The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
“Alexa, Can I Trust You?”
Open accessAbstract
Several recent incidents highlight significant security and privacy risks associated with intelligent virtual assistants (IVAs). Better diagnostic testing of IVA ecosystems can reveal such vulnerabilities and lead to more trustworthy systems.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Currently, it is possible to develop apps for consumer voice assistants (eg, skills for Amazon Alexa or actions for Google Assistant). However, these products may be of privacy [76] or safety concerns [77].”
From Voice-Based Conversational Agents for the Prevention and Management of Chronic and Mental Health Conditions: Systematic Literature Review (2021) · cites this paper as [77]
In the citing paper
“users still lack trust in voice-based chatbots [61] due to privacy concerns and security vulnerabilities [62]”
From Interacting with a Chatbot-Based Advising System: Understanding the Effect of Chatbot Personality and User Gender on Behavior (2022) · cites this paper as [62]
In the citing paper
“AI has recently been the objective of substantial interest from policy-making and regulatory bodies, as well as in discussions and reflections on ethics, privacy management and trust [21].”
From Future directions for chatbot research: An interdisciplinary research agenda (2021) · cites this paper as [21]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A survey of techniques for internet traffic classification using machine learning
Nguyen, T. T. T., & Armitage, G. (2008) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2008.080406 · Cited by 1,664
Rahbar, A. G., & Yang, O. W. W. (2008) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2008.080408 · Cited by 676
Guide to protecting the confidentiality of Personally Identifiable Information (PII)
McCallister, E., Grance, T., & Scarfone, K. A. (2010) · doi:10.6028/nist.sp.800-122 · Cited by 337
Realtime Encrypted Traffic Identification using Machine Learning
Gu, C., Zhang, S., & Sun, Y. (2011) · Journal of Software · doi:10.4304/jsw.6.6.1009-1016 · Cited by 20
Flagged first, then by citations
Research works printed but not linked: 9
- anderson, 2017, How Burger King Revealed the Hackability of Voice Assistants
- opam, 2017, Google's Super Bowl Ad Accidentally Set off a Lot of Google Homes
- york, 2016, Dyn Statement on 10/21/2016 DDoS Attack
- owens, 2016, Stranger Hacks Family's Baby Monitor and Talks to Child at Night, GlobeCOM San Francisco
- rodionova, 2017, Burger King Ad Backfires after Asking Google What's in a Whopper and Is told'Cyanide, The Independent
- wood, 2017, Devices Sprout Ears: What Do Alexa and Siri Mean for Privacy?, The Christian Science Monitor
- 2017, Exploring the Amazon Echo Dot Part 1 Intercepting Firmware Updates
- liptak, 2017, Amazon's Alexa Started Ordering People Dollhouses after Hearing Its Name on TV
- 2016, Gartner Says Worldwide Spending on VPA-Enabled Wireless Speakers Will Top $2 Billion by 2020
Cited by
Sorted by citations
Items 201–228 of 228
Speech Assistant System With Local Client and Server Devices to Guarantee Data Privacy
Hirsch, H. (2022) · Frontiers in Computer Science · doi:10.3389/fcomp.2022.778367
Forensic Data Analysis using the Case Studies on Anti Forensic Devices
Kavya, P., Ganiga, K. G., Chethana, L., Srivatsava, A., Kumar, D. V. S. S., & Dr Pooja Nayak, S. (2022) · International Journal of Engineering Research in Computer Science and Engineering · doi:10.36647/ijercse/09.09.art009
Forensic Data Analysis Using the Case Studies on Anti Forensic Devices
Kavya, P., Ganiga, K. G., Chethana, L., Srivatsava, A., Kumar, D. V. S. S., & Dr Pooja Nayak, S. (2022) · International Journal of Engineering Research in Computer Science and Engineering · doi:10.36647/ijercse/09.08.art011
Intelligent Virtual Assistants (IVAs): Trust and Zero Trust
Wylde, A. (2023) · Lecture notes in networks and systems · doi:10.1007/978-3-031-37963-5_8
Anselmi, G., Mandalari, A. M., Lazzaro, S., & Angelis, V. D. (2023) · doi:10.1145/3615591.3615677
The Impact of Perceived Surveillance on Continuance Usage Intention of Voice Assistants
Abdussami, R., & Candiwan, C. (2023) · Syntax Literate Jurnal Ilmiah Indonesia · doi:10.36418/syntax-literate.v8i9.13590
Ramanjinamma, M. G. (2023) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2023.56658
Privacy Respecting Design Principles for Smart Home DevicesPreprint
Murphy, R., Keedwell, E. C., & Hartley, S. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4643647
Automated Methods for Modeling Thinking and Reasoning Based on the Partial Model Theory
Palchunov, D. E. (2023) · International Scientific-Technical Conference on Actual Problems of Electronic Instrument Engineering (APEIE) · doi:10.1109/apeie59731.2023.10347648
AI based Chatbot for Students FAQs
Bhujbal, M. P. M., Gavandhare, M. R. A., Gobe, M. P. R., & Ghodake, R. G. (2022) · International journal of research in science & engineering · doi:10.55529/ijrise.21.45.49
Elmasry, A. (2024) · Al-Mağallah Al-ʿilmiyyaẗ Lil-Maktabāt wa Al-Waṯā'iq wa Al-Ma'lūmāt · doi:10.21608/jslmf.2022.160027.1132
Measuring Impact on Confidence in Institutions by their Use of Software Components
Paulin, A. (2024) · Central and Eastern European eDem and eGov Days · doi:10.1145/3670243.3670249
Three Essays on Artificial Intelligence Adoption and Use
Nguyen, Q. (2019) · University of North Texas Digital Library (University of North Texas) · doi:10.12794/metadc1538732
Perspective Chapter: Social Awareness in HRI
Barretto, M. R. P., & Pereira-Barretto, V. (2025) · IntechOpen eBooks · doi:10.5772/intechopen.1008996
Enhancing programming literacy through educational data mining and problem-solving analysis
Kumar, C. S. S., Paramasivam, D., Baskar, A., Kannan, G., & Rajan, Y. S. (2025) · AIP conference proceedings · doi:10.1063/5.0262326
Exploring Smart Speaker Disclosure and Adoption Intentions: A Privacy Adoption Calculus Perspective
Vanderkooi, D., Mashatan, A., & Turetken, O. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-87499-4_4
Virtual Personal Desktop Assistant
Mane, P. T., Adhude, T., Bansode, K., Pimple, P., Khairnar, P., & Sarade, R. (2025) · doi:10.38124/ijisrt/25jun487
Shamim, U., Woodcock, A., Nair, A., & Spinelli, G. (2025) · Disability and Rehabilitation Assistive Technology · doi:10.1080/17483107.2025.2530195
Desktop-Based Virtual Assistant Using Python Based on Natural Language Processing
Sharma, V. K., Shukla, N., Shahi, S., Pandey, S. K., & Gupta, S. G. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-96-6063-6_3
Djonkam, K. A. S., Rey, G., & Tigli, J. (2025) · Applied Sciences · doi:10.3390/app15179638
CAMPUS-ONE- An AI Agent for Institutional Support
D, K. M., Dsouza, B. J., Akshitha, B., Chandana, B., & N, S. K. (2025) · International Conference on IoT Based Control Networks and Intelligent Systems (ICICNIS) · doi:10.1109/icicnis66685.2025.11315812
Neto, A., Gomes, L., & Vale, Z. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-01234-0_26
Nutsugbodo, R. Y., Arthur-Amissah, A., & Ayentimi, D. T. (2026) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-80686-169-920261006
La confiance en contexte numérique : étude de ses déterminants et lien avec les émotions
Cho, J. A. S. (2022) · theses.fr (ABES) · doi:10.70675/bd8159c5zfaf1z4358z9c77zec68bcf24150
Nathvani, A., Kaarve, C., Velani, K., & Verma, S. (2026) · International Conference on Emerging Technologies and Future Innovations (ETFI) · doi:10.1109/etfi68128.2026.11484715
Ge, J., Huang, H., Li, B., He, Y., & Rui, J. (2026) · Ad Hoc Networks · doi:10.1016/j.adhoc.2026.104339
Look at Me When I Talk to You: A Video Dataset to Enable Voice Assistants to Recognize Errors
Cuadra, A., Lee, H., Cho, J., & Ju, W. (2021) · arXiv · doi:10.48550/arxiv.2104.07153 · Cited by 5
Metadata
- Authors
- Chung, H., Iorga, M., Voas, J., & Lee, S.
- Affiliations
- National Institute of Standards and Technology (US)
- Korea University (KR)
- Venue
- Computer
- Published
- 2017
- Volume
- 50
- Issue
- 9
- Pages
- 100-104
- ISSN
- 0018-9162 (ISSN-L)
- 1558-0814
- PMC
- PMC5714311
- OpenAlex
- W2759491482
- Cited by
- 230
- References
- 4
- Citations by year
- 2026: 4 · 2025: 15 · 2024: 12 · 2023: 27 · 2022: 38 · 2021: 49 · 2020: 42 · 2019: 28 · 2018: 14 · 2017: 1
- FWCI
- 59.54
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Computer (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Hardware and Architecture › Security and Verification in Computing
- Keywords
- virtual assistants, security vulnerabilities, privacy risks, trustworthiness, diagnostic testing, voice assistants
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
