit the final version.
If the editors are satisfied with the revision of the book chapter, the
authors will be invited to submit a camera-ready version of the paper.

*Deadlines*

December  15th , 2015: Submission of abstracts (500 words)

December 30th, 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

Ahmed21 at umbc.edu, or alsmadi at gmail.com, ialsmadi at newhaven.edu . The
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 number of 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 book chapters 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 ahmed21 at umbc.edu or alsmadi at gmail.com, ialsmadi at newhaven.edu

-- 
*Ahmed AlEroud, *Ph.D,
Visiting Associate Research Scientist
University of Maryland, Baltimore County(UMBC)
Department of Information Systems,
Assistant Professor of Computer Information Systems
Yarmouk University, Jordan
E-mail:*ahmed21 at umbc.edu <ahmed21 at umbc.edu>  *