Product Information:-

  • Journals
  • Books
  • Case Studies
  • Regional information
Request a service from our experts.

Machine Learning for Safety, Security and Trust of Cloud and IoT-based Data in Consumer Electronic


Special issue call for papers from Information and Computer Security

Guest editors

Dr. B. B. Gupta, National Institute of Technology, Kurukshetra, India
Email: [email protected]
Dr. Dharma P. Agrawal, University of Cincinnati, Cincinnati, USA
Email: [email protected]

Aims and Scope

Today, with fast changing technology and life-style, we are more and more dependent on uncountable gadgets and electronics goods. Therefore, it is required to control all goods, whether consumer electronics (e.g. TV, refrigerator, fan, video games, remote control cars, etc), gadgets (Google Glass, Raspberry Pi, Apple iBook, etc) or home automation systems (e.g. lighting, heating, ventilation, air conditioning (HVAC), security, etc). All are required to be controlled and from a single platform only. Therefore, Cloud and IoT-based consumer electronics is playing a key role in insuring developing these technologies in efferent and effective manner and improving the quality of life. In short, use of Cloud and IoT is to make consumer electronics ‘A smart Controlled consumer electronics’. However, these cloud and IoT based consumer electronics data and services open a number of safety, security and trust issues and challenges. The concept of applying machine learning approaches to ensure the safety, security and trust of cloud and IoT-based consumer electronics user’s data is feasible and sound. Moreover, machine learning and its associated learning paradigms show promise in a large number of application areas of cloud and IoT-based consumer electronics user’s data security and safely, cloud and IoT-based consumer electronics user’s data management, cloud and IoT-based consumer electronics user’s trust and optimization analysis and so forth. However, the recent advances in machine learning paradigm and its solutions are promising; more investigations are still required to convert theoretical approaches into practical solutions that can be efficiently adopted for safety, security and trust of smart Controlled consumer electronics’ data.
This special issue mainly focuses on machine learning for safety, security and trust of Cloud and IoT-based data in consumer electronics, particularly addressing new applications of the approaches. We are soliciting original contributions, of leading researchers and practitioners from academia as well as industry, which address a wide range of theoretical and application issues in this domain. 

Topics of Interest

The topics relevant to this special issue include but are not limited to:

•    Safety, security and trust of Cloud and IoT-based data in consumer electronic
•    Information revelation and privacy in Cloud and IoT-based consumer electronics platform
•    Cyber-security issues in Cloud and IoT-based consumer electronics
•    Business and organisational aspects of Cloud and IoT-based data security
•    Security governance and compliance for Cloud and IoT-based data in consumer electronic
•    Smart consumers-seller interactions and consumer-computer-interaction
•    Standards for Cloud and IoT-based consumer electronics
•    Machine learning for Safety, security and trust of Cloud and IoT-based data
•    Cloud and IoT-based consumer’s data analysis tools and services
•    Anonymous authentication for privacy preserving in Cloud and IoT-based consumer electronics
•    Privacy concepts and applications in Cloud and IoT-based consumer electronics Platforms
•    Security and privacy of Cloud and IoT-based consumer’s data
•    User-facing security technologies for Cloud and IoT-based data in consumer electronic
•    User perceptions and understanding of security of Cloud and IoT-based data in consumer electronic
•    Deep learning algorithms for safety, security and trust of Cloud and IoT-based data
•    Artificial neural network and neural system applied to cloud computing and mitigating the privacy risks of cloud networking
•    Cloud databases built to be highly scalable and robust against hardware failures
•    Cyber attacks and solutions for high fidelity Cloud storage
•    Risk assessment and modelling of Cloud and IoT-based data
•    Ethics, legal, and social considerations in cloud and IoT-based consumer electronics platform

Important note

It should be noted that all submissions should remain within the general scope of Information and Computer Security, and that the journal is particularly interested in receiving submissions that consider the business and organisational aspects of security, and welcomes papers from both human and technical perspective on the topic.  However, please note it does not look to solicit papers relating to the underlying mechanisms and functions of security methods (although relevant applications of the technology may be considered).

Important Dates

Manuscripts Due: March 31, 2020
First Decision Date: June 30, 2020
Revision Due: August 15, 2020
Final Decision Date: November 01, 2020
Final Paper Due: December 30, 2020

Submission Details

To submit your research, please visit: https://mc.manuscriptcentral.com/iacs

To view the author guidelines for this journal, please visit: https://www.emeraldgrouppublishing.com/products/journals/author_guidelines.htm?id=ics