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Threat Analysis of Smart Home Assistants Involving Novel Acoustic Based Attack-Vectors

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Threat Analysis of Smart Home Assistants Involving Novel Acoustic Based Attack-Vectors Master of Science in Engineering: Computer Security June 2019 Threat Analysis of Smart Home Assistants Involving Novel Acoustic Based Attack-Vectors Adam Björkman Max Kardos Faculty of Computing, Blekinge Institute of Technology, 371 79 Karlskrona, Sweden This thesis is submitted to the Faculty of Computing at Blekinge Institute of Technology in partial fulfilment of the requirements for the degree of Master of Science in Engineering: Computer Security. The thesis is equivalent to 20 weeks of full time studies. The authors declare that they are the sole authors of this thesis and that they have not used any sources other than those listed in the bibliography and identified as references. They further declare that they have not submitted this thesis at any other institution to obtain a degree. Contact Information: Author(s): Adam Björkman E-mail: [email protected] Max Kardos E-mail: [email protected] University advisers: Assistant Professor Fredrik Erlandsson Assistant Professor Martin Boldt Department of Computer Science and Engineering Faculty of Computing Internet : www.bth.se Blekinge Institute of Technology Phone : +46 455 38 50 00 SE–371 79 Karlskrona, Sweden Fax : +46 455 38 50 57 Abstract Background. Smart home assistants are becoming more common in our homes. Often taking the form of a speaker, these devices enable communication via voice commands. Through this communication channel, users can for example order a pizza, check the weather, or call a taxi. When a voice command is given to the assistant, the command is sent to cloud services over the Internet, enabling a multi- tude of functions associated with risks regarding security and privacy. Furthermore, with an always active Internet connection, smart home assistants are a part of the Internet of Things, a type of historically not secure devices. Therefore, it is crucial to understand the security situation and the risks that a smart home assistant brings with it. Objectives. This thesis aims to investigate and compile threats towards smart home assistants in a home environment. Such a compilation could be used as a foundation during the creation of a formal model for securing smart home assistants and other devices with similar properties. Methods. Through literature studies and threat modelling, current vulnerabili- ties towards smart home assistants and systems with similar properties were found and compiled. A few vulnerabilities were tested against two smart home assistants through experiments to verify which vulnerabilities are present in a home environ- ment. Finally, methods for the prevention and protection of the vulnerabilities were found and compiled. Results. Overall, 27 vulnerabilities towards smart home assistants and 12 towards similar systems were found and identified. The majority of the found vulnerabilities focus on exploiting the voice interface. In total, 27 methods to prevent vulnerabili- ties in smart home assistants or similar systems were found and compiled. Eleven of the found vulnerabilities did not have any reported protection methods. Finally, we performed one experiment consisting of four attacks against two smart home assis- tants with mixed results; one attack was not successful, while the others were either completely or partially successful in exploiting the target vulnerabilities. Conclusions. We conclude that vulnerabilities exist for smart home assistants and similar systems. The vulnerabilities differ in execution difficulty and impact. How- ever, we consider smart home assistants safe enough to usage with the accompanying protection methods activated. Keywords: Smart home assistants, threats, voice interface, vulnerability, exploit i Sammanfattning Bakgrund. Smarta hemassistenter blir allt vanligare i våra hem. De tar ofta formen av en högtalare och möjliggör kommunikation via röstkommandon. Genom denna kommunikationskanal kan användare bland annat beställa pizza, kolla väderleken eller beställa en taxi. Röstkommandon som ges åt enheten skickas till molntjänster över internet och möjliggör då flertalet funktioner med associerade risker kring säker- het och integritet. Vidare, med en konstant uppkoppling mot internet är de smarta hemassistenterna en del av sakernas internet; en typ av enhet som historiskt sett är osäker. Således är det viktigt att förstå säkerhetssituationen och riskerna som medföljer användningen av smarta hemassistenter i en hemmiljö. Syfte. Syftet med rapporten är att göra en bred kartläggning av hotbilden mot smarta hemassistenter i en hemmiljö. Dessutom kan kartläggningen fungera som en grund i skapandet av en modell för att säkra både smarta hemassistenter och andra enheter med liknande egenskaper. Metod. Genom literaturstudier och hotmodellering hittades och sammanställdes nuvarande hot mot smarta hemassistenter och system med liknande egenskaper. Nå- gra av hoten testades mot två olika smarta hemassistenter genom experiment för att säkerställa vilka hot som är aktuella i en hemmiljö. Slutligen hittades och sam- manställdes även metoder för att förhindra och skydda sig mot sårbarheterna. Resultat. Totalt hittades och sammanställdes 27 stycken hot mot smarta hemassis- tenter och 12 mot liknande system. Av de funna sårbarheterna fokuserar majoriteten på manipulation av röstgränssnittet genom olika metoder. Totalt hittades och sam- manställdes även 27 stycken metoder för att förhindra sårbarheter i smarta hemas- sistenter eller liknande system, varav elva sårbarheter inte förhindras av någon av dessa metoder. Slutligen utfördes ett experiment där fyra olika attacker testades mot två smarta hemassistenter med varierande resultat. En attack lyckades inte, medan resterande antingen helt eller delvis lyckades utnyttja sårbarheterna. Slutsatser. Vi konstaterar att sårbarheter finns för smarta hemassistenter och för liknande system. Sårbarheterna varierar i svårighet att uföra samt konsekvens. Dock anser vi att smarta hemassistenter är säkra nog att använda med medföljande sky- ddsmetoder aktiverade. Nyckelord: Smarta hemassistenter, hotbild, röstgränssnitt, sammanställning, at- tack iii Acknowledgments We want to thank Martin Boldt and Fredrik Erlandsson for their supervision and guidance during the thesis. We also want to thank Knowit Secure, its employees, and our company supervisor Mats Persson, for their motivation and expertise. Finally, we would like to thank our families for their unrelenting support. v Contents Abstract i Sammanfattning iii Acknowledgments v 1 Introduction 1 1.1 Problem Description and Research Gap . 2 1.2 Aim and Research Questions . 2 1.3 Scope and Limitations . 3 1.4 Document Outline . 3 2 Background 5 2.1 Smart Home Assistant . 5 2.1.1 Amazon Echo . 6 2.1.2 Google Home . 6 2.2 Application Programming Interface . 6 2.3 Automatic Speech Recognition . 7 2.4 Speaker Recognition . 7 2.5 Threats Towards Smart Home Assistants . 7 2.5.1 Threat Mitigation . 8 2.5.2 Threat Classification . 8 2.5.3 Vulnerability Databases . 8 2.6 Threat Modelling . 8 2.6.1 STRIDE . 8 3 Related Works 11 4 Method 13 4.1 Systematic Literature Review . 13 4.1.1 Database Selection . 13 4.1.2 Selection Criteria . 14 4.1.3 Quality Assessment . 14 4.1.4 Data Extraction Strategy and Synthesis . 15 4.2 Threat Assessment of Smart Home Assistants . 15 4.2.1 Keywords . 15 4.2.2 Quality Assessment Criteria . 16 4.3 Threat Assessment of Similar Systems . 17 vii 4.3.1 Keywords . 17 4.3.2 Quality Assessment Criteria . 18 4.4 Threat Modelling . 18 4.4.1 Generalised STRIDE Analysis . 18 4.5 Experiment Design . 19 4.5.1 Experiment Environment . 20 4.5.2 Functionality Test of SHA . 20 4.5.3 Chosen Attacks . 20 4.5.4 Experiment Layout . 20 4.6 Experiment Execution . 21 4.6.1 Replay Attack . 22 4.6.2 Adversarial Attack Using Phsychoacoustic Hiding . 23 4.6.3 Harmful API Behaviour . 24 4.6.4 Unauthorised SHA Functionality . 25 5 Results 27 5.1 Threat Status of Smart Home Assistants . 27 5.1.1 Vulnerabilities . 28 5.1.2 Protection Methods . 31 5.2 Threat Status on Similar Systems . 33 5.2.1 Vulnerabilities . 34 5.2.2 Protection Methods . 36 5.3 Threat Modelling . 37 5.3.1 Possible Threats . 37 5.3.2 Protection Methods . 39 5.4 Threat Validation on SHA . 40 5.4.1 Replay Attack . 42 5.4.2 Harmful API Behaviour . 42 5.4.3 Unauthorised SHA Functionality . 43 5.4.4 Threat Validation Summary . 44 6 Analysis and Discussion 47 6.1 Research Implications . 47 6.2 Research Question Analysis . 48 6.3 Literature Reviews . 49 6.4 Threat Modelling . 50 6.5 Experiments . 51 6.5.1 Features Not Supported . 51 6.5.2 Vulnerability Score . 52 7 Conclusions and Future Work 53 7.1 Future Works . 53 Appendices 63 A Permission Forms 65 A.1 Permission IEEEXplore . 65 viii B Scripts 67 B.1 Script for Search Result Extraction . 67 ix List of Figures 2.1 A command flow example as found in an Amazon SHA ©2018 IEEE. See Appendix A.1 for permission. 6 4.1 A generalised system targeted in the STRIDE analysis process . 19 5.1 The amount of protection methods addressing each vulnerability found during threat assessment of SHAs . 33 5.2 The amount of protection methods addressing each vulnerability found during threat assessment of similar systems . 37 5.3 The amount of protection methods addressing each SHA vulnerability generated during the threat modelling process . 40 xi List of Tables 4.1 Form describing the data extracted from the literature review papers 15 4.2 Search keywords, sorted by category, used in the threat assessment of home assistants . 16 4.3 Search keywords, sorted by category, used in the threat assessment of systems similar to smart home assistants . 17 4.4 Attacks and their corresponding target, found during the threat as- sessments, chosen for the experimentation phase . 21 5.1 The amount of papers found through each database for the threat assessment of smart home assistants . 27 5.2 Papers remaining for the threat assessment of smart home assistants, after application of selection criteria . 28 5.3 Papers remaining for the threat assessment of smart home assistants, after application of quality assessment criteria .
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