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Security evaluation of smart door locks
KTH, School of Electrical Engineering and Computer Science (EECS).
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Smart locks are a part of the up and rising Internet of Things (IoT). They’re used as a complement to traditional locks in order to make it easier to share keys electronically, rather than physically. Smart door locks are mounted on a existing door and enables users to control the state of the lock with their smartphone. In this report we want to investigate if previous acknowledged attacks on smart locks still exists in today’s available locks for the Swedish market. By studying previous work and conduct a threat model, we create attacks to apply on the locks in order to answer what deficiencies exist in smart door locks today.The results conclude that there are several deficiencies in today’s smart locks, where the most severe has been reported under responsible disclosure to the manufacturer. The locks investigated shows vulnerabilities in state consistency, password policies and password reset mechanism.

Abstract [sv]

Smarta lås är en del av sakernas internet (IoT). Smarta lås används som ett komplement till traditionella lås för att göra det enklare att dela nycklar elektroniskt. Smarta dörrlås monteras på befintlig dörr och gör det möjligt för användare att styra låset med sin smartphone. I den här rapporten vill vi undersöka om tidigare kända attacker på smarta lås fortfarande finns i dagens tillgängliga lås på svenska marknaden. Genom att studera tidigare arbete och genomföra en hotmodell skapar vi attacker för att applicera på låsen, för att kunna svara på vilka brister som finns i smarta dörrlås idag.

Resultatet drar slutsatsen att det finns flera brister i dagens smarta lås, där de allvarligaste har rapporterats till tillverkaren. De undersökta låsen visar sårbarhet i konsistens mellan tillstånd, lösenordspolicys och lösenordsåterställning.

Place, publisher, year, edition, pages
2019. , p. 69
Series
TRITA-EECS-EX ; 2019:300
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-254962OAI: oai:DiVA.org:kth-254962DiVA, id: diva2:1336796
Subject / course
Computer Science
Educational program
Master of Science - Computer Science
Supervisors
Examiners
Available from: 2019-07-10 Created: 2019-07-10 Last updated: 2019-07-10Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
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  • vancouver
  • Other style
More styles
Language
  • de-DE
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  • Other locale
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Output format
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