Audio-Replay Attack Detection Countermeasures

Lavrentyeva, Galina; Novoselov, Sergey; Malykh, Egor; Kozlov, Alexander; Kudashev, Oleg; Shchemelinin, Vadim

doi:10.1007/978-3-319-66429-3_16

Cited by 9 publications

(3 citation statements)

References 21 publications

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“…It is noteworthy that human language entails ambiguous words, contractions, similes, jargon, and others; therefore, it takes implausible assessment and couple of minutes for blockchain and NLP to decipher the accurate output [12] and [13]. Concisely, when the needed signal has been deciphered and cognized, an acoustic echo cancellation comes in place to negate noise from the receiver signal to ensure that only the needed and intended signal remains in the system [6], [14], and [15].…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Assessment of Smart Home Assistants as an IoT

Obaid

2021

Int. J. CIM

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A smart home personal assistant technology is an intrinsic system, which incorporates many elements such as users, Smart Home Personal Assistants (SPA) devices, cloud, skill provider and other responsive devices. Even though Smart Home Personal Assistants give a robust security and privacy options, the devices face many weaknesses, which make the system vulnerable and can be comprised by adversaries, who can capitalize on limitations to gain access to delicate information and privacy of users. In this research, the aim is to assess how invention and innovation of security and SPA can be harnessed by users to interrelate with the system. Subsequently, this write-up will address both the problems related to the system and attempt to bring in solutions, which makes the technology more adaptable and versatile to all users. Initial studies show that some of the weakness underlying the technology include the open-nature of the voice channel, complexity of the architecture, software implications, and the utility of the technology to less proficient users. As a result, the study anticipates at solving the voice squatting attack, using the SPA intelligent assistant, incorporating a filer to filter the ultrasonic attack and noise as well as trying to assess the efficacy of the elements developed against the voice squatting attacks. The study found out that there is a need to mitigate the attacks on the blockchain technology and Natural Language Processors (NLP) to assure protection of SPA from attacks.

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Section: Theoretical Frameworkmentioning

confidence: 99%

Assessment of Smart Home Assistants as an IoT

Obaid

2021

Int. J. CIM

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“…Lavrentyeva et al [31] used a reduced version of Light Convolutional Neural Network architecture (LCNN) based on the method of the Max-Feature-Map activation (MFM) to investigate different countermeasures to defend against voice replay attacks. The LCNN with Fast Fourier-based features acquired an equal error rate of 7.34% on ASV spoof 2017 dataset in comparison to the spoofing detection method used in [32] which had an error rate of 30.74%.…”

Section: Replay Attacksmentioning

confidence: 99%

Smart Home Voice Assistants: A Literature Survey of User Privacy and Security Vulnerabilities

Sharif

Tenbergen

2020

J. Complex Syst. Inform. Model. Q.

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Intelligent voice assistants are internet-connected devices, which listen to their environment and react to spoken user commands in order to retrieve information from the internet, control appliances in the household, or notify the user of incoming messages, reminders, and the like. With their increasing ubiquity in smart homes, their application seems only limited by the imagination of developers, who connect these off-the-shelf devices to existing apps, online services, or appliances. However, since their inherent nature is to observe the user in their home, their ubiquity also raises concern of security and user privacy. To justify the trust placed into the devices, the devices must be secure from unauthorized access and the back-end infrastructure tasked with speech-to-text analysis, command interpretation, and connection to other services and appliances must maintain confidentiality of data. To investigate existing possible vulnerabilities, approaches to mitigate them, as well as general considerations in this emerging field, we supplement the findings of a recent study with results from a systematic literature review. We were able to compile a list of six main types of user privacy vulnerabilities, partially confirming previous findings, but also finding additional issues. We discuss these vulnerabilities, their associated attack vectors, and possible mitigations users can take to protect themselves.

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“…Categorization of countermeasures found in related studies. Lavrentyeva et al[75] explore different countermeasures to defend against voice replay attacks. Even though the countermeasure is implemented at #3 of the architecture because it needs extensive computational power, it aims at securing #1.…”

mentioning

confidence: 99%

Smart Home Personal Assistants: A Security and Privacy Review

Edu,

Such,

Suarez-Tangil

2019

Preprint

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Smart Home Personal Assistants (SPA) are an emerging innovation that is changing the means by which home users interact with technology. However, there are a number of elements that expose these systems to various risks: i) the open nature of the voice channel they use, ii) the complexity of their architecture, iii) the AI features they rely on, and iv) their use of a wide range of underlying technologies. This paper presents an in-depth review of the security and privacy issues in SPA, categorizing the most important attack vectors and their countermeasures. Based on this, we discuss open research challenges that can help steer the community to tackle and address current security and privacy issues in SPA. One of our key findings is that even though the attack surface of SPA is conspicuously broad and there has been a significant amount of recent research efforts in this area, research has so far focused on a small part of the attack surface, particularly on issues related to the interaction between the user and the SPA devices. We also point out that further research is needed to tackle issues related to authorization, speech recognition or profiling, to name a few. To the best of our knowledge, this is the first article to conduct such a comprehensive review and characterization of the security and privacy issues and countermeasures of SPA.

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Audio-Replay Attack Detection Countermeasures

Cited by 9 publications

References 21 publications

Assessment of Smart Home Assistants as an IoT

Assessment of Smart Home Assistants as an IoT

Smart Home Voice Assistants: A Literature Survey of User Privacy and Security Vulnerabilities

Smart Home Personal Assistants: A Security and Privacy Review

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