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An Empirical Analysis of Smart Connected Home Data
Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0003-0546-072X
Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0002-8512-2976
Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0003-0998-6585
2018 (English)In: Internet of Things – ICIOT 2018, Springer, 2018, p. 134-149Conference paper, Published paper (Refereed)
Abstract [en]

The increasing presence of heterogeneous Internet of Things devices inside the home brings with it added convenience and value to the householders. At the same time, these devices tend to be Internet-connected and continuously monitor and collect data about the residents and their daily lifestyle activities. Such data can be of a sensitive nature, given that the house is the place where privacy is naturally expected. To gain insight into this state of affairs, we empirically investigate the privacy policies of 87 different categories of commercial smart home devices in terms of data being collected. This is done using a combination of manual and data mining techniques. The overall contribution of this work is a model that identifies and categorizes smart connected home data in terms of its collection mode, collection method, and collection phase. Our findings bring up several implications for smart connected home privacy, which include the need for better security controls to safeguard the privacy of the householders.

Place, publisher, year, edition, pages
Springer, 2018. p. 134-149
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 10972
Keywords [en]
Smart home, IoT, Data model, Privacy policies
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mau:diva-12509DOI: 10.1007/978-3-319-94370-1_10Scopus ID: 2-s2.0-85049026562Local ID: 26281OAI: oai:DiVA.org:mau-12509DiVA, id: diva2:1409556
Conference
International Conference on Internet of Things (ICIOT 2018), Seattle, USA (June 25 - June 30)
Available from: 2020-02-29 Created: 2020-02-29 Last updated: 2024-02-05Bibliographically approved
In thesis
1. Smart connected homes: concepts, risks, and challenges
Open this publication in new window or tab >>Smart connected homes: concepts, risks, and challenges
2018 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The growth and presence of heterogeneous connected devices inside the home have the potential to provide increased efficiency and quality of life to the residents. Simultaneously, these devices tend to be Internet-connected and continuously monitor, collect, and transmit data about the residents and their daily lifestyle activities. Such data can be of a sensitive nature, such as camera feeds, voice commands, physiological data, and more. This data allows for the implementation of services, personalization support, and benefits offered by smart home technologies. Alas, there has been a rift of security and privacy attacks on connected home devices that compromise the security, safety, and privacy of the occupants. In this thesis, we provide a comprehensive description of the smart connected home ecosystem in terms of its assets, architecture, functionality, and capabilities. Especially, we focus on the data being collected by smart home devices. Such description and organization are necessary as a precursor to perform a rigorous security and privacy analysis of the smart home. Additionally, we seek to identify threat agents, risks, challenges, and propose some mitigation approaches suitable for home environments. Identifying these is core to characterize what is at stake, and to gain insights into what is required to build more robust, resilient, secure, and privacy-preserving smart home systems. Overall, we propose new concepts, models, and methods serving as a foundation for conducting deeper research work in particular linked to smart connected homes. In particular, we propose a taxonomy of devices; classification of data collected by smart connected homes; threat agent model for the smart connected home; and identify challenges, risks, and propose some mitigation approaches.

Place, publisher, year, edition, pages
Malmö university. Faculty of Technology and Society, 2018
Series
Studies in Computer Science ; 7
Keywords
Smart Connected Homes, Internet of Things, Smart Home Devices, Data Lifecycle, Security Risks, Privacy Management, Vulnerability Assessment, Security Mitigations, Threat Agents, Smart Home Services, System Architecture
National Category
Engineering and Technology
Identifiers
urn:nbn:se:mau:diva-7793 (URN)10.24834/2043/25061 (DOI)25061 (Local ID)9789171049292 (ISBN)9789171049308 (ISBN)25061 (Archive number)25061 (OAI)
Presentation
2018-09-03, Storm, Gäddan, 15:15 (English)
Opponent
Note

Note: The papers are not included in the fulltext online.

Available from: 2020-02-28 Created: 2020-02-28 Last updated: 2024-03-18Bibliographically approved
2. On Privacy and Security in Smart Connected Homes
Open this publication in new window or tab >>On Privacy and Security in Smart Connected Homes
2021 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The growth and presence of heterogeneous sensor-equipped Internet-connected devices inside the home can increase efficiency and quality of life for the residents. Simultaneously, these devices continuously collect, process, and transmit data about the residents and their daily lifestyle activities to unknown parties outside the home. Such data can be sensitive and personal, leading to increasingly intimate insights into private lives. This data allows for the implementation of services, personalization support, and benefits offered by smart home technologies. Alas, there has been a surge of cyberattacks on connected home devices that essentially compromise privacy and security of the residents.

Providing privacy and security is a critical issue in smart connected homes. Many residents are concerned about unauthorized access into their homes and about the privacy of their data. However, it is typically challenging to implement privacy and security in a smart connected home because of its heterogeneity of devices, the dynamic nature of the home network, and the fact that it is always connected to the Internet, amongst other things. As the numbers and types of smart home devices are increasing rapidly, so are the risks with these devices. Concurrently, it is also becoming increasingly challenging to gain a deeper understand- ing of the smart home. Such understanding is necessary to build a more privacy-preserving and secure smart connected home. Likewise, it is needed as a precursor to perform a comprehensive privacy and security analysis of the smart home.

In this dissertation, we render a comprehensive description and account of the smart connected home that can be used for conducting risk analysis. In doing so, we organize the underlying smart home devices ac- cording to their functionality, identify their data-collecting capabilities, and survey the data types being collected by them. Such is done using the technical specification of commercial devices, including their privacy policies. This description is then leveraged for identifying threats and for analyzing risks present in smart connected homes. Such is done by analyzing both scholarly literature and examples from the industry, and leveraging formal modeling. Additionally, we identify malicious threat agents and mitigations that are relevant to smart connected homes. This is performed without limiting the research and results to a particular configuration and type of smart home.

This research led to three main findings. First, the majority of the surveyed commercial devices are collecting instances of sensitive and personal data but are prone to critical vulnerabilities. Second, there is a shortage of scientific models that capture the complexity and heterogeneity of real-world smart home deployments, especially those intended for privacy risk analysis. Finally, despite the increasing regulations and attention to privacy and security, there is a lack of proactive and integrative approaches intended to safeguard privacy and security of the residents. We contributed to addressing these three findings by developing a framework and models that enable early identification of threats, better planning for risk management scenarios, and mitigation of potential impacts caused by attacks before they reach the homes and compromise the lives of the residents.

Overall, the scientific contributions presented in this dissertation help deepen the understanding and reasoning about privacy and security concerns affecting smart connected homes, and contributes to advancing the research in the area of risk analysis as applied to such systems.

Place, publisher, year, edition, pages
Malmö: Malmö universitet, 2021. p. 66
Series
Studies in Computer Science
Keywords
smart connected homes, Internet of Things, smart homes devices, smart home data, threat identification, risk analysis, privacy, security, vulnerability assessment, mitigations, threat agents
National Category
Computer Sciences
Identifiers
urn:nbn:se:mau:diva-39619 (URN)10.24834/isbn.9789178771646 (DOI)978-91-7877-163-9 (ISBN)978-91-7877-164-6 (ISBN)
Public defence
2021-01-11, D138 Orkanen och Zoom, Malmö University, Malmö, 13:15 (English)
Opponent
Supervisors
Note

Note: The papers are not included in the fulltext online

Available from: 2021-01-21 Created: 2021-01-21 Last updated: 2024-03-04Bibliographically approved

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Bugeja, JosephJacobsson, AndreasDavidsson, Paul

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