IEEE Consumer Electronics Magazine - January/February 2024 - 10

Guest Editors' Introduction
Introduction
Security and Privacy-Aware Emerging
Computing
Deepak Puthal
Khalifa University
Bidyadhar Subudhi
Indian Institute of Technology Goa
Thanos Stouraitis
Khalifa University
& IN THE EVER-EVOLVING landscape of technology,
the rapid proliferation of emerging computing
paradigms has opened new frontiers of
innovation, transforming the way we interact with
and perceive the world. This relentless march of
progress has ushered in the era of " Security and
Privacy-Aware Emerging Computing, " a paradigm
that places the fundamental values of security and
privacy at its core. It seeks to develop innovative
solutions that safeguard sensitive data, protect
user privacy, and fortify the security of emerging
computing systems.
The convergence of technologies such as edge
computing, the Internet of Things (IoT), artificial
intelligence (AI), blockchain, and more has
unlocked unprecedented opportunities for enhancing
our lives, industries, and societies. However,
these advances have also introduced complex challenges
in securing sensitive data, protecting individual
privacy, and ensuring the resilience of these
emerging computing ecosystems. This Special Section
curated 10 articles that tackle security and privacy
concerns in emerging computing. Below, we
provide a brief introduction to all the selected
articles in this Special Section.
In the article titled " Assigning trust to devices
in the context of consumer IoT applications, " Macedo
et al. highlighted the importance of securing
consumer IoT devices, particularly in applications
like smart homes and wearables, to prevent potential
data leaks and security threats. It introduced a
mathematical trust metric based on a two-level
approach for objectively assessing confidence and
enhancing security in IoT device communication.
In the article titled " Securing clustered edge
intelligence with blockchain, " Dehury et al. discussed
a blockchain-based solution to ensure the
immutability and traceability of edge devices' event
history, enhancing security for data from source
devices to cloud servers. This secure clustered
edge intelligence mechanismholds the potential for
establishing transparent and efficient systems.
In the article titled " Securing industrial control
systems from cyber-attacks: A stacked neural-network-based
approach, " Jagtap et al. presented a
stacked deep-learning model validated on industrial
datasets to address limitations in existing literature.
Additionally, it introduced JARA, an opensource
intrusion detection system capable of
detecting HnS IIoT malware when deployed on a
Linux virtual machine, offering enhanced cybersecurity
for cyber-physical systems.
In the article titled " AI-driven EEC for healthcare
Digital Object Identifier 10.1109/MCE.2023.3318090
Date ofcurrent version 13 October 2023.
IoT: Security challenges and future research
directions, " Adil et al. provided a comprehensive
10
2162-2248 ß 2023 IEEE
Published by the IEEE Consumer Technology Society
IEEE Consumer Electronics Magazine
IEEE Consumer Electronics Magazine - January/February 2024

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