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Evaluating the Security and Privacy Risk Postures of Virtual Assistants

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arxiv 2312.14633 v1 pith:6UK3VLD7 submitted 2023-12-22 cs.CR cs.SE

classification cs.CRcs.SE
keywords securityprivacyassistantsaccessanalysisposturesusedvirtual
verification ladder T0 review T1 audit T2 compute T3 formal
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Virtual assistants (VAs) have seen increased use in recent years due to their ease of use for daily tasks. Despite their growing prevalence, their security and privacy implications are still not well understood. To address this gap, we conducted a study to evaluate the security and privacy postures of eight widely used voice assistants: Alexa, Braina, Cortana, Google Assistant, Kalliope, Mycroft, Hound, and Extreme. We used three vulnerability testing tools, AndroBugs, RiskInDroid, and MobSF, to assess the security and privacy of these VAs. Our analysis focused on five areas: code, access control, tracking, binary analysis, and sensitive data confidentiality. The results revealed that these VAs are vulnerable to a range of security threats, including not validating SSL certificates, executing raw SQL queries, and using a weak mode of the AES algorithm. These vulnerabilities could allow malicious actors to gain unauthorized access to users' personal information. This study is a first step toward understanding the risks associated with these technologies and provides a foundation for future research to develop more secure and privacy-respecting VAs.

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  1. Multi-Tool Analysis of User Interface & Accessibility in Deployed Web-Based Chatbots

    cs.HC 2025-06 conditional novelty 5.0 of 10

    In a four-tool audit of 106 web chatbots, over 80 percent showed critical accessibility failures and tool agreements were inconsistent, but the sample and tool independence limit the strength of the specific numbers.

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