Smart Connected Homes

Bugeja, Joseph; Jacobsson, Andreas; Davidsson, Paul

doi:10.1002/9781119456735.ch13

Cited by 11 publications

(7 citation statements)

References 25 publications

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“…In order to populate α l for the entire attack tree, we can use the aggregation rule defined by Equation (1).…”

Section: Privacy Metricsmentioning

confidence: 99%

“…For affected users, we assume that this represents whether the leaked data affects one individual to multiple users, e.g., the entire family, and grade this using an ordinal scale (1)(2)(3). The affected users is also related to the smart home backend (i.e., B).…”

Section: Ident Level (Imentioning

confidence: 99%

“…In Table 6, we display the risk factors associated with α i . These factors are combined using multiplication, and thus α i = Norm(damage potential × affected users), with Norm being a function that normalizes the output into the range of [1][2][3][4][5][6][7][8][9][10].…”

Section: Ident Level (Imentioning

confidence: 99%

“…These connected devices collect and exchange data with each other and their users using embedded sensors and the Internet, seamlessly merging the physical and digital worlds inside the home. Consequently, these technologies are linked to a variety of benefits, including improved convenience, energy efficiency, enhanced security and safety, and more [ 1 ]. The smart home market has seen rapid growth over the past few years.…”

Section: Introductionmentioning

confidence: 99%

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PRASH: A Framework for Privacy Risk Analysis of Smart Homes

Bugeja

Jacobsson

Davidsson

2021

Sensors

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Smart homes promise to improve the quality of life of residents. However, they collect vasts amounts of personal and sensitive data, making privacy protection critically important. We propose a framework, called PRASH, for modeling and analyzing the privacy risks of smart homes. It is composed of three modules: a system model, a threat model, and a set of privacy metrics, which together are used for calculating the privacy risk exposure of a smart home system. By representing a smart home through a formal specification, PRASH allows for early identification of threats, better planning for risk management scenarios, and mitigation of potential impacts caused by attacks before they compromise the lives of residents. To demonstrate the capabilities of PRASH, an executable version of the smart home system configuration was generated using the proposed formal specification, which was then analyzed to find potential attack paths while also mitigating the impacts of those attacks. Thereby, we add important contributions to the body of knowledge on the mitigations of threat agents violating the privacy of users in their homes. Overall, the use of PRASH will help residents to preserve their right to privacy in the face of the emerging challenges affecting smart homes.

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“…In order to populate α l for the entire attack tree, we can use the aggregation rule defined by Equation (1).…”

Section: Privacy Metricsmentioning

confidence: 99%

Section: Ident Level (Imentioning

confidence: 99%

Section: Ident Level (Imentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

PRASH: A Framework for Privacy Risk Analysis of Smart Homes

Bugeja

Jacobsson

Davidsson

2021

Sensors

Self Cite

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“…Desde hace 30 años, se han realizado varias investigaciones con el objetivo de hacer que todos los objetos cotidianos sean un poco más interactivos. Conceptos como el hogar inteligente (Ricquebourg, et al, 2006) (Bugeja, Jacobsson, & Davidsson, 2018) también conocido como el hogar del mañana, han evolucionado antes de que nos demos cuenta de un hogar conectado para entrar en la era de IoT. Si se definiera IoT, sería mejor decir que es una red que interconecta objetos físicos usando Internet (Ma & Liu, 2017).…”

Section: Introductionunclassified

Uso del asistente virtual Alexa como herramienta de interacción para el monitoreo de clima en hogares inteligentes por medio de Raspberry Pi y DarkSky API

Calvopiña

Tapia

Tello-Oquendo

2020

risti

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Resumen: En los últimos años, el desarrollo de la domótica ha aumentado gracias al uso de las capacidades de la Internet de las Cosas (IoT, por sus siglas en inglés) que proveen tecnologías emergentes como Raspberry Pi. Esto permite automatizar tareas en casa o monitorear parámetros específicos. Este artículo propone una mejora en la interacción entre el sistema domótico inteligente y el usuario final utilizando un asistente de voz inteligente en lugar de aplicaciones móviles o una plataforma web local. Además, se exploran otras fuentes de información para pronósticos meteorológicos, como las interfaces de programación de aplicaciones (API) que proporcionan este servicio. Palabras-clave: Raspberry Pi; Asistente de voz inteligente; Clima; Alexa. Using the Alexa virtual assistant as an interaction tool for climate monitoring in smart homes by Raspberry Pi and DarkSky API

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Smart Home Device Security: A Survey of Smart Home Authentication Methods with a Focus on Mutual Authentication and Key Management Practices

Raju¹,

Moh²

2022

Cybersecurity in Smart Homes

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Smart Connected Homes

Cited by 11 publications

References 25 publications

PRASH: A Framework for Privacy Risk Analysis of Smart Homes

PRASH: A Framework for Privacy Risk Analysis of Smart Homes

Uso del asistente virtual Alexa como herramienta de interacción para el monitoreo de clima en hogares inteligentes por medio de Raspberry Pi y DarkSky API

Smart Home Device Security: A Survey of Smart Home Authentication Methods with a Focus on Mutual Authentication and Key Management Practices

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