Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Perceiving Loudness, Pitch, and Location01:21

Perceiving Loudness, Pitch, and Location

943
The human brain perceives pitch through two primary mechanisms reflected in place theory and frequency theory. Each mechanism describes how sound waves are interpreted as specific pitches by the brain, offering insights into the intricate processes of auditory perception.
Place theory, or place coding, suggests that different pitches are heard because various sound waves activate specific locations along the cochlea's basilar membrane. The brain determines the pitch of a sound by...
943
Masking and Demasking Agents01:19

Masking and Demasking Agents

3.4K
EDTA titrations may necessitate masking and demasking agents to temporarily protect a particular metal ion in a mixture from the EDTA reaction. These agents facilitate the sequential analysis of the metal ions by forming stable complexes with some—but not all—metal ions during certain steps.
There are many masking agents, such as cyanide, fluoride, triethanolamine, thiourea, and 2,3-bis(sulfanyl)propan-1-ol (formerly 2,3-dimercapto-1-propanol), with the masking agent chosen based on...
3.4K
Design Example01:23

Design Example

531
The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...
531
Perception of Sound Waves01:01

Perception of Sound Waves

5.4K
The human ear is not equally sensitive to all frequencies in the audible range. It may perceive sound waves with the same pressure but different frequencies as having different loudness. Moreover, the perception of sound waves depends on the health of an individual's ears, which decays with age. The health of one's ears may also be affected by regular exposure to loud noises.
The pitch of a sound depends on the frequency and the pressure amplitude of the source. Two sounds of the same...
5.4K
Auditory Perception01:17

Auditory Perception

1.0K
The auditory system is essential for sound perception, utilizing various critical structures. When sound waves enter the outer ear, they travel through the ear canal and cause the eardrum to vibrate. These vibrations are then transmitted to the middle ear, where three tiny bones – the malleus, incus, and stapes – amplify the sound. This amplification is crucial, as it ensures that the sound vibrations are strong enough to be conveyed to the inner ear. These vibrations then reach the...
1.0K
Signal and System01:26

Signal and System

1.6K
A signal x(t) is a set of data or a time function representing a variable of interest. Signals typically convey information about a phenomenon, such as atmospheric temperature, humidity, human voice, television images, a dog's bark, or birdsongs. More generally, a signal can be a function of more than one independent variable. For instance, images depend on horizontal and vertical positions and can be regarded as two-dimensional signals. However, this text will focus on one-dimensional...
1.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Facile fabrication of iron-sulfur co-doped porous carbon based on the hyper-crosslinking technique for efficient electromagnetic wave absorption.

Nanoscale·2026
Same author

Reaction mechanisms and microstructural development of MSWI fly ash in geopolymers enhanced by mechanochemical activation.

Waste management (New York, N.Y.)·2026
Same author

Differences in cortisol levels between preterm and term infants: a systematic review and meta-analysis combined with Mendelian randomization study.

Frontiers in pediatrics·2026
Same author

From conventional to biosensor-based detection of <i>Cryptosporidium</i> spp. and <i>Toxoplasma gondii</i> in food and water: Implications for food and water safety.

Food and waterborne parasitology·2026
Same author

Genistein Pretreatment Attenuates Ovalbumin-Induced Food Allergy in Mice with Intestinal Barrier Preservation and Modulation of Gut Microbiota and Metabolites.

Foods (Basel, Switzerland)·2026
Same author

Global burden, projections, and causal factors of maternal sepsis and other maternal infections: A comprehensive epidemiological and mendelian randomization study.

PLoS neglected tropical diseases·2026
Same journal

An Optimized Behavioral Intervention for Managing Gestational Weight Gain Using Semi-Physical Modeling and Hybrid Model Predictive Control.

IEEE International Conference on Communications : [proceedings]. IEEE International Conference on Communications·2025
Same journal

Real-time Continuous Blood Pressure Estimation with Contact-free Bedseismogram.

IEEE International Conference on Communications : [proceedings]. IEEE International Conference on Communications·2024
Same journal

<i>Whispering</i>: Joint Service Offloading and Computation Reuse in Cloud-Edge Networks.

IEEE International Conference on Communications : [proceedings]. IEEE International Conference on Communications·2021
See all related articles

Related Experiment Video

Updated: Jan 18, 2026

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
09:09

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

814

Exploiting Physical Presence Sensing to Secure Voice Assistant Systems.

Bang Tran1, Shenhui Pan1, Xiaohui Liang1

  • 1Department of Computer Science, University of Massachusetts Boston.

IEEE International Conference on Communications : [Proceedings]. IEEE International Conference on Communications
|September 8, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a defense system for voice assistant systems (VAS) to detect and prevent malicious voice replay and injection attacks. The system uses Mel-Cepstral Frequency Coefficients (MFCC) and deep learning to achieve 76.4%-89.1% detection accuracy in smart-home scenarios.

More Related Videos

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

936
Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

2.0K

Related Experiment Videos

Last Updated: Jan 18, 2026

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
09:09

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

814
Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

936
Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

2.0K

Area of Science:

  • Cybersecurity
  • Artificial Intelligence
  • Smart Home Technology

Background:

  • Voice Assistant Systems (VAS) offer convenience but are vulnerable to security threats like voice replay and injection attacks.
  • Attackers can exploit nearby compromised speakers to remotely manipulate VAS devices in smart homes.
  • Existing defenses may require additional hardware or user effort, limiting practical application.

Purpose of the Study:

  • To propose a novel defense system for VAS integrated directly into the device.
  • To secure VAS against voice replay and injection attacks without extra hardware or user intervention.
  • To leverage correlations between voice and wireless data for attack detection.

Main Methods:

  • Continuous collection of voice and wireless data from the VAS device.
  • Extraction of Mel-Cepstral Frequency Coefficients (MFCC) features from both data streams.
  • Application of a deep learning model trained on time-series data to differentiate user commands from malicious inputs.

Main Results:

  • The proposed system demonstrated successful detection of voice replay and injection attacks in real-world smart-home settings.
  • Detection probabilities ranged from 76.4% to 89.1% across various tested scenarios.
  • The system effectively utilizes the correlation between voice and wireless data influenced by user activity.

Conclusions:

  • The developed defense system offers a robust, integrated solution for enhancing VAS security.
  • The approach effectively mitigates sophisticated voice-based attacks in smart-home environments.
  • This method provides a user-friendly and hardware-independent security enhancement for voice assistant devices.