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Fingerprinting Encrypted Voice Traffic on Smart Speakers with Deep Learning
[article]
2020
arXiv
pre-print
Preserved Fulltext
This paper investigates the privacy leakage of smart speakers under an encrypted traffic analysis attack, referred to as voice command fingerprinting. ...
In this attack, an adversary can eavesdrop both outgoing and incoming encrypted voice traffic of a smart speaker, and infers which voice command a user says over encrypted traffic. ...
Selcuk Uluagac, for their insightful comments on this paper. ...
arXiv:2005.09800v1
fatcat:5broa65upjgfrck3slpk5zn77m
Fine-hearing Google Home: why silence will not protect your privacy
2020
Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications
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Smart speakers and voice-based virtual assistants are used to retrieve information, interact with other devices, and command a variety of Internet of Things (IoT) nodes. ...
To this aim, smart speakers and voice-based assistants typically take advantage of cloud architectures: vocal commands of the user are sampled, sent through the Internet to be processed and transmitted ...
Conclusions and Future Works In this paper, we investigated the feasibility of adopting machine learning techniques to breach the privacy of users interacting with smart speakers or voice assistants. ...
doi:10.22667/jowua.2020.03.31.035
dblp:journals/jowua/CaputoVRMC20
fatcat:mp2aphhxm5dcjnpec6nx3vcxty
A Survey on Amazon Alexa Attack Surfaces
[article]
2021
arXiv
pre-print
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The success of Alexa is based on its effortless usability, but in turn, that has led to a lack of sufficient security. ...
Alexa's user-friendly, personalized vocal experience offers customers a more natural way of interacting with cutting-edge technology by allowing the ability to directly dictate commands to the assistant ...
speakers through multiple deep learning models. ...
arXiv:2102.11442v1
fatcat:kyo7jhjd2zen5o2ebd26wuj4na
Side channel attacks on smart home systems: A short overview
2017
IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
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Permanent repository link: http://openaccess.city.ac.uk/19447/ Link to published version: http://dx.Abstract-This paper provides an overview on side-channel attacks with emphasis on vulnerabilities in ...
This paper starts by reviewing side-channel attack categories, then it gives an overview on recent attack studies on different layers of a smart home and their malicious goals. ...
Voice communication is a common activity in every home. [28] proposed a novel attack to identify speakers despite encrypted voice communication. ...
doi:10.1109/iecon.2017.8217429
dblp:conf/iecon/AbrishamchiACB17
fatcat:p5l6yaht2fekbncffx6h2c4vyu
Paper Titles
2019
2019 IEEE 8th Global Conference on Consumer Electronics (GCCE)
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Linux The Flow Control in Unmanned Stores with Sensing Floor The Impact of "Surround Sound on Eye and Head Movement While Watching Moving Images The Implementation of Traffic Analytics Using Deep Learning ...
HSR Wireless Network Handover Mechanism for QoS Improvement on Control Plane Robust Detection and Recognition of Japanese Traffic Sign in the Complex Scenes Based on Deep Learning Robust Reflection Removal ...
doi:10.1109/gcce46687.2019.9015409
fatcat:6k3r6jixrvglrkrkzek636gb54
GCCE 2020 Subject Index
2020
2020 IEEE 9th Global Conference on Consumer Electronics (GCCE)
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Research for Unique Venue of Cultural Properties Made by Bricks in Japan
Research on the Less Stress Acquisition Method for the Activity Information of Actual Residents Using the International Standard ...
ECHONET Lite
Research on the Less Stress Acquisition Method for the Activity Information of Actual Residents Using the International Standard ECHONET Lite
S 3 7 A B C D E F G H I K L M N O P Q R S ...
Text Scoring for Collaborative Learning Big Traffic Data Analytics for Smart Urban Intelligent Traffic System Using Machine Learning Techniques Big Traffic Data Analytics for Smart Urban Intelligent Traffic ...
doi:10.1109/gcce50665.2020.9291796
fatcat:bmnnn7xnxrefhaneq262fe4i6u
Biometrics for Internet-of-Things Security: A Review
2021
Sensors
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The purpose of this review is to provide a comprehensive survey on the current biometrics research in IoT security, especially focusing on two important aspects, authentication and encryption. ...
As for encryption, biometric-cryptographic systems, which integrate biometrics with cryptography and take advantage of both to provide enhanced security for IoT, are thoroughly reviewed and discussed. ...
For example, despite the strong authentication performance offered by using iris, voice is clearly a better choice than iris in the authentication scenario of smart speakers. ...
doi:10.3390/s21186163
pmid:34577370
fatcat:urk3rlktjbahvdc5evaanqjn3y
Security and Privacy Analysis of Youth-Oriented Connected Devices
2022
Sensors
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This article focuses on analyzing the security and privacy of such devices to promote safe Internet use, especially by young people. ...
Our results help other researchers address these issues with a more global perspective. ...
In addition, knowledge of such security and privacy issues in connected devices will enable users to be aware of the threats associated with the use of these devices and to learn good usage practices to ...
doi:10.3390/s22113967
pmid:35684588
fatcat:ed7xm34h6fbsbbzeb4b5l5vmim
Spying on the Smart Home: Privacy Attacks and Defenses on Encrypted IoT Traffic
[article]
2017
arXiv
pre-print
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Our experiments show that traffic shaping can effectively and practically mitigate many privacy risks associated with smart home IoT devices. ...
We evaluate several strategies for mitigating the privacy risks associated with smart home device traffic, including blocking, tunneling, and rate-shaping. ...
Supervised machine learning can accurately fingerprint smart home devices using Internet traffic rates. ...
arXiv:1708.05044v1
fatcat:d7x4izf5w5eo5aa3hym27qfcau
Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things
[article]
2020
arXiv
pre-print
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Artificial intelligence (AI), especially deep learning, is now a proven success in various areas including computer vision, speech recognition, and natural language processing. ...
This paper presents a comprehensive survey on AIoT to show how AI can empower the IoT to make it faster, smarter, greener, and safer. ...
system for conferences), as well as the cloud computing with acceptable latency (e.g., on-line mode of smart voice assistant). ...
arXiv:2011.08612v1
fatcat:dflut2wdrjb4xojll34c7daol4
A Systematic Survey of Attack Detection and Prevention in Connected and Autonomous Vehicles
[article]
2022
arXiv
pre-print
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There are some surveys with a limited discussion on Attacks Detection and Prevention Systems (ADPS), but such surveys provide only partial coverage of different types of ADPS for CAVs. ...
The number of Connected and Autonomous Vehicles (CAVs) is increasing rapidly in various smart transportation services and applications due to many benefits to society, people, and the environment. ...
Deep learning techniques use artificial or deep neural networks, algorithms inspired by the human brain. ...
arXiv:2203.14965v1
fatcat:4orttcmbjfei5dbhsjnaovmm7a
SDN-Enabled FiWi-IoT Smart Environment Network Traffic Classification Using Supervised ML Models
2021
Photonics
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This paper, we propose a machine learning supervised network traffic classification scheduling model in SDN enhanced-FiWi-IoT that can intelligently learn and guarantee traffic based on its QoS requirements ...
We capture the different IoT and non-IoT device network traffic trace files based on the traffic flow and analyze the traffic traces to extract statistical attributes (port source and destination, IP address ...
network (WLAN) traffic, based on the quality of service class identification (QoS-CI) for traffic types such as voice, video, IoT and data. ...
doi:10.3390/photonics8060201
fatcat:xte7aviqrzdkrntp6mkgeq3qma
Non-Invasive Challenge Response Authentication for Voice Transactions with Smart Home Behavior
2020
Sensors
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Smart speakers, such as Alexa and Google Home, support daily activities in smart home environments. ...
The Coloured Petri Net model was created for synthetic data generation, and one month data were collected in test bed with real users. ...
Figure 2 . 2 Open Smart Speaker Architecture with non-invasive Authorization that is based on data-driven approach. ...
doi:10.3390/s20226563
pmid:33212905
pmcid:PMC7698362
fatcat:aotvt7hcavbzxepjap7cq5jxki
AI-Assisted Authentication: State of the Art, Taxonomy and Future Roadmap
[article]
2022
arXiv
pre-print
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With the emerging AI-assisted authentication schemes, our comprehensive survey provides an overall understanding on a high level, which paves the way for future research in this area. ...
In contrast to other relevant surveys, our research is the first of its kind to focus on the roles of AI in authentication. ...
Such neural networks are naturally compatible with ordinal problems like voice recognition. 1.1.2 Supervised, Semi-Supervised and Reinforcement Learning Supervised learning is one of the subcategories ...
arXiv:2204.12492v1
fatcat:vdeuhy63cvawjdhclricvkq42q
Towards Privacy Preserving IoT Environments: A Survey
2018
Wireless Communications and Mobile Computing
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However, with the increasing wide adoption of IoT, come significant privacy concerns to lose control of how our data is collected and shared with others. ...
IoT promises to enable a plethora of smart services in almost every aspect of our daily interactions and improve the overall quality of life. ...
Several strategies have been investigated to avoid the privacy risks associated with smart home traffic monitoring such as traffic blocking, tunnelling, and rate-shaping. ...
doi:10.1155/2018/1032761
fatcat:j76yhuc5rjhvbifkk5foq3klzq
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