IEEE Consumer Electronics Magazine - January/February 2024 - 98

Privacy-Aware Emerging Computing
FIGURE 1. Key features of blockchain technology.
introduced smart contracts. Unlike centralized
digital ledgers, blockchain uses neighborhood
verification to synchronize distributed ledgers.
Figure 1 depicts the essential characteristics of
blockchain.
On the other hand, rapid technological
advancements have enabled numerous
latency-critical Internet of Things (IoT) applications.
Edge computing was introduced as a
cloud extension to support such types of applications.
Other names for edge computing
include mobile cloud, virtual cloudlet, and fog
computing.2 Despite the differences in these
technologies, the goal remains the same, i.e.,
enabling thousands of things to operate applications
at the network's edge. The edge-computing
model is identical to cloud computing
in that it equips users with heterogeneity, low
latency, location awareness, and improved
Quality of Service for applications, especially
those that are resource-intensive and latencysensitive.
The distributed formation of edge
computing has diverse well-being.3 However,
the intercommunication of heterogeneous
edge devices and the transfer of assistance
across edge devices pretend significant security
and privacy-associated upshots.
Intelligent Edge for IoT Networks
As shown in Figure 2, the edge-computing
layer is made up of smart-computing devices
that are confined to the IoT device layer. With
shorter latency and more profound communication
expenses, the edge layer becomes
an ideal choice for latency-critical IoT
98
FIGURE 2. Secured and intelligent edgecomputing
framework.
applications. On the other hand, intelligent
edge-computing analyzes data at the edge layer
employing artificial intelligence (AI) and
machine-learning (ML) algorithms.4 In intelligent
edge computing, an edge device collects
data from IoT devices and shares it with other
edge servers over the networks for model
training, analysis, and prediction.5 Because
data are so important in edge-learning techniques,
they are vulnerable to confined changes.
The attacker craves to poison the learning
approach and compromise the users or systems
privacy. Thus, addressing security and
privacy concerns is critical for the attainment
of edge intelligence.
Importance of Blockchain in Edge
Networks
While edge computing has several benefits,
it has drawbacks too, such as privacy and
security concerns. The flaws are caused by
subscription-based user demands, service
migration, and heterogeneous nodes. Currently,
combining blockchain and edge-computing
technology gives a system better
security and management. The new system
ensures integrity and validity.6 The new system
also eliminates the burden of ample storage
because resources are distributed rather
than simply stored on a centralized server.
Despite the benefits of integrating systems,
there are challenges to overcome. Concerns
about privacy and security are raised because
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IEEE Consumer Electronics Magazine - January/February 2024

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