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Smart connected homes: concepts, risks, and challenges
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0003-0546-072X
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 [en]
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: urn:nbn:se:mau:diva-7793DOI: 10.24834/2043/25061Local ID: 25061ISBN: 9789171049292 (print)ISBN: 9789171049308 (electronic)OAI: oai:DiVA.org:mau-7793DiVA, id: diva2:1404734
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
List of papers
1. Smart Connected Homes
Open this publication in new window or tab >>Smart Connected Homes
2018 (English)In: Internet of Things A to Z: Technologies and Applications / [ed] Qusay F. Hassan, John Wiley & Sons, 2018, p. 359-384Chapter in book (Other academic)
Place, publisher, year, edition, pages
John Wiley & Sons, 2018
Keywords
smart connected home, Internet of Things, smart home services, system architectures, security, privacy, reliability, usability, interoperability
National Category
Engineering and Technology
Identifiers
urn:nbn:se:mau:diva-10482 (URN)10.1002/9781119456735.ch13 (DOI)25158 (Local ID)978-1-119-45674-2 (ISBN)25158 (Archive number)25158 (OAI)
Available from: 2020-02-28 Created: 2020-02-28 Last updated: 2022-08-29Bibliographically approved
2. On Privacy and Security Challenges in Smart Connected Homes
Open this publication in new window or tab >>On Privacy and Security Challenges in Smart Connected Homes
2016 (English)In: Proceedings: 2016 European Intelligence and Security Informatics Conference, IEEE, 2016Conference paper, Published paper (Refereed)
Abstract [en]

Smart homes have become increasingly popular for IoT products and services with a lot of promises for improving the quality of life of individuals. Nevertheless, the heterogeneous, dynamic, and Internet-connected nature of this environment adds new concerns as private data becomes accessible, often without the householders’ awareness. This accessibility alongside with the rising risks of data security and privacy breaches, makes smart home security a critical topic that deserves scrutiny. In this paper, we present an overview of the privacy and security challenges directed towards the smart home domain. We also identify constraints, evaluate solutions, and discuss a number of challenges and research issues where further investigation is required.

Place, publisher, year, edition, pages
IEEE, 2016
Keywords
smart home, security, privacy, IoT
National Category
Computer Systems
Identifiers
urn:nbn:se:mau:diva-12630 (URN)10.1109/EISIC.2016.044 (DOI)000411272300033 ()2-s2.0-85017282760 (Scopus ID)21507 (Local ID)21507 (Archive number)21507 (OAI)
Conference
European Intelligence and Security Informatics Conference (EISIC), Uppsala, Sweden (August 17-19)
Available from: 2020-02-29 Created: 2020-02-29 Last updated: 2024-02-05Bibliographically approved
3. An Analysis of Malicious Threat Agents for the Smart Connected Home
Open this publication in new window or tab >>An Analysis of Malicious Threat Agents for the Smart Connected Home
2017 (English)In: Proceeding of 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), IEEE, 2017Conference paper, Published paper (Refereed)
Abstract [en]

Smart connected home systems aim to enhance the comfort, convenience, security, entertainment, and health of the householders and their guests. Despite their advantages, their interconnected characteristics make smart home devices and services prone to various cybersecurity and privacy threats. In this paper, we analyze six classes of malicious threat agents for smart connected homes. We also identify four different motives and three distinct capability levels that can be used to group the different intruders. Based on this, we propose a new threat model that can be used for threat profiling. Both hypothetical and real-life examples of attacks are used throughout the paper. In reflecting on this work, we also observe motivations and agents that are not covered in standard agent taxonomies.

Place, publisher, year, edition, pages
IEEE, 2017
Keywords
Smart homes, Privacy, Terrorism, Computer security, Taxonomy, Home appliances, connected home, IoT, threat agent, threat agent motivations, threat agent capabilities
National Category
Engineering and Technology
Identifiers
urn:nbn:se:mau:diva-12595 (URN)10.1109/PERCOMW.2017.7917623 (DOI)000411208400111 ()2-s2.0-85020053641 (Scopus ID)22578 (Local ID)22578 (Archive number)22578 (OAI)
Conference
IEEE International Conference on Pervasive Computing and Communication (PerCom) 2017 - the First International Workshop on Pervasive Smart Living Spaces (PerLS 2017), Kona, Big Island, Hawaii, USA (March 13–17, 2017)
Available from: 2020-02-29 Created: 2020-02-29 Last updated: 2023-12-27Bibliographically approved
4. An Investigation of Vulnerabilities in Smart Connected Cameras
Open this publication in new window or tab >>An Investigation of Vulnerabilities in Smart Connected Cameras
2018 (English)In: 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), IEEE, 2018, p. 656-661Conference paper, Published paper (Refereed)
Abstract [en]

The Internet of Things is enabling innovative ser-vices promising added convenience and value in various domains such as the smart home. Increasingly, households, office envi-ronments and cities, are being fitted with smart camera systems aimed to enhance the security of citizens. At the same time, sev-eral systems being deployed suffer from weak security implemen-tations. Recognizing this, and to understand the extent of this situation, in this study we perform a global vulnerability assess-ment using the Shodan search engine and the Common Vulnera-bilities and Exposures database. This is done to detect smart con-nected cameras exposed on the Internet alongside their sensitive, potentially private, data being broadcasted. Furthermore, we discuss whether the discovered data can be used to compromise the safety and privacy of individuals, and identify some mitiga-tions that can be adopted. The results indicate that a significant number of smart cameras are indeed prone to diverse security and privacy vulnerabilities.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
IoT, IoT security, Shodan, smart connected cameras, smart connected homes, vulnerabilities
National Category
Engineering and Technology
Identifiers
urn:nbn:se:mau:diva-12708 (URN)10.1109/PERCOMW.2018.8480184 (DOI)000541062400110 ()2-s2.0-85056473592 (Scopus ID)26328 (Local ID)978-1-5386-3227-7 (ISBN)978-1-5386-3228-4 (ISBN)26328 (Archive number)26328 (OAI)
Conference
IEEE PerCom 2018 - Second International Workshop on Pervasive Smart Living Spaces (PerLS 2018), Athens, Greece (19 March - 23 March)
Available from: 2020-02-29 Created: 2020-02-29 Last updated: 2024-04-05Bibliographically approved
5. Functional Classification and Quantitative Analysis of Smart Connected Home Devices
Open this publication in new window or tab >>Functional Classification and Quantitative Analysis of Smart Connected Home Devices
2018 (English)In: 2018 Global Internet of Things Summit (GIoTS), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 144-149Conference paper, Published paper (Refereed)
Abstract [en]

The home environment is rapidly becoming more complex with the introduction of numerous and heterogeneous Internet of Things devices. This development into smart connected homes brings with it challenges when it comes to gaining a deeper understanding of the home environment as a socio-technical system. A better understanding of the home is essential to build robust, resilient, and secure smart home systems. In this regard, we developed a novel method for classifying smart home devices in a logical and coherent manner according to their functionality. Unlike other approaches, we build the categorization empirically by mining the technical specifications of 1,193 commercial devices. Moreover, we identify twelve capabilities that can be used to characterize home devices. Alongside the classification, we also quantitatively analyze the entire spectrum of commercial smart home devices in accordance to their functionality and capabilities. Overall, the categorization and analysis provide a foundation for identifying opportunities of generalizations and common solutions for the smart home.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
Global Internet of Things Summit
Keywords
classification, connected home, devices, IoT, smart home, survey, taxonomy, web mining
National Category
Engineering and Technology
Identifiers
urn:nbn:se:mau:diva-12487 (URN)10.1109/giots.2018.8534563 (DOI)000456099600039 ()2-s2.0-85059075949 (Scopus ID)26327 (Local ID)26327 (Archive number)26327 (OAI)
Conference
Global IoT Summit, Bilbao, Spain (June 4 - June 7)
Available from: 2020-02-29 Created: 2020-02-29 Last updated: 2023-12-15Bibliographically approved
6. An Empirical Analysis of Smart Connected Home Data
Open this publication in new window or tab >>An Empirical Analysis of Smart Connected Home Data
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
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 10972
Keywords
Smart home, IoT, Data model, Privacy policies
National Category
Engineering and Technology
Identifiers
urn:nbn:se:mau:diva-12509 (URN)10.1007/978-3-319-94370-1_10 (DOI)2-s2.0-85049026562 (Scopus ID)26281 (Local ID)26281 (Archive number)26281 (OAI)
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

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Bugeja, Joseph

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