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IEEE Journal of Selected Topics in Appli 2023 : Security and Privacy-preserving Solutions on Remote Sensing Data of Smart Cities

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Submission Deadline Feb 28, 2023
 

Call For Papers

CALL FOR PAPERS
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Special Issue on
“Security and Privacy-preserving Solutions on Remote Sensing Data of Smart Cities”
Remote sensing is the process of detecting and monitoring the physical characteristics of an area by measuring its
reflected and emitted radiation at a distance (typically from satellite or aircraft), which helps sense things about the Earth
in smart cities. Although it empowers us, when we consider how Artificial Intelligence and Machine Learning
algorithms are applied to this data, it becomes pretty scary pretty fast unless there is some kind of universal
understanding of how it can be used. It carries two pressing issues: Security and Privacy.
On the one hand, we need to safeguard the security and policy interests of the globe in connection with the distribution
of satellite-acquired Earth remote sensing data; otherwise, attackers and unwanted third parties can perturb the data
forging damage on the ecology and the earth. On the other hand, some of remotely sensed data are sensitive. Sensitive
data refers to data that should not be disclosed unintentionally, like the Gravity Recovery and Climate Experiment
(GRACE) of a significant location or locations of oil reservoirs in a strategic area. Keeping these data private in a way
that adversaries cannot find them without proper permission carries the “privacy-preservation” issue.
Inspired and motivated by the facts that Security and Privacy issues raise concerns for remote sensing data, it is the right
time to consider additional research and rules to ensure technologies do not infringe on privacy or compromise security.
This Special Issue seeks to investigate this challenge by soliciting tutorials and research papers about it. Potential
research directions are fostered for this Special Issue. Surveys and state-of-the-art tutorials are also considered.
The broad topics include (but are not limited to):
1-Cyber Security issues on remote sensing data of smart cities
2- Privacy issues on remote sensing data of smart cities
3- Remote Sensing Data at the control level using Artificial Intelligence
4- Secure Machine Learning for Remote Sensing Data on Smart cities
5- Remote Sensing Data Protection for Smart Cities
Schedule
1 Jul 2022 Submission system opening
28 Feb 2023 Submission system closing
Format
All submissions will be peer reviewed according to the IEEE Geoscience and Remote Sensing Society guidelines. Submitted
articles should not have been published or be under review elsewhere. Submit your manuscript on
http://mc.manuscriptcentral.com/jstars, using the Manuscript Central interface and select the “Security and Privacypreserving
Solutions on Remote Sensing Data of Smart Cities”special issue manuscript type. Prospective authors
should consult the site https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9082768 for guidelines and information
on paper submission. All submissions must be formatted using the IEEE standard format (double column, single spaced).
Please visit http://www.ieee.org/publications_standards/publications/authors/author_templates.html to download a template
for transactions. Please note that as of Jan. 1, 2020, IEEE J-STARS has become a fully open-access journal charging a flat
publication fee $1,250 per paper.
Guest Editors
Mehdi Gheisari
Islamic Azad University, Iran
(mehdi.gheisari61@gmail.com)
Mehdi Sookhak
Texas AM University at Corpus Christi, USA ( m.sookhak@ieee.org)
Hamidreza Rabiei Dastjerdi CeADAR (Ireland’s National Centre for Applied Data Analytics & AI), University College
Dublin (UCD), Ireland (hamid.rabiei@ucd.ie)
Hamid Esmaeili Najafabadi University of Calgary, Canada (Hamid.esmaeilinajafa@ucalgary.ca)
Bahram Sadeghi Bigham Institute for Advanced Studies in Basic Sciences, Iran (b_sadeghi_b@iasbs.ac.ir)
Yang Liu Harbin Institute of Technology, Shenzhen, China (Liu.Yang@hit.edu.cn)

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