The Experts below are selected from a list of 297 Experts worldwide ranked by ideXlab platform
Tiziano Bianchi - One of the best experts on this subject based on the ideXlab platform.
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Processing in the Encrypted Domain using a Composite Signal Representation
2020Co-Authors: Tiziano Bianchi, P.j.m. Veugen, Alessandro Piva, Mauro BarniAbstract:The current solutions for secure processing in the encrypted domain are usually based on homomorphic cryptosystems operating on very large algebraic structures. Recently, a Composite Signal representation has been proposed that allows to speed up linear operations on encrypted Signals via parallel processing and to reduce the size of the encrypted Signals. Though many of the most common Signal processing operations can be applied to Composite Signals, some operations require to process the Signal samples independently from each other, thus requiring an unpacking of the Composite Signals. In this paper, we will address the above issues, showing both merits and limits of the Composite Signal representation when applied in practical scenarios. A secure protocol for converting an encrypted Composite representation into the encryptions of the single Signal samples will be introduced. Two case studies clearly highlights pros and cons of using the Composite Signal representation in the proposed scenarios.
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WIFS - Processing in the encrypted domain using a Composite Signal representation: Pros and cons
2009 First IEEE International Workshop on Information Forensics and Security (WIFS), 2020Co-Authors: Tiziano Bianchi, Thijs Veugen, Alessandro Piva, Mauro BarniAbstract:The current solutions for secure processing in the encrypted domain are usually based on homomorphic cryptosystems operating on very large algebraic structures. Recently, a Composite Signal representation has been proposed that allows to speed up linear operations on encrypted Signals via parallel processing and to reduce the size of the encrypted Signals. Though many of the most common Signal processing operations can be applied to Composite Signals, some operations require to process the Signal samples independently from each other, thus requiring an unpacking of the Composite Signals. In this paper, we will address the above issues, showing both merits and limits of the Composite Signal representation when applied in practical scenarios. A secure protocol for converting an encrypted Composite representation into the encryptions of the single Signal samples will be introduced. A case study clearly highlights pros and cons of using the Composite Signal representation in the proposed scenarios.
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Efficient Implementation of a Buyer-Seller Watermarking Protocol Using a Composite Signal Representation
2020Co-Authors: Mina Deng, Tiziano Bianchi, Alessandro Piva, Bart PreneelAbstract:Buyer-seller watermarking protocols integrate watermarking techniques with cryptography, for copyright protection, piracy traci ng, and privacy protec- tion. In this paper, our main contribution is the development of an efficient buyer- seller watermarking protocol based on homomorphic public-key cryptosystem, and the use of Composite Signal representation in the encrypted domain to re- duce both the computational overhead and the large communication bandwidth which are due to the use of homomorphic public-key encryption schemes. Both complexity analysis and simulation results confirm the effic iency of the proposed solution, suggesting that this technique can be successful ly used in practical ap- plications.
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Composite Signal Representation for Fast and Storage-Efficient Processing of Encrypted Signals
IEEE Transactions on Information Forensics and Security, 2010Co-Authors: Tiziano Bianchi, Alessandro Piva, Mauro BarniAbstract:Signal processing tools working directly on encrypted data could provide an efficient solution to application scenarios where sensitive Signals must be protected from an untrusted processing device. In this paper, we consider the data expansion required to pass from the plaintext to the encrypted representation of Signals, due to the use of cryptosystems operating on very large algebraic structures. A general Composite Signal representation allowing us to pack together a number of Signal samples and process them as a unique sample is proposed. The proposed representation permits us to speed up linear operations on encrypted Signals via parallel processing and to reduce the size of the encrypted Signal. A case study-1-D linear filtering-shows the merits of the proposed representation and provides some insights regarding the Signal processing algorithms more suited to work on the Composite representation.
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an efficient buyer seller watermarking protocol based on Composite Signal representation
ACM workshop on Multimedia and security, 2009Co-Authors: Mina Deng, Tiziano Bianchi, Alessandro Piva, Bart PreneelAbstract:Buyer-seller watermarking protocols integrate watermarking techniques with cryptography, for copyright protection, piracy tracing, and privacy protection. In this paper, we propose an efficient buyer-seller watermarking protocol based on homomorphic public-key cryptosystem and Composite Signal representation in the encrypted domain. A recently proposed Composite Signal representation allows us to reduce both the computational overhead and the large communication bandwidth which are due to the use of homomorphic public-key encryption schemes. Both complexity analysis and simulation results confirm the efficiency of the proposed solution, suggesting that this technique can be successfully used in practical applications.
Alessandro Piva - One of the best experts on this subject based on the ideXlab platform.
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Processing in the Encrypted Domain using a Composite Signal Representation
2020Co-Authors: Tiziano Bianchi, P.j.m. Veugen, Alessandro Piva, Mauro BarniAbstract:The current solutions for secure processing in the encrypted domain are usually based on homomorphic cryptosystems operating on very large algebraic structures. Recently, a Composite Signal representation has been proposed that allows to speed up linear operations on encrypted Signals via parallel processing and to reduce the size of the encrypted Signals. Though many of the most common Signal processing operations can be applied to Composite Signals, some operations require to process the Signal samples independently from each other, thus requiring an unpacking of the Composite Signals. In this paper, we will address the above issues, showing both merits and limits of the Composite Signal representation when applied in practical scenarios. A secure protocol for converting an encrypted Composite representation into the encryptions of the single Signal samples will be introduced. Two case studies clearly highlights pros and cons of using the Composite Signal representation in the proposed scenarios.
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WIFS - Processing in the encrypted domain using a Composite Signal representation: Pros and cons
2009 First IEEE International Workshop on Information Forensics and Security (WIFS), 2020Co-Authors: Tiziano Bianchi, Thijs Veugen, Alessandro Piva, Mauro BarniAbstract:The current solutions for secure processing in the encrypted domain are usually based on homomorphic cryptosystems operating on very large algebraic structures. Recently, a Composite Signal representation has been proposed that allows to speed up linear operations on encrypted Signals via parallel processing and to reduce the size of the encrypted Signals. Though many of the most common Signal processing operations can be applied to Composite Signals, some operations require to process the Signal samples independently from each other, thus requiring an unpacking of the Composite Signals. In this paper, we will address the above issues, showing both merits and limits of the Composite Signal representation when applied in practical scenarios. A secure protocol for converting an encrypted Composite representation into the encryptions of the single Signal samples will be introduced. A case study clearly highlights pros and cons of using the Composite Signal representation in the proposed scenarios.
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Efficient Implementation of a Buyer-Seller Watermarking Protocol Using a Composite Signal Representation
2020Co-Authors: Mina Deng, Tiziano Bianchi, Alessandro Piva, Bart PreneelAbstract:Buyer-seller watermarking protocols integrate watermarking techniques with cryptography, for copyright protection, piracy traci ng, and privacy protec- tion. In this paper, our main contribution is the development of an efficient buyer- seller watermarking protocol based on homomorphic public-key cryptosystem, and the use of Composite Signal representation in the encrypted domain to re- duce both the computational overhead and the large communication bandwidth which are due to the use of homomorphic public-key encryption schemes. Both complexity analysis and simulation results confirm the effic iency of the proposed solution, suggesting that this technique can be successful ly used in practical ap- plications.
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Composite Signal Representation for Fast and Storage-Efficient Processing of Encrypted Signals
IEEE Transactions on Information Forensics and Security, 2010Co-Authors: Tiziano Bianchi, Alessandro Piva, Mauro BarniAbstract:Signal processing tools working directly on encrypted data could provide an efficient solution to application scenarios where sensitive Signals must be protected from an untrusted processing device. In this paper, we consider the data expansion required to pass from the plaintext to the encrypted representation of Signals, due to the use of cryptosystems operating on very large algebraic structures. A general Composite Signal representation allowing us to pack together a number of Signal samples and process them as a unique sample is proposed. The proposed representation permits us to speed up linear operations on encrypted Signals via parallel processing and to reduce the size of the encrypted Signal. A case study-1-D linear filtering-shows the merits of the proposed representation and provides some insights regarding the Signal processing algorithms more suited to work on the Composite representation.
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an efficient buyer seller watermarking protocol based on Composite Signal representation
ACM workshop on Multimedia and security, 2009Co-Authors: Mina Deng, Tiziano Bianchi, Alessandro Piva, Bart PreneelAbstract:Buyer-seller watermarking protocols integrate watermarking techniques with cryptography, for copyright protection, piracy tracing, and privacy protection. In this paper, we propose an efficient buyer-seller watermarking protocol based on homomorphic public-key cryptosystem and Composite Signal representation in the encrypted domain. A recently proposed Composite Signal representation allows us to reduce both the computational overhead and the large communication bandwidth which are due to the use of homomorphic public-key encryption schemes. Both complexity analysis and simulation results confirm the efficiency of the proposed solution, suggesting that this technique can be successfully used in practical applications.
Bart Preneel - One of the best experts on this subject based on the ideXlab platform.
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Efficient Implementation of a Buyer-Seller Watermarking Protocol Using a Composite Signal Representation
2020Co-Authors: Mina Deng, Tiziano Bianchi, Alessandro Piva, Bart PreneelAbstract:Buyer-seller watermarking protocols integrate watermarking techniques with cryptography, for copyright protection, piracy traci ng, and privacy protec- tion. In this paper, our main contribution is the development of an efficient buyer- seller watermarking protocol based on homomorphic public-key cryptosystem, and the use of Composite Signal representation in the encrypted domain to re- duce both the computational overhead and the large communication bandwidth which are due to the use of homomorphic public-key encryption schemes. Both complexity analysis and simulation results confirm the effic iency of the proposed solution, suggesting that this technique can be successful ly used in practical ap- plications.
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an efficient buyer seller watermarking protocol based on Composite Signal representation
ACM workshop on Multimedia and security, 2009Co-Authors: Mina Deng, Tiziano Bianchi, Alessandro Piva, Bart PreneelAbstract:Buyer-seller watermarking protocols integrate watermarking techniques with cryptography, for copyright protection, piracy tracing, and privacy protection. In this paper, we propose an efficient buyer-seller watermarking protocol based on homomorphic public-key cryptosystem and Composite Signal representation in the encrypted domain. A recently proposed Composite Signal representation allows us to reduce both the computational overhead and the large communication bandwidth which are due to the use of homomorphic public-key encryption schemes. Both complexity analysis and simulation results confirm the efficiency of the proposed solution, suggesting that this technique can be successfully used in practical applications.
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MM&Sec - An efficient buyer-seller watermarking protocol based on Composite Signal representation
Proceedings of the 11th ACM workshop on Multimedia and security - MM&Sec '09, 2009Co-Authors: Mina Deng, Tiziano Bianchi, Alessandro Piva, Bart PreneelAbstract:Buyer-seller watermarking protocols integrate watermarking techniques with cryptography, for copyright protection, piracy tracing, and privacy protection. In this paper, we propose an efficient buyer-seller watermarking protocol based on homomorphic public-key cryptosystem and Composite Signal representation in the encrypted domain. A recently proposed Composite Signal representation allows us to reduce both the computational overhead and the large communication bandwidth which are due to the use of homomorphic public-key encryption schemes. Both complexity analysis and simulation results confirm the efficiency of the proposed solution, suggesting that this technique can be successfully used in practical applications.
Pradip Sircar - One of the best experts on this subject based on the ideXlab platform.
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a new technique to reduce cross terms in the wigner distribution
Digital Signal Processing, 2007Co-Authors: Ram Bilas Pachori, Pradip SircarAbstract:A new method for time-frequency representation (TFR) of a Signal, which combines the Fourier-Bessel (FB) expansion and the Wigner-Ville distribution (WVD) has been presented in this paper. The FB expansion decomposes a multicomponent Signal into a number of monocomponent Signals, and then the WVD technique is applied on each component of the Composite Signal to analyze its time-frequency distribution (TFD). The simulation results show that the proposed technique based on the FB decomposition is a powerful tool for analyzing multicomponent nonstationary Signals and for obtaining the TFR of the Signal without introducing cross terms.
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Analysis of multi-component non-stationary Signals using Fourier-Bessel transform and Wigner distribution
2006 14th European Signal Processing Conference, 2006Co-Authors: Ram Bilas Pachori, Pradip SircarAbstract:We present a new method for time-frequency representation (TFR), which combines the Fourier-Bessel (FB) transform and the Wigner-Ville distribution (WVD). The FB transform decomposes a multi-component Signal into a number of mono-component Signals, and then the WVD technique is applied on each component of the Composite Signal to analyze its time-frequency distribution (TFD). The simulation results show that the proposed technique based on the FB decomposition is a powerful tool for analyzing multi-component non-stationary Signals and for obtaining the TFR of the Signal without cross terms.
Gregory W. Wornell - One of the best experts on this subject based on the ideXlab platform.
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Quantization index modulation: a class of provably good methods for digital watermarking and information embedding
2000 IEEE International Symposium on Information Theory (Cat. No.00CH37060), 2000Co-Authors: Brian Chen, Gregory W. WornellAbstract:We consider the problem of embedding one Signal (e.g., a digital watermark), within another "host" Signal to form a third, "Composite" Signal. The goal is to achieve efficient rate-distortion-robustness trade-offs. We introduce a new class of embedding methods called distortion-compensated quantization index modulation. In several different contexts involving both intentional and unintentional attacks, capacity-achieving methods exist within this class, while in other contexts these methods achieve provably better rate-distortion-robustness performance than previously proposed spread-spectrum and generalized low-bit(s) modulation methods.
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quantization index modulation a class of provably good methods for digital watermarking and information embedding
International Symposium on Information Theory, 2000Co-Authors: Brian Chen, Gregory W. WornellAbstract:We consider the problem of embedding one Signal (e.g., a digital watermark), within another "host" Signal to form a third, "Composite" Signal. The embedding is designed to achieve efficient tradeoffs among the three conflicting goals of maximizing the information-embedding rate, minimizing the distortion between the host Signal and Composite Signal, and maximizing the robustness of the embedding. We introduce new classes of embedding methods, termed quantization index modulation (QIM) and distortion-compensated QIM (DC-QIM), and develop convenient realizations in the form of what we refer to as dither modulation. Using deterministic models to evaluate digital watermarking methods, we show that QIM is "provably good" against arbitrary bounded and fully informed attacks, which arise in several copyright applications, and in particular it achieves provably better rate distortion-robustness tradeoffs than currently popular spread-spectrum and low-bit(s) modulation methods. Furthermore, we show that for some important classes of probabilistic models, DC-QIM is optimal (capacity-achieving) and regular QIM is near-optimal. These include both additive white Gaussian noise (AWGN) channels, which may be good models for hybrid transmission applications such as digital audio broadcasting, and mean-square-error-constrained attack channels that model private-key watermarking applications.
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dither modulation a new approach to digital watermarking and information embedding
electronic imaging, 1999Co-Authors: Brian Chen, Gregory W. WornellAbstract:We consider the problem of embedding one Signal (e.g., a digital watermark), within another 'host' Signal to form a third, 'Composite' Signal. The embedding must be done in such a way that minimizes distortion between the host Signal and Composite Signal, maximizes the information-embedding rate, and maximizes the robustness of the embedding. In general, these three goals are conflicting, and the embedding process must be designed to efficiently trade-off the three quantities. We propose a new class of embedding methods, which we term quantization index modulation (QIM), and develop a convenient realization of a QIM system that we call dither modulation in which the embedded information modulates a dither Signal and the host Signal is quantized with an associated dithered quantizer. QIM and dither modulation systems have considerable performance advantages over previously proposed spread-spectrum and low-bit(s) modulation systems in terms of the achievable performance trade-offs among distortion, rate, and robustness of the embedding. We also demonstrate these performance advantages in the context of 'no-key' digital watermarking applications, in which attackers can access watermarks in the clear. We also examine the fundamental limits of digital watermarking from an information theoretic perspective and discuss the achievable limits of QIM and alternative systems.© (1999) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
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Provably Robust Digital Watermarking
Proceeding of SPIE: Multimedia Systems and Applications II, 1999Co-Authors: Brian Chen, Gregory W. WornellAbstract:Copyright notification and enforcement, authentication, covert communication, and hybrid transmission are examples of emerging multimedia applications for digital watermarking methods, methods for embedding one Signal (e.g., the digital watermark) within another “host” Signal to form a third, “Composite” Signal. The embedding is designed to achieve efficient trade-offs among the three conflicting goals of maximizing information-embedding rate, minimizing distortion between the host Signal and Composite Signal, and maximizing the robustness of the embedding. Quantization indexmodulation (QIM) methods are a class of watermarking methods that achieve provably good rate-distortion-robustness performance. Indeed, QIM methods exist that achieve performance within a few dB of capacity in the case of a (possibly colored) Gaussian host Signal and an additive (possibly colored) Gaussian noise channel. Also, QIM methods can achieve capacity with a type of postprocessing called distortion compensation. This capacity is independent of host Signal statistics, and thus, contrary to popular belief, the information-embedding capacity when the host Signal is not available at the decoder is the same as the case when the host Signal is available at the decoder. A low-complexity realization of QIM called dither modulation has previously been proven to be better than both linear methods of spread spectrum and nonlinear methods of low-bit(s) modulation against square-error distortionconstrained intentional attacks. We introduce a new form of dither modulation called spread-transform dither modulation that retains these favorable performance characteristics while achieving better performance against other attacks such as JPEG compression.