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Keywords = wireless snooping attack

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21 pages, 5892 KB  
Review
Smart Home Privacy Protection Methods against a Passive Wireless Snooping Side-Channel Attack
by Mohammad Ali Nassiri Abrishamchi, Anazida Zainal, Fuad A. Ghaleb, Sultan Noman Qasem and Abdullah M. Albarrak
Sensors 2022, 22(21), 8564; https://doi.org/10.3390/s22218564 - 7 Nov 2022
Cited by 18 | Viewed by 6288
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 [...] Read more.
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. Full article
(This article belongs to the Collection IoT and Smart Homes)
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23 pages, 469 KB  
Article
Energy-Efficient Privacy Protection for Smart Home Environments Using Behavioral Semantics
by Homin Park, Can Basaran, Taejoon Park and Sang Hyuk Son
Sensors 2014, 14(9), 16235-16257; https://doi.org/10.3390/s140916235 - 2 Sep 2014
Cited by 27 | Viewed by 7839
Abstract
Research on smart environments saturated with ubiquitous computing devices is rapidly advancing while raising serious privacy issues. According to recent studies, privacy concerns significantly hinder widespread adoption of smart home technologies. Previous work has shown that it is possible to infer the activities [...] Read more.
Research on smart environments saturated with ubiquitous computing devices is rapidly advancing while raising serious privacy issues. According to recent studies, privacy concerns significantly hinder widespread adoption of smart home technologies. Previous work has shown that it is possible to infer the activities of daily living within environments equipped with wireless sensors by monitoring radio fingerprints and traffic patterns. Since data encryption cannot prevent privacy invasions exploiting transmission pattern analysis and statistical inference, various methods based on fake data generation for concealing traffic patterns have been studied. In this paper, we describe an energy-efficient, light-weight, low-latency algorithm for creating dummy activities that are semantically similar to the observed phenomena. By using these cloaking activities, the amount of fake data transmissions can be flexibly controlled to support a trade-off between energy efficiency and privacy protection. According to the experiments using real data collected from a smart home environment, our proposed method can extend the lifetime of the network by more than 2× compared to the previous methods in the literature. Furthermore, the activity cloaking method supports low latency transmission of real data while also significantly reducing the accuracy of the wireless snooping attacks. Full article
(This article belongs to the Special Issue Wireless Sensor Networks and the Internet of Things)
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