Privacy of IoT-Enabled Smart Home Systems

Dasgupta, Avirup; Gill, Asif Qumer; Hussain, Farookh Khadeer

doi:10.5772/intechopen.84338

Cited by 22 publications

(10 citation statements)

References 35 publications

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“…Machine learning also contributes to developing numerous solutions, such as chatbots [ 20 ], automated video analyzers for CCTVs [ 21 ], anomaly detection solutions [ 22 ], and intelligent computer–human interaction technologies [ 23 ]. Despite the beneficial applications of a smart home, these systems raise concerns, mainly regarding information security and privacy, since they are prone to data leakage, which might result in catastrophic consequences for users [ 24 , 25 ]. Figure 1 illustrates a schematic view of a smart home and a few of its applications.…”

Section: Smart Home Securitymentioning

confidence: 99%

Smart Home Privacy Protection Methods against a Passive Wireless Snooping Side-Channel Attack

Abrishamchi

Zainal

Ghaleb

et al. 2022

Sensors

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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.

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Section: Smart Home Securitymentioning

confidence: 99%

Smart Home Privacy Protection Methods against a Passive Wireless Snooping Side-Channel Attack

Abrishamchi

Zainal

Ghaleb

et al. 2022

Sensors

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“…Dasgupta et al [ 76 ] focused on the consumer privacy aspect of smart home IoT systems. Their paper goes through what are the major privacy concerns as well as where privacy solutions currently exist.…”

Section: Securitymentioning

confidence: 99%

“…The total of connected devices around the world is projected to be in tens of billions. Therefore, as the number of connected devices worldwide is expected to continue to expand exponentially, IoT systems are anticipated to become much more prevalent in the coming years [3][4][5]. Since this beginning, the number of connected devices has been ever increasing to an estimated 50 billion devices by 2020, shown below in Figure 1 [6].…”

Section: Introductionmentioning

confidence: 99%

Recent Advances in Internet of Things (IoT) Infrastructures for Building Energy Systems: A Review

Yaïci

Krishnamurthy²,

Entchev

et al. 2021

Sensors

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This paper summarises a literature review on the applications of Internet of Things (IoT) with the aim of enhancing building energy use and reducing greenhouse gas emissions (GHGs). A detailed assessment of contemporary practical reviews and works was conducted to understand how different IoT systems and technologies are being developed to increase energy efficiencies in both residential and commercial buildings. Most of the reviewed works were invariably related to the dilemma of efficient heating systems in buildings. Several features of the central components of IoT, namely, the hardware and software needed for building controls, are analysed. Common design factors across the many IoT systems comprise the selection of sensors and actuators and their powering techniques, control strategies for collecting information and activating appliances, monitoring of actual data to forecast prospect energy consumption and communication methods amongst IoT components. Some building energy applications using IoT are provided. It was found that each application presented has the potential for significant energy reduction and user comfort improvement. This is confirmed in two case studies summarised, which report the energy savings resulting from implementing IoT systems. Results revealed that a few elements are user-specific then need all be considered in the decision processes. Last, based on the studies reviewed, a few aspects of prospective research were recommended.

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“…A side effect of measuring with various smart systems is that for many people, it is still an invasion of their privacy. Besides, as mentioned earlier, people's behaviour also ensures that the systems are not always used optimally [47]. If the users of the systems did not have to deal with privacy or annoying people, the system to control the use of space could have looked very different.…”

Section: Behaviourmentioning

confidence: 99%

The Sense of Occupancy Sensing

Bakker

Veuger

2021

Applied Sciences

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Purpose: This research is about the added value of occupancy sensing and the factors that influence the added value. The objective of this research is to gain insight into the added value of occupancy sensing from a facility management perspective and the factors that influence the perceived added value. Design/methodology/approach: The paper provides insight into the added value of occupancy sensing from a facility management perspective, obtained through qualitative research. By conducting interviews with suppliers, users and an organisation that consciously chooses not to use occupancy sensing, the added value becomes apparent. The interviewed experts were approached as a result of selected articles or through the Saxion UAS network. The people who responded were interviewed. A limited number of 10 interviews was chosen because that was the minimum number of interviews required for this study. Findings: Several factors influence the added value of occupancy sensing. From the literature, these are data maturity, human behaviour and the quality of sensors. For the study, goal/motivation, preconditions and data or Information Technology (IT) were added. The interviews showed that organisations choose occupancy sensing mainly because smart buildings are on the rise, it is popular and they can make decisions based on the data and evidence. The most important precondition is that it must be known in advance what needs to be measured and that the facility managers are included in the process. The most significant influence on the success of added value is human behaviour. If the end users are not included in the new way of working, there is a good chance that they are not satisfied and that there is no added value. The functioning of IT and the use of the data also influence the added value. This research shows that added value is only achieved if the preconditions are met and factors such as human behaviour are taken into account. When this works well, facility management as a department will also be able to deliver substantial value to the entire organisation. Research limitations/implications: The limitations of this research were that there was only one interview with a non-user. Their opinion would be more valuable where the respondents are asked more about the data maturity of the organisation and their alignment with the organisation’s strategy. The limitations mainly have to do with the limited time frame of the research. In further research, it is also indicated that for a more complete study, this time frame should be extended. Practical implications: The results can be used by everybody who needs to get insight into the use of occupancy sensing from a facility management perspective and the added value for facility management. Originality/value: While there is a significant amount of literature on occupancy sensing and the use of sensors in office environments, there is only limited research on the added value of occupancy sensing from a facility management perspective. Paper type: Research paper. The literature review shows that the added value of facility management is difficult to make tangible. Many organisations see facility management as a cost item, and therefore, the costs must always be taken into account. There is a shift from cost to added value for the organisation, but this only works if the strategy of facility management (FM)/corporate real estate management (CREM) is aligned with the strategy of the organisation. In many cases, this does not yet appear to be the case. For future research, the advice is to look more into other smart features and their added value. Data maturity is a limitation of this research, and the relationship between data maturity and facility management should be studied more. The future is digital and data-driven, and there are not sufficient studies on that.

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Privacy of IoT-Enabled Smart Home Systems

Cited by 22 publications

References 35 publications

Smart Home Privacy Protection Methods against a Passive Wireless Snooping Side-Channel Attack

Smart Home Privacy Protection Methods against a Passive Wireless Snooping Side-Channel Attack

Recent Advances in Internet of Things (IoT) Infrastructures for Building Energy Systems: A Review

The Sense of Occupancy Sensing

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