[Air-L] CFP | Special Issue on on Big Data Analytics and Intelligent Systems for Cybersecurity (Journal of Big Data)

Yassine MALEH y.maleh at uhp.ac.ma
Sat Feb 13 09:49:29 PST 2021


(We apologize if you receive multiple copies of this email)

Special Issue "*Big Data Analytics and Intelligent Systems for
Cybersecurity*" (
https://home.liebertpub.com/cfp/special-issue-on-big-data-analytics-and-intelligent-systems-/314
/)
*Journal: *Big Data
<https://home.liebertpub.com/publications/big-data/611> (Impact
Factor: *3.644| CiteScore™: *5.6*)
Deadline for Manuscript Submission: *September 15, 2021*
*Submission Link:*
https://home.liebertpub.com/publications/big-data/611/for-authors
<https://lnkd.in/dfSGhpJ>

---------------------------------------------------------------------------------

Guest Editors:

Prof. Ahmed A. Abd El-Latif, Menoufia University, Egypt
Prof. Lo’ai Tawalbeh, Texas A&M University-SA, TX, USA
Prof. Yassine Maleh, University Sultan Moulay Slimane, Morocco
Prof. Gokay Saldamli, San Jose State University, CA, USA

Scope:

*Big Data* analytics is an umbrella term for multidisciplinary methods of
data analytics that employ advanced mathematical and statistical techniques
to analyze large data sets. While data science is a powerful tool to
enhance performance, it is only as strong as the data used to develop the
solutions.  Big data analytics is the intelligence brought to data to
transform data into actionable insights for the benefit of industry and
society. Big data analytics benefits organizations in many ways, driving
competitiveness and innovation. On the other hand, big data might contain
sensitive and private information that might be at risk of exposure during
the analysis process.

Big data sets harness information from multiple sources such as databases,
data warehouses, and log and event files. Also, data can be obtained from
security controls such as intrusion prevention systems and user-generated
data from emails and social media posts. So, it is crucial to protect the
data of individuals and organizations.

This special issue addresses the use of big data analytics and intelligent
systems in cybersecurity and the associated issues and challenges.

Suggested Topics:

   - Intelligent systems for effective detection of cyber-attacks with big
   data analytics
   - Big data analytics for Cyber threat intelligence and detection
   - Big data analytics for intrusion detection in Internet of Things (IoT)
   systems
   - Big data analytics for Cloud/Edge systems security
   - Malware detection using big data analytics and intelligent systems
   - Dimensionality reduction and sampling techniques for valuable
   cybersecurity data extraction
   - Advanced persistent threat (APT) detection techniques in big data
   analytics
   - Representation of cyber-attack data for cross-platform processing
   - Network forensics using big data analytics
   - Forensic Data Analytics (FDA)
   - Data Analytics for privacy-by-design in smart health
   - Stream data processing for real-time threat analysis
   - User security policies for Big data analytics
   - Case Studies and Innovative Applications
   - Other topics addressing smart city big data and applications

We will seek papers with conceptual and theoretical contributions and
papers documenting interesting and important effects with a plausible
theory to explain these effects in consumer behavior contexts.

Submission Guidelines:
Prospective authors are requested to submit new, unpublished manuscripts
for inclusion in the upcoming event described in this call for papers.
Paper submissions for this special issue should follow the submission
format and guidelines
<https://home.liebertpub.com/publications/big-data/611/for-authors>.

*Indexing/Abstracting: *


   - PubMed/MEDLINE
   - PubMed
   - Central Science Citation Index Expanded
   - Journal Citation Reports/Science Edition
   - Scopus

Deadline for manuscript submissions: *September 15, 2021.*
For more information:
https://home.liebertpub.com/cfp/special-issue-on-big-data-analytics-and-intelligent-systems-/314/

Best regards,
Special Issue Editors



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