Personal and Ubiquitous Computing
Akshi Kumar Delhi Technological University, New Delhi Sudhir Kumar Sharma Institute of Information Technology and Management, New Delhi Dimitrios A. Karras National Kapodistrian University of Athens (NKUA) Bhuvan Unhelkar University of South Florida
There has been an upsurge in the use of mobile services, sensors, and application data to better help understand user behaviour, and to gain tangible benefits from, the Internet of Things (IoT).
There is a great deal of research on the applications of pervasive and ubiquitous computing including mobile health, transportation, energy, and urban planning, amongst others.
The Web of Things (or WoT) aims to provide a single universal application layer protocol which enables things to communicate with each other in a seamless way and to facilitate interoperability across platforms and application domains.
While communication between objects and across the web is a focal point of WoT, the approach inherits the same security and privacy issues already present in the Internet. These issues are around the heterogeneous and the constrained nature of devices, identity management, privacy, physical as well as digital access to devices, and trust. Also, new threat vectors have emerged that amplify conventional hacking methods, enabling large?scale and intelligence?driven attacks against a variety of platforms, including mobile, cloud, IoT, as well as conventional networks.
Machine Learning (ML) has emerged as one of the most effective computational paradigms to provide embedded intelligence in IoT devices. The goal is to monitor users, devices and networks to form patterns and at the same time generate reliable actionable information about threats, vulnerabilities and intrusion with minimal human intervention, providing holistic security and privacy solutions.
This issue aims to stimulate discussions about security and privacy in WoT, ubiquitous and mobile computing environments. Papers that describe innovative ML techniques and novel security and privacy solutions are strongly encouraged, especially around identity management, data confidentiality, authorization and access control and in general the dynamics of context aware systems.
Topics of interest for this issue include, but are not limited to:
Context aware security in computing Security attacks related to IP-enabled environments Security threats of sensor-cloud environments Security management of mobile data Secure user interactions and ubiquitous services Security and privacy in location?based services Security and privacy in mobile social networks System and data integrity Trust management in ubiquitous services Threats and vulnerabilities in WoT systems Architectures for securing the WoT Intrusion and malware detection for Web-enabled IoT Privacy preservation and trust in WoT systems Security designs for Internet of Resources (IoR: cloud) System and data integrity in the Internet of People (IoP) Blockchain for secure and smart IoT Security in portable devices and wearable computers Energy efficient security solutions
Submissions should be original papers and should not be under consideration for publication elsewhere.
Extended versions of papers from relevant conferences and workshops are invited as long as the additional contribution is substantial (at least 30% of new content).
Authors should follow the formatting and submission instructions for Personal and Ubiquitous Computing at . For more information visit the Springer Nature Information for journal Article Authors pages at
During the first submission step in Editorial Manager select Original article as the article type. In further steps, you should confirm that your submission belongs to this special issue by choosing the special issue title from the drop-down menu.
All papers will be peer-reviewed.
Paper submission due: March 25, 2021
First notification: May 30, 2021
Revisions due: July 25, 2021
Final decision: September 30, 2021