The Experts below are selected from a list of 267 Experts worldwide ranked by ideXlab platform
Hernández Encinas Luis - One of the best experts on this subject based on the ideXlab platform.
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NetVote: A Strict-Coercion Resistance Re-Voting Based Internet Voting Scheme with Linear Filtering
'MDPI AG', 2020Co-Authors: Querejeta-azurmendi Iñigo, Arroyo Guardeño David, Hernández-ardieta, Jorge L., Hernández Encinas LuisAbstract:This paper proposes NetVote, an internet voting protocol where usability and ease in deployment are a priority. We introduce the notion of strict coercion resistance, to distinguish between vote-buying and coercion resistance. We propose a protocol with ballot secrecy, practical everlasting privacy, verifiability and strict coercion resistance in the re-voting setting. Coercion is mitigated via a random dummy vote padding strategy to hide voting patterns and make re-voting deniable. This allows us to build a Filtering phase with Linear complexity, based on zero knowledge proofs to ensure correctness while maintaining privacy of the process. Voting tokens are formed by anonymous credentials and pseudorandom identifiers, achieving practical everlasting privacy, where even if dealing with a future computationally unbounded adversary, vote intention is still hidden. It is not assumed for voters to own cryptographic keys prior to the election, nor store cryptographic material during the election. This property allows voters not only to vote multiple times, but also from different devices each time, granting the voter a vote-from-anywhere experience. This paper builds on top of the paper published in CISIS’19. In this version, we modify the Filtering. Moreover, we formally define the padding technique, which allows us to perform the Linear Filtering scheme. Similarly we provide more details on the protocol itself and include a section of the security analysis, where we include the formal definitions of strict coercion resistance and a game based definition of practical everlasting privacy. Finally, we prove that NetVote satisfies them all
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NetVote: A Strict-Coercion Resistance Re-Voting Based Internet Voting Scheme with Linear Filtering
'MDPI AG', 2020Co-Authors: Querejeta-azurmendi Iñigo, Arroyo Guardeño David, Hernández-ardieta, Jorge L., Hernández Encinas LuisAbstract:© 2020 by the authors.This paper proposes NetVote, an internet voting protocol where usability and ease in deployment are a priority. We introduce the notion of strict coercion resistance, to distinguish between vote-buying and coercion resistance. We propose a protocol with ballot secrecy, practical everlasting privacy, verifiability and strict coercion resistance in the re-voting setting. Coercion is mitigated via a random dummy vote padding strategy to hide voting patterns and make re-voting deniable. This allows us to build a Filtering phase with Linear complexity, based on zero knowledge proofs to ensure correctness while maintaining privacy of the process. Voting tokens are formed by anonymous credentials and pseudorandom identifiers, achieving practical everlasting privacy, where even if dealing with a future computationally unbounded adversary, vote intention is still hidden. It is not assumed for voters to own cryptographic keys prior to the election, nor store cryptographic material during the election. This property allows voters not only to vote multiple times, but also from different devices each time, granting the voter a vote-from-anywhere experience. This paper builds on top of the paper published in CISIS’19. In this version, we modify the Filtering. Moreover, we formally define the padding technique, which allows us to perform the Linear Filtering scheme. Similarly we provide more details on the protocol itself and include a section of the security analysis, where we include the formal definitions of strict coercion resistance and a game based definition of practical everlasting privacy. Finally, we prove that NetVote satisfies them all.This research has been partially supported by Ministerio de Economía, Industria y Competitividad (MINECO), Agencia Estatal de Investigación (AEI), and European Regional Development Fund (ERDF, EU), through project COPCIS, grant number TIN2017-84844-C2-1-R, and by Comunidad de Madrid (Spain) through project CYNAMON, grant number P2018/TCS-4566-CM, co-funded along with ERDF.Peer reviewe
Querejeta-azurmendi Iñigo - One of the best experts on this subject based on the ideXlab platform.
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NetVote: A Strict-Coercion Resistance Re-Voting Based Internet Voting Scheme with Linear Filtering
'MDPI AG', 2020Co-Authors: Querejeta-azurmendi Iñigo, Arroyo Guardeño David, Hernández-ardieta, Jorge L., Hernández Encinas LuisAbstract:This paper proposes NetVote, an internet voting protocol where usability and ease in deployment are a priority. We introduce the notion of strict coercion resistance, to distinguish between vote-buying and coercion resistance. We propose a protocol with ballot secrecy, practical everlasting privacy, verifiability and strict coercion resistance in the re-voting setting. Coercion is mitigated via a random dummy vote padding strategy to hide voting patterns and make re-voting deniable. This allows us to build a Filtering phase with Linear complexity, based on zero knowledge proofs to ensure correctness while maintaining privacy of the process. Voting tokens are formed by anonymous credentials and pseudorandom identifiers, achieving practical everlasting privacy, where even if dealing with a future computationally unbounded adversary, vote intention is still hidden. It is not assumed for voters to own cryptographic keys prior to the election, nor store cryptographic material during the election. This property allows voters not only to vote multiple times, but also from different devices each time, granting the voter a vote-from-anywhere experience. This paper builds on top of the paper published in CISIS’19. In this version, we modify the Filtering. Moreover, we formally define the padding technique, which allows us to perform the Linear Filtering scheme. Similarly we provide more details on the protocol itself and include a section of the security analysis, where we include the formal definitions of strict coercion resistance and a game based definition of practical everlasting privacy. Finally, we prove that NetVote satisfies them all
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NetVote: A Strict-Coercion Resistance Re-Voting Based Internet Voting Scheme with Linear Filtering
'MDPI AG', 2020Co-Authors: Querejeta-azurmendi Iñigo, Arroyo Guardeño David, Hernández-ardieta, Jorge L., Hernández Encinas LuisAbstract:© 2020 by the authors.This paper proposes NetVote, an internet voting protocol where usability and ease in deployment are a priority. We introduce the notion of strict coercion resistance, to distinguish between vote-buying and coercion resistance. We propose a protocol with ballot secrecy, practical everlasting privacy, verifiability and strict coercion resistance in the re-voting setting. Coercion is mitigated via a random dummy vote padding strategy to hide voting patterns and make re-voting deniable. This allows us to build a Filtering phase with Linear complexity, based on zero knowledge proofs to ensure correctness while maintaining privacy of the process. Voting tokens are formed by anonymous credentials and pseudorandom identifiers, achieving practical everlasting privacy, where even if dealing with a future computationally unbounded adversary, vote intention is still hidden. It is not assumed for voters to own cryptographic keys prior to the election, nor store cryptographic material during the election. This property allows voters not only to vote multiple times, but also from different devices each time, granting the voter a vote-from-anywhere experience. This paper builds on top of the paper published in CISIS’19. In this version, we modify the Filtering. Moreover, we formally define the padding technique, which allows us to perform the Linear Filtering scheme. Similarly we provide more details on the protocol itself and include a section of the security analysis, where we include the formal definitions of strict coercion resistance and a game based definition of practical everlasting privacy. Finally, we prove that NetVote satisfies them all.This research has been partially supported by Ministerio de Economía, Industria y Competitividad (MINECO), Agencia Estatal de Investigación (AEI), and European Regional Development Fund (ERDF, EU), through project COPCIS, grant number TIN2017-84844-C2-1-R, and by Comunidad de Madrid (Spain) through project CYNAMON, grant number P2018/TCS-4566-CM, co-funded along with ERDF.Peer reviewe
Jacob Benesty - One of the best experts on this subject based on the ideXlab platform.
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on optimal frequency domain multichannel Linear Filtering for noise reduction
IEEE Transactions on Audio Speech and Language Processing, 2010Co-Authors: Mehrez Souden, Jacob Benesty, Sofiene AffesAbstract:Several contributions have been made so far to develop optimal multichannel Linear Filtering approaches and show their ability to reduce the acoustic noise. However, there has not been a clear unifying theoretical analysis of their performance in terms of both noise reduction and speech distortion. To fill this gap, we analyze the frequency-domain (non-causal) multichannel Linear Filtering for noise reduction in this paper. For completeness, we consider the noise reduction constrained optimization problem that leads to the parameterized multichannel non-causal Wiener filter (PMWF). Our contribution is fivefold. First, we formally show that the minimum variance distortionless response (MVDR) filter is a particular case of the PMWF by properly formulating the constrained optimization problem of noise reduction. Second, we propose new simplified expressions for the PMWF, the MVDR, and the generalized sidelobe canceller (GSC) that depend on the signals' statistics only. In contrast to earlier works, these expressions are explicitly independent of the channel transfer function ratios. Third, we quantify the theoretical gains and losses in terms of speech distortion and noise reduction when using the PWMF by establishing new simplified closed-form expressions for three performance measures, namely, the signal distortion index, the noise reduction factor (originally proposed in the paper titled ldquoNew insights into the noise reduction Wiener filter,rdquo by J. Chen (IEEE Transactions on Audio, Speech, and Language Processing, Vol. 15, no. 4, pp. 1218-1234, Jul. 2006) to analyze the single channel time-domain Wiener filter), and the output signal-to-noise ratio (SNR). Fourth, we analyze the effects of coherent and incoherent noise in addition to the benefits of utilizing multiple microphones. Fifth, we propose a new proof for the a posteriori SNR improvement achieved by the PMWF. Finally, we provide some simulations results to corroborate the findings of this work.
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on optimal frequency domain multichannel Linear Filtering for noise reduction
IEEE Transactions on Audio Speech and Language Processing, 2010Co-Authors: Mehrez Souden, Jacob Benesty, Sofiene AffesAbstract:Several contributions have been made so far to develop optimal multichannel Linear Filtering approaches and show their ability to reduce the acoustic noise. However, there has not been a clear unifying theoretical analysis of their performance in terms of both noise reduction and speech distortion. To fill this gap, we analyze the frequency-domain (non-causal) multichannel Linear Filtering for noise reduction in this paper. For completeness, we consider the noise reduction constrained optimization problem that leads to the parameterized multichannel non-causal Wiener filter (PMWF). Our contribution is fivefold. First, we formally show that the minimum variance distortionless response (MVDR) filter is a particular case of the PMWF by properly formulating the constrained optimization problem of noise reduction. Second, we propose new simplified expressions for the PMWF, the MVDR, and the generalized sidelobe canceller (GSC) that depend on the signals' statistics only. In contrast to earlier works, these expressions are explicitly independent of the channel transfer function ratios. Third, we quantify the theoretical gains and losses in terms of speech distortion and noise reduction when using the PWMF by establishing new simplified closed-form expressions for three performance measures, namely, the signal distortion index, the noise reduction factor (originally proposed in the paper titled ldquoNew insights into the noise reduction Wiener filter,rdquo by J. Chen (IEEE Transactions on Audio, Speech, and Language Processing, Vol. 15, no. 4, pp. 1218-1234, Jul. 2006) to analyze the single channel time-domain Wiener filter), and the output signal-to-noise ratio (SNR). Fourth, we analyze the effects of coherent and incoherent noise in addition to the benefits of utilizing multiple microphones. Fifth, we propose a new proof for the a posteriori SNR improvement achieved by the PMWF. Finally, we provide some simulations results to corroborate the findings of this work.
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On the optimal Linear Filtering techniques for noise reduction
Speech Communication, 2007Co-Authors: Jingdong Chen, Jacob Benesty, Yiteng HuangAbstract:Noise reduction, which aims at extracting the clean speech from noisy observations, has plenty of applications. It has attracted a considerable amount of research attention over the past several decades. Although many methods have been developed, the most widely used one, by far, is the optimal Linear Filtering technique, which achieves clean speech estimate by passing the noisy observation through an optimal Linear filter/transformation. The representative algorithms of this include Wiener Filtering, spectral restoration, subspace method, etc. Many experiments have been carried out, from various points of view, to show that the optimal Filtering technique can reduce the level of noise that is present in the speech signal and improve the corresponding signal-to-noise ratio (SNR). However, there is not much theoretical justification so far for the noise reduction and SNR improvement. This paper attempts to provide a theoretical analysis on the performance (including noise reduction, speech distortion, and SNR improvement) of the optimal Filtering noise-reduction techniques including the time-domain causal Wiener filter, the subspace method, and the frequency-domain subband Wiener filter. We show that the optimal Linear filter, regardless of how we delineate it, can indeed reduce the level of noise (but at a price of attenuating the desired speech signal). Most importantly, we prove that the a posteriori SNR (defined after the optimal Filtering) is always greater than, or at least equal to the a priori SNR, which reveals that the optimal Linear Filtering technique is indeed able to make noisy speech signals cleaner. We will also discuss the bounds for noise reduction, speech distortion, and SNR improvement.
Melinda C Anderson - One of the best experts on this subject based on the ideXlab platform.
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effects of noise nonLinear processing and Linear Filtering on perceived speech quality
Ear and Hearing, 2010Co-Authors: Kathryn H Arehart, James M Kates, Melinda C AndersonAbstract:OBJECTIVES The purpose of this study was to measure subjective quality ratings in listeners with normal hearing and listeners with hearing loss for speech subjected to a wide range of processing conditions that are representative of real hearing aids. DESIGN Speech quality was assessed using a rating scale in a group of 14 listeners with normal hearing and 15 listeners with mild to moderately severe sensorineural hearing loss. Controlled simulations of hearing aid processing were used to process speech that included speech subjected to (1) noise and nonLinear processing, (2) Linear Filtering, and (3) combinations of noise, nonLinear processing, and Linear Filtering. The 32 conditions of noise and nonLinear processing included stationary speech-shaped nose, multitalker babble, peak clipping, quantization noise, spectral subtraction, and dynamic range compression (in quiet, with babble, and with spectral subtraction). The 32 Linear Filtering conditions included high-pass Filtering, low-pass Filtering, band-pass Filtering, positive and negative spectral tilt, and resonance peaks. Subsets of these conditions were used for the 36 conditions that combined noise and nonLinear processing with Linear processing. RESULTS Both listeners with normal hearing and listeners with hearing loss gave consistent (reliable) ratings. In both listener groups, sound quality was significantly affected by the noise, nonLinear processing, and Linear Filtering conditions. Compared with the listeners with normal hearing, the listeners with hearing loss showed significantly lower ratings of sound quality in nearly all of the processing conditions. For the conditions included in the current hearing aid simulation, noise and nonLinear conditions had a greater effect on quality judgments than did the Linear Filtering conditions. CONCLUSIONS The data reported here provide a comprehensive dataset of speech quality ratings for simulated hearing aid processing conditions. The results indicate that quality ratings by listeners with hearing loss are significantly lower than quality ratings by listeners with normal hearing. In addition, quality ratings by listeners with hearing loss are impacted by signal processing at least as much as, and often more than, the quality ratings by listeners with normal hearing. Finally, quality ratings for speech processed with a simulated hearing aid are impacted more by noise and nonLinear signal processing than by Linear Filtering.
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Quality judgments for music signals by normal‐hearing and hearing‐impaired listeners.
The Journal of the Acoustical Society of America, 2009Co-Authors: Kathryn H Arehart, James M Kates, Melinda C AndersonAbstract:Noise, distortion, nonLinear signal‐processing algorithms, and Linear Filtering can all affect the sound quality of a hearing aid or other audio device. Most hearing‐aid research concentrates on speech, but music reproduction can also be an important factor in user satisfaction. In this presentation, quality judgments are made for several different music signals by normal‐hearing and hearing‐impaired listeners. The music signals include orchestral classical music, jazz instrumental, and vocal. The signal processing uses a simulated hearing aid. The noise and nonLinear signal degradations include additive noise, multitalker babble, peak‐clipping distortion, quantization noise, multichannel compression, spectral subtraction. Linear Filtering conditions include bandwidth limitation, spectral resonance peaks, and spectral tilt. Conditions combining noise and nonLinear processing with Linear Filtering are also included. Subject ratings of the degraded music will be presented, along with comparisons of the rati...
Sofiene Affes - One of the best experts on this subject based on the ideXlab platform.
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on optimal frequency domain multichannel Linear Filtering for noise reduction
IEEE Transactions on Audio Speech and Language Processing, 2010Co-Authors: Mehrez Souden, Jacob Benesty, Sofiene AffesAbstract:Several contributions have been made so far to develop optimal multichannel Linear Filtering approaches and show their ability to reduce the acoustic noise. However, there has not been a clear unifying theoretical analysis of their performance in terms of both noise reduction and speech distortion. To fill this gap, we analyze the frequency-domain (non-causal) multichannel Linear Filtering for noise reduction in this paper. For completeness, we consider the noise reduction constrained optimization problem that leads to the parameterized multichannel non-causal Wiener filter (PMWF). Our contribution is fivefold. First, we formally show that the minimum variance distortionless response (MVDR) filter is a particular case of the PMWF by properly formulating the constrained optimization problem of noise reduction. Second, we propose new simplified expressions for the PMWF, the MVDR, and the generalized sidelobe canceller (GSC) that depend on the signals' statistics only. In contrast to earlier works, these expressions are explicitly independent of the channel transfer function ratios. Third, we quantify the theoretical gains and losses in terms of speech distortion and noise reduction when using the PWMF by establishing new simplified closed-form expressions for three performance measures, namely, the signal distortion index, the noise reduction factor (originally proposed in the paper titled ldquoNew insights into the noise reduction Wiener filter,rdquo by J. Chen (IEEE Transactions on Audio, Speech, and Language Processing, Vol. 15, no. 4, pp. 1218-1234, Jul. 2006) to analyze the single channel time-domain Wiener filter), and the output signal-to-noise ratio (SNR). Fourth, we analyze the effects of coherent and incoherent noise in addition to the benefits of utilizing multiple microphones. Fifth, we propose a new proof for the a posteriori SNR improvement achieved by the PMWF. Finally, we provide some simulations results to corroborate the findings of this work.
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on optimal frequency domain multichannel Linear Filtering for noise reduction
IEEE Transactions on Audio Speech and Language Processing, 2010Co-Authors: Mehrez Souden, Jacob Benesty, Sofiene AffesAbstract:Several contributions have been made so far to develop optimal multichannel Linear Filtering approaches and show their ability to reduce the acoustic noise. However, there has not been a clear unifying theoretical analysis of their performance in terms of both noise reduction and speech distortion. To fill this gap, we analyze the frequency-domain (non-causal) multichannel Linear Filtering for noise reduction in this paper. For completeness, we consider the noise reduction constrained optimization problem that leads to the parameterized multichannel non-causal Wiener filter (PMWF). Our contribution is fivefold. First, we formally show that the minimum variance distortionless response (MVDR) filter is a particular case of the PMWF by properly formulating the constrained optimization problem of noise reduction. Second, we propose new simplified expressions for the PMWF, the MVDR, and the generalized sidelobe canceller (GSC) that depend on the signals' statistics only. In contrast to earlier works, these expressions are explicitly independent of the channel transfer function ratios. Third, we quantify the theoretical gains and losses in terms of speech distortion and noise reduction when using the PWMF by establishing new simplified closed-form expressions for three performance measures, namely, the signal distortion index, the noise reduction factor (originally proposed in the paper titled ldquoNew insights into the noise reduction Wiener filter,rdquo by J. Chen (IEEE Transactions on Audio, Speech, and Language Processing, Vol. 15, no. 4, pp. 1218-1234, Jul. 2006) to analyze the single channel time-domain Wiener filter), and the output signal-to-noise ratio (SNR). Fourth, we analyze the effects of coherent and incoherent noise in addition to the benefits of utilizing multiple microphones. Fifth, we propose a new proof for the a posteriori SNR improvement achieved by the PMWF. Finally, we provide some simulations results to corroborate the findings of this work.