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Consumer-Friendly Methods for Privacy Protection Against Cleaning Robots

Wuwang, Yanxiu 1; Schiefer, Gunther ORCID iD icon 1
1 Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB), Karlsruher Institut für Technologie (KIT)


As Internet of Things (IoT) technologies enter the consumer market, smart cleaning robots have gained high attention and usage in households. However, consumers behave differently even if many claim they are concerned about smart robot privacy issues. In this paper, we attempt to discover effective measures for average consumers to guard against potential privacy intrusions brought by cleaning robots. We defined our target devices, provided an ideal smart home network topology and established our threat model. We documented network redirection and analytic methods we used during our research. We categorized existing privacy protection methods and described their general procedures. We assessed and evaluated the protection methods against three aspects: protection effectiveness, functionality loss and consumer-friendliness. In the end we performed a tabular qualitative comparison and expressed our vision towards privacy protection against cleaning robots.

Zugehörige Institution(en) am KIT Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2022
Sprache Englisch
Identifikator ISBN: 978-3-031-21311-3
ISSN: 0302-9743, 1611-3349
KITopen-ID: 1000156108
Erschienen in Attacks and Defenses for the Internet-of-Things – 5th International Workshop, ADIoT 2022, Copenhagen, Denmark, September 30, 2022, Revised Selected Papers. Ed.: W. Li
Veranstaltung 5th International Workshop on Attacks and Defenses for Internet-of-Things (ADIoT 2022), Kopenhagen, Dänemark, 30.09.2022
Verlag Springer Nature Switzerland
Seiten 102–121
Serie Lecture Notes in Computer Science (LNCS) ; 13745
Vorab online veröffentlicht am 11.12.2022
Schlagwörter cleaning robot, privacy, protection, consumer, internet of things
Nachgewiesen in Dimensions
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