Impact Score 5.45
In the past 10 years, several techniques have been proposed to address the security and privacy issues of smart systems. For dealing with cyber security a set of technologies and processes designed to protect computers, networks, programs, and data from attack, unauthorized access, change, or destruction. However, Smart cities are likely to increase the standard of living, endorseviable growth, and improve the functionality of urban structures. Currently, several smart systems have been employed in the conventional system, which lead to a number of security and privacy issues. In this regards, the system necessitates effective countermeasures to deal with this. Based on the current practical situations, machine learning (ML) based algorithms have been widely employed as one of the major tools to increase the security infrastructures by improving the efficiency of intrusion detection system. The ML based tools has been widely adopted to secure the Wireless sensor network (WSNs), predictions of personalized decisions, secure the smart-phone, improving the biometric security systems, secure the collected data from different smart sensors, protecting the data collected from smart-meters and many more.
The main intent of this special issue is to cover both the theory and applications of various ML techniques as solutions to privacy and security issues in smart systems. It aims to provide an intellectual forum for researchers in Academia, and Scientists and Engineers from a wide range of application areas to present their latest research findings in ML techniques to identify future challenges towards privacy and security concerns.
Topics include but are not limited to the following:
Dr. Janmenjoy Nayak, Department of CSE, Aditya Institute of Technology and Management, Srikakulam, AP-532402, E-mail: [email protected] David Al-Dabass, School of Computing & Informatics, Nottingham Trent University, Nottingham, UK, Email: [email protected] Danilo Pelusi, Communication Sciences, University of Teramo, Coste Sant'agostino Campus, Teramo, Italy, E-mail: [email protected] Manohar Mishra, Department of Electrical and Electronics Engineering, Faculty of Engineering and Technology, Siksha ‘O’ Anusandhan University, Bhubaneswar, Odisha, India, E-mail: [email protected]
Submission of Manuscripts: 31st DECEMBER 2020Notification to Authors (1st Revision): 31st MARCH 2021Submission of Revised Manuscripts: 30th MAY 2021Notification to Authors (2nd Revision): 30th JUNE 2021Final Versions Due: 31st AUGUST 2021
Peer Review Process
All the papers will go through double blind review process.Suggestions reviewers will be given in three parts:- Mandatory changes / corrections- Possible modifications for betterment- Suggestions for extending the work in future (for implementing while submitting in journal special issues of the conference)A thorough check will be done and the guest editors will check any significant similarity between the manuscript under consideration and any published paper or submitted manuscripts of which they are aware. In such case, the article will be directly rejected without proceeding further. Guest editors will make all reasonable effort to receive the reviewer’s comments and recommendation on time.
Paper submissions for the special issue should follow the submission format and guidelines (https://www.springer.com/journal/521/submission-guidelines).Authors should select ‘SI: Machine Learning for Security and Privacy’ during the submission step 'Additional Information'.The submitted papers must provide original research that has not been published nor currently under review by other venues. Previously published conference papers should be clearly identified by the authors at the submission stage and an explanation should be provided about how such papers have been extended to be considered for this special issue.