Call for Papers

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Computers & Electrical Engineering, Elsevier (IF: 1.747) ****
https://www.journals.elsevier.com/computers-and-electrical-engineering

https://www.journals.elsevier.com/computers-and-electrical-engineering/call-for-papers/artificial-intelligence-based-information-security

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Special Issue on Artificial Intelligence-based Information Security
-[Extended Submission Deadline]

Information and Communication Technology (ICT) has become very prominent in
the area of Computers and Electrical Engineering (CEE) all across the world.
The use of ICT in CEE devices such as tablets and smart-phones helps
end-users to provide a reliable way to use their services. The worldwide
connectivity of CEE devices using ICT enhances and has expanded the users'
experience. However, the increasing use of ICT in CEE has led to the risk of
various attack vectors and unauthorized access to consumers' personal
information. The opportunity for attackers is directly proportional to the
volume of information stored in CEE devices. ICT has opened up a number of
privacy and security issues in CEE, such as consumer information exposure,
unauthorized software updates, and insecure communication, which have become
key research challenges.

The application of Artificial Intelligence (AI) to information security in
CEE is feasible and sound. The currently available AI techniques for
information security in CEE are still in the challenging phase, such as
collecting and processing large amounts of data from diverse CEE devices.
The design and development of AI techniques for CEE security make rapid
innovations possible. It can deliver efficient AI-based solutions to handle
the large amount of CEE data with limited computational capacity.

This special issue focuses on the design and development of innovative AI
principles and methods for CEE security. We invite technical articles that
have a broad scope and general interest to an engineering audience. The
topics of interest include the following:

*          Context-aware information security in CEE
*          Innovative deep learning paradigms for CEE security
*          Prevention of consumer information exposure using AI
*          Large-scale graph paradigms for information analysis
*          Extraction and analysis of CEE device data for
           decision support and optimization
*          Trusted update mechanisms for CEE
*          Reinforcement learning for large-scale data analysis
*          Big data analysis using AI in the CEE industry
*          AI for a secure Internet of Things (IoT) ecosystem
*          Adversary profiling using intelligent and automated
           methods
*          Detection of cyber threats using AI
*          Privacy and security issues in CEE Software and

Hardware Systems

*          Smartphone and mobile device security

Submission Procedure:

Research articles must not have been published or submitted for publication
elsewhere. All articles will be peer reviewed and accepted based on quality,
originality, novelty, and relevance to the special issue theme. Before
submission authors should refer to the journal's Author Guidelines, which is
available at:
<http://www.elsevier.com/wps/find/journaldescription.cws_home/367/authorinst
ructions>
http://www.elsevier.com/wps/find/journaldescription.cws_home/367/authorinstr
uctions.

Manuscripts must be submitted online at:
<https://www.evise.com/profile/#/COMPELECENG/login>
https://www.evise.com/profile/#/COMPELECENG/login by selecting SI-aisec from
the "Issues" pull-down menu during the submission process.

Schedule:

*          Submission of manuscript: Jan. 31, 2019
*          First notification: Mar. 30, 2019
*          Submission of revised manuscript: Apr. 30, 2019
*          Notification of the re-review: May 30, 2019
*          Final notification: Jun. 30, 2019
*          Final paper due: Jul. 30, 2019
*          Publication Date: Nov. 2019

Guest Editors
James J. Park (Leading GE)
Seoul National University of Science and Technology (
jamespark.seoul@gmail.com)

Hong Shen
University of Adelaide, Australia ( 
hong.shen@adelaide.edu.au)

Muhammad K. Khan
King Saud University, Saudi Arabia ( 
mkhurram@ksu.edu.sa)