Citation: Nassiri Abrishamchi, M.A.;
Zainal, A.; Ghaleb, F.A.; Qasem, S.N.;
Albarrak, A.M. Smart Home Privacy
Protection Methods against a Passive
Wireless Snooping Side-Channel
Attack. Sensors 2022, 22, 8564.
https://doi.org/10.3390/s22218564
Academic Editors: Sara Comai and
Fabio Salice
Received: 1 October 2022
Accepted: 3 November 2022
Published: 7 November 2022
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Review
Smart Home Privacy Protection Methods against a Passive
Wireless Snooping Side-Channel Attack
Mohammad Ali Nassiri Abrishamchi
1
, Anazida Zainal
1,
* , Fuad A. Ghaleb
1
, Sultan Noman Qasem
2
and Abdullah M. Albarrak
2
1
School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia
2
Computer Science Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud
Islamic University (IMSIU), Riyadh 11432, Saudi Arabia
* Correspondence: anazida@utm.my
Abstract:
Smart home technologies have attracted more users in recent years due to significant
advancements in their underlying enabler components, such as sensors, actuators, and processors,
which are spreading in various domains and have become more affordable. However, these IoT-based
solutions are prone to data leakage; this privacy issue has motivated researchers to seek a secure
solution to overcome this challenge. In this regard, wireless signal eavesdropping is one of the
most severe threats that enables attackers to obtain residents’ sensitive information. Even if the
system encrypts all communications, some cyber attacks can still steal information by interpreting
the contextual data related to the transmitted signals. For example, a “fingerprint and timing-based
snooping (FATS)” attack is a side-channel attack (SCA) developed to infer in-home activities passively
from a remote location near the targeted house. An SCA is a sort of cyber attack that extracts valuable
information from smart systems without accessing the content of data packets. This paper reviews
the SCAs associated with cyber–physical systems, focusing on the proposed solutions to protect the
privacy of smart homes against FATS attacks in detail. Moreover, this work clarifies shortcomings
and future opportunities by analyzing the existing gaps in the reviewed methods.
Keywords: smart home; data privacy; side-channel attacks; IoT security; wireless snooping attack
1. Introduction
1.1. Overview
The smart home is a concept that has existed for a few decades [
1
–
3
] and has promised
technologically improved living environments to enhance the quality of residents’ domestic
lives. In recent years, due to the emergence and rapid growth of the Internet of Things (IoT)
and machine intelligence solutions, this technology has further evolved from a remotely
controlled or automated home to a more realistic, smart home. Modern IoT-based smart
homes provide various services to enhance convenience and residents’ control over their
buildings while combining several intelligent devices. Some of the offered benefits of
current smart homes include the management of and services for the following: tempera-
ture [
4
], ambient lighting [
5
], utility consumption [
6
], internal surveillance [
7
], safety risks
such as fire incidents [
8
], physical security [
9
], intrusion incidents [
10
], and health monitor-
ing for elderly people, kids, and pets [
11
]. However, taking advantage of the mentioned
services is not entirely risk-free for users; e.g., there is a privacy violation risk.
IoT systems depend heavily on wireless communication solutions. Since a home
network carries a remarkable volume of residents’ personal information, any data breach
incident can be a catastrophe for users—for instance, the unauthorized disclosure of lifestyle,
health conditions, political views, and financial situations [
12
,
13
]. In many cases, poten-
tial damages from a data leakage incident in a smart home would be complicated to
compensate, if not impossible. Therefore, rising smart home privacy concerns have mo-
tivated researchers to seek appropriate solutions to mitigate this risk. In this work, we
Sensors 2022, 22, 8564. https://doi.org/10.3390/s22218564 https://www.mdpi.com/journal/sensors
