Privacy Mining from IoT-based Smart Homes

Recently, a wide range of smart devices are deployed in a variety of environments to improve the quality of human life. One of the important IoT-based applications is smart homes for healthcare, especially for elders. IoT-based smart homes enable elders' health to be properly monitored and taken care of. However, elders' privacy might be disclosed from smart homes due to non-fully protected network communication or other reasons. To demonstrate how serious this issue is, we introduce in this paper a Privacy Mining Approach (PMA) to mine privacy from smart homes by conducting a series of deductions and analyses on sensor datasets generated by smart homes. The experimental results demonstrate that PMA is able to deduce a global sensor topology for a smart home and disclose elders' privacy in terms of their house layouts.Comment: This paper, which has 11 pages and 7 figures, has been accepted BWCCA 2018 on 13th August 201

A probability based hybrid energy-efficient privacy preserving scheme to encounter with wireless traffic snooping in smart home

Application of pervasive computing devices in smart homes are rising sharply and due to this matter, demands for efficient privacy protection are increasing urgently. Possibility of interference in wireless networks is proved by previous work. Adversaries can discover contextual information because of traffic monitoring and classifying transmitters based on their radio fingerprints while data packets are encrypted or content is not important for attackers. To conceal communication patterns various approaches have been investigated. They are mainly based on injection of dummy packets into the network traffic and adding delay to transmission time. In this paper, we introduce a hybrid energy-efficient privacy preserving scheme for generating and sending dummy packets through a decision-making algorithm which works based on probability to maximize confusion of attacker in clarifying the real pattern of network traffi

Side channel attacks on smart home systems: A short overview

This paper provides an overview on side-channel attacks with emphasis on vulnerabilities in the smart home. Smart homes are enabled by the latest developments in sensors, communication technologies, internet protocols, and cloud services. The goal of a smart home is to have smart household devices collaborate without involvement of residents to deliver the variety of services needed for a higher quality of life. However, security and privacy challenges of smart homes have to be overcome in order to fully realize the smart home. Side channel attacks assume data is always leaking, and leakage of data from a smart home reveals sensitive information. This paper starts by reviewing side-channel attack categories, then it gives an overview on recent attack studies on different layers of a smart home and their malicious goals

Research on the Development Status and the Trend of Smart Home

The emergence of the Internet of Things (IoT) technology provides new directions and contents for the development of smart homes, breaks the time and space barriers between people and home systems, and the application of IoT technology realizes the integration and management of information between smart home devices, prompting people\u27s home life to be safe, comfortable and intelligent, exploring the life needs of contemporary users, and building a harmonious relationship between people and smart home systems. At present, smart home is developing rapidly and has a greater impact on people\u27s home life. This paper will elaborate on the development status of smart homes in the context of the Internet of Things and explore and study the significance and development trend of Internet of Things technology in the field of the smart home

A systematic review of crime facilitated by the consumer Internet of Things

The nature of crime is changing — estimates suggest that at least half of all crime is now committed online. Once everyday objects (e.g. televisions, baby monitors, door locks) that are now internet connected, collectively referred to as the Internet of Things (IoT), have the potential to transform society, but this increase in connectivity may generate new crime opportunities. Here, we conducted a systematic review to inform understanding of these risks. We identify a number of high-level mechanisms through which offenders may exploit the consumer IoT including profiling, physical access control and the control of device audio/visual outputs. The types of crimes identified that could be facilitated by the IoT were wide ranging and included burglary, stalking, and sex crimes through to state level crimes including political subjugation. Our review suggests that the IoT presents substantial new opportunities for offending and intervention is needed now to prevent an IoT crime harvest

Energy-Efficient Privacy Protection for Smart Home Environments Using Behavioral Semantics

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

Aceitação das tecnologias da casa inteligente: um estudo transversal com potenciais clientes do Brasil

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Produção, Florianópolis, 2023.O desenvolvimento de tecnologias associadas a produtos inteligentes tem se difundido globalmente e em diversas áreas, incluindo empreendimentos residenciais. Nesse contexto, as casas inteligentes surgem como um novo produto e se tornam o foco de diversos estudos, do mercado da construção civil e de discussões tecnológicas, políticas e ambientais. Porém, o processo de disseminação da casa inteligente para uso dos clientes vem ocorrendo de forma lenta e distinta conforme a região que se desenvolvem as tecnologias da casa inteligente. Existem os benefícios percebidos pelo usuário que promovem o uso dessas tecnologias, mas existem fatores que interferem como barreiras no processo de aceitação da casa inteligente. Dessa forma, o objetivo desse trabalho é propor um modelo e estimar o efeito dos fatores que determinam a aceitação das tecnologias da casa inteligente pelos usuários. A fim de alcançar este objetivo, foram utilizadas algumas técnicas e ferramentas como método para o desenvolvimento deste trabalho. A revisão sistemática da literatura e a meta análise foram utilizadas para análise e síntese do portfólio dos estudos. Para identificação dos fatores que interferem na aceitação de tecnologias da casa inteligente por parte do usuário, foi utilizada a abordagem de Strucutural Equation Modeling. Por meio desse estudo, foi possível identificar que os constructos Expectativa de Esforço e Expectativa de Performance apresentam efeito significativo em relação a Atitude e que os constructos Influência Social, Motivação Hedônica, Valor de Preço e Atitude são significativos para a Intenção de Uso. Para identificação do valor percebido pelo cliente diante das funcionalidades da casa inteligente foi utilizada a técnica de preferência declarada e o Willingness to Pay. Esse estudo permitiu identificar que as funcionalidades Eletrodomésticos, Iluminação, Ar Condicionado, Segurança, Medidor, TV e Som e Janelas e Cortinas possuem utilidade significativa pela percepção do usuário. O maior valor médio disposto a pagar pelo usuário é em relação a funcionalidade Segurança, R$3.059,30, e o menor valor médio disposto a pagar é em relação a funcionalidade Janelas e Cortinas, R$501,70. Contudo, esta tese apresenta o ineditismo da realização da meta análise sobre aceitação de tecnologias da casa inteligente, da estimação de aceitação das tecnologias da casa inteligente com potenciais clientes da América do Sul, mais precisamente do sul e sudeste do Brasil, e da estimação conjunta da utilidade de diversas funcionalidades integrantes da casa inteligente e incluindo a disposição a pagar por estas funcionalidades.Abstract: The new technologies associated with smart products have spread globally and in several areas, including residential developments. In this context, smart homes emerge as a new product and become the focus of research in many areas, such as the civil construction market, technological innovation, political and environmental. However, the dissemination of smart home technologies to the customer has been taking place slowly and differently depending on the region of the country. There are many benefits perceived by the user that promote the use of these technologies. However, there are still numerous barriers to accepting the smart home. Thus, this work aims to propose a model and estimate the effect of factors that determine the acceptance of smart home technologies by users. The current research utilized some techniques and tools to reach the thesis goal. A systematic literature review and meta-analysis were used to analyze and synthesize the study portfolio. The Structural Equation Modeling approach was used to identify the factors that interfere with the user's acceptance of smart home technologies. Through this study, it was possible to identify that the Effort Expectation and Performance Expectation constructs have a significant effect on Attitude and that the Social Influence, Hedonic Motivation, Price Value, and Attitude constructs are significant for Intention to Use. The stated preference technique and the Willingness to Pay were used to identify the value perceived by the customer of the features of the smart home. This study allowed us to identify that the functionalities of Appliances, Lighting, Air Conditioning, Security, Meter, TV and Sound, and Windows and Curtains have significant utility in the user's perception. The highest average amount willing to pay by the user is for the Security feature, R$3,059.30, and the lowest average amount is for the Windows and Curtains feature, R$501.70. Moreover, this thesis presents some innovative contributions to the literature, such as the meta-analysis of acceptance of smart home technologies, the estimation of acceptance of smart home technologies with potential customers in South America, more precisely in the south and southeast of Brazil, and estimation of the utility of several functionalities that are part of the smart home, including the willingness to pay for these functionalities