*Special issue on*
*Cybersecurity Management in the era of AI*
https://www.springer.com/journal/10922/updates/17974838
***Submissions due:* October 31st, 2020****
*We encourage early submission, please check the open submission schedule
policy below.*
Fifth Generation (5G) and beyond cellular networks have revolutionized the
communication architecture, providing connectivity for people, things,
data, applications, transport, and cities in smart networked environments,
at faster data rates, reduced latencies, and acceptable costs. The massive
number and volume of heterogonous connected devices in such an open space,
as well as the advancements in human computer interaction (HCI), artificial
intelligence (AI), computing and communication technologies have led to an
increasing number of personal and ubiquitous intelligent systems. Such a
wide deployment of connected smart technologies introduces new challenges
to system security and privacy, mainly for Cyber-physical Systems.
Cyberphysical is a term used for the integration of physical and computing
domains as seen in many different areas such as medical, automotive, energy
and other critical systems. Nowadays, cyberphysical systems are highly
prone to cyber attacks and other forms of security threats at the
communication layer due to system high connectivity characteristics. Some
of today's emerging security threats are hard to detect using traditional
security and privacy measures and techniques. Therefore, innovative
security methods and privacy protection solutions are needed to provide
more secure and robust privacy-preserving intelligent cyber-physical
systems. To achieve this, *cybersecurity management systems *need to adapt
to the changing cyber security threats autonomously with minimal user
intervention to provide maximum protection against cyber attacks,
intrusions, malware and various types of data breaches. AI has the
potential to be leveraged in different aspects of cybersecurity and
cyberthreat detection. It has received significant interest lately, where a
plethora of AI and other intelligent learning solutions such as deep and
reinforcement learning are now being integrated into cybersecurity systems
to provide more secure and robust privacy-preserving solutions for personal
and ubiquitous systems. Such integration will play a vital role in
providing enhanced security for intelligent autonomous systems and enables
organizations to make crucial changes to their security landscape.
This Special Issue invites theoretical and applied cutting edge research on
standards, frameworks, models, and approaches on cybersecurity management
in the era of AI and intelligent learning technologies. More specifically,
we encourage original paper submissions on the most recent advances in
security network and system management solutions using AI. The Special
Issue also welcomes contributions from the industry perspective. Topics of
interest include, but they are not limited to:
- Cybersecurity management in cyber-physical systems using AI;
- Security, privacy, and trust issues in cyber-physical systems;
- Blockchain-enabled cyber-physical systems;
- Utilizing AI technologies for cyber investigation and threat
intelligence;
- The integration of AI and Blockchain for security critical
infrastructures;
- Design, optimization and modeling of cybersecurity management
systems;
- AI and ML for intrusion detection/prevention in sensitive
environments;
- Advanced AI techniques to secure future Internet
architectures/protocols;
- Trust management in cyber-physical networks and systems;
- Privacy management at edge of the network using machine learning;
- Trustworthy data collection and processing using intelligent
learning techniques;
- Cybersecurity management of big data;
- AI-based cybersecurity techniques for IoT, IoE, IoH, and IoV;
- Cybersecurity of connected and autonomous vehicles;
- Cybersecurity and AI for digital twin;
- Management framework for intelligent secure networking.
- Cybersecurity management to protect organizations' sensitive
data using intelligent learning techniques;
- AI-enabled digital investigation;
Planned Schedule
*Open-submission schedule:* in this special issue, we implement an "open"
submission approach, where we do not have a submission time period.
Interested authors can submit the paper any time before the fixed deadline,
and the review process will begin right after the paper submission, i.e.,
in a first-in first-serve fashion. The submission schedule is:
- Manuscript due: *October 31st, 2020.*
- Revision notification: within *two* months after the submission.
- Revised paper due: within *one* month after the revision
notification.
- Final notification: *one* month after the revised paper
notification.
- Expected Publication of the Special Issue: *Second Quarter of
2021* (early accepted papers will be accessible online before the deadline).
Submission Format and Review Guidelines
The submitted manuscripts must be written in English and describe original
research neither published nor currently under review by other journals or
conferences. Parallel submissions will not be accepted. *All papers will
undergo a similarity check using iThenticate and the work similarity should
be below 20%.* All submitted papers, if relevant to the theme and
objectives of the special issue, will go through an external peer-review
process. Submissions should (*i*) conform strictly to the *Instructions for
Authors* available on the JNSM website and (*ii*) be submitted through
the *Editorial
Management* system available at http://www.editorialmanager.com/jons.
*Guest Editors of the Special Issue: *
● Moayad Aloqaily, xAnalytics Inc., Canada
● Salil Kanhere, UNSW Sydney, Australia
● Paolo Bellavista, DEIS, Università di Bologna, Italy
● Michele Nogueira, Federal University of Parana, Brazil
*Best Regards*
*Moayad Aloqaily, Ph.D., P.Eng.*
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