The Experts below are selected from a list of 105 Experts worldwide ranked by ideXlab platform
Yookun Cho - One of the best experts on this subject based on the ideXlab platform.
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An efficient Pointer protection scheme to defend buffer overflow attacks
Lecture Notes in Computer Science, 2006Co-Authors: Yongsu Park, Yookun ChoAbstract:We present a new efficient Pointer protection method to defend buffer overflow attacks. It uses a simple watermark to protect the Pointer: during dereferencing the Pointer Variable, a watermark is also written/updated and before referencing the Pointer Variable, it verifies consistency of the watermark. If the Pointer's watermark does not exist or was damaged, our scheme regards this as an intrusion and stops the execution. The proposed scheme has the following strong points. First, unlike other randomization methods, our scheme has no possibility of malfunction caused by the execution of arbitrary instructions. Second, we conducted various experiments on prototype implementation, which showed that our scheme is as secure as the previous randomization schemes. Third, experimental results showed that the performance degradation is not high. Forth, unlike other randomization schemes, our scheme can support attack profiling.
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PARA - An efficient Pointer protection scheme to defend buffer overflow attacks
Applied Parallel Computing. State of the Art in Scientific Computing, 2006Co-Authors: Yongsu Park, Yookun ChoAbstract:We present a new efficient Pointer protection method to defend buffer overflow attacks. It uses a simple watermark to protect the Pointer: during dereferencing the Pointer Variable, a watermark is also written/updated and before referencing the Pointer Variable, it verifies consistency of the watermark. If the Pointer's watermark does not exist or was damaged, our scheme regards this as an intrusion and stops the execution. The proposed scheme has the following strong points. First, unlike other randomization methods, our scheme has no possibility of malfunction caused by the execution of arbitrary instructions. Second, we conducted various experiments on prototype implementation, which showed that our scheme is as secure as the previous randomization schemes. Third, experimental results showed that the performance degradation is not high. Forth, unlike other randomization schemes, our scheme can support attack profiling.
Yongsu Park - One of the best experts on this subject based on the ideXlab platform.
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An efficient Pointer protection scheme to defend buffer overflow attacks
Lecture Notes in Computer Science, 2006Co-Authors: Yongsu Park, Yookun ChoAbstract:We present a new efficient Pointer protection method to defend buffer overflow attacks. It uses a simple watermark to protect the Pointer: during dereferencing the Pointer Variable, a watermark is also written/updated and before referencing the Pointer Variable, it verifies consistency of the watermark. If the Pointer's watermark does not exist or was damaged, our scheme regards this as an intrusion and stops the execution. The proposed scheme has the following strong points. First, unlike other randomization methods, our scheme has no possibility of malfunction caused by the execution of arbitrary instructions. Second, we conducted various experiments on prototype implementation, which showed that our scheme is as secure as the previous randomization schemes. Third, experimental results showed that the performance degradation is not high. Forth, unlike other randomization schemes, our scheme can support attack profiling.
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PARA - An efficient Pointer protection scheme to defend buffer overflow attacks
Applied Parallel Computing. State of the Art in Scientific Computing, 2006Co-Authors: Yongsu Park, Yookun ChoAbstract:We present a new efficient Pointer protection method to defend buffer overflow attacks. It uses a simple watermark to protect the Pointer: during dereferencing the Pointer Variable, a watermark is also written/updated and before referencing the Pointer Variable, it verifies consistency of the watermark. If the Pointer's watermark does not exist or was damaged, our scheme regards this as an intrusion and stops the execution. The proposed scheme has the following strong points. First, unlike other randomization methods, our scheme has no possibility of malfunction caused by the execution of arbitrary instructions. Second, we conducted various experiments on prototype implementation, which showed that our scheme is as secure as the previous randomization schemes. Third, experimental results showed that the performance degradation is not high. Forth, unlike other randomization schemes, our scheme can support attack profiling.
David Higdon - One of the best experts on this subject based on the ideXlab platform.
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Calibration of Computational Models With Categorical Parameters and Correlated Outputs via Bayesian Smoothing Spline ANOVA
Journal of the American Statistical Association, 2015Co-Authors: Curtis B. Storlie, William A. Lane, Emily M. Ryan, James R. Gattiker, David HigdonAbstract:It has become commonplace to use complex computer models to predict outcomes in regions where data do not exist. Typically these models need to be calibrated and validated using some experimental data, which often consists of multiple correlated outcomes. In addition, some of the model parameters may be categorical in nature, such as a Pointer Variable to alternate models (or submodels) for some of the physics of the system. Here, we present a general approach for calibration in such situations where an emulator of the computationally demanding models and a discrepancy term from the model to reality are represented within a Bayesian smoothing spline (BSS) ANOVA framework. The BSS-ANOVA framework has several advantages over the traditional Gaussian process, including ease of handling categorical inputs and correlated outputs, and improved computational efficiency. Finally, this framework is then applied to the problem that motivated its design; a calibration of a computational fluid dynamics (CFD) model of...
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Calibration of Computational Models with Categorical Parameters and Correlated Outputs via Bayesian Smoothing Spline ANOVA
arXiv: Methodology, 2014Co-Authors: Curtis B. Storlie, William A. Lane, Emily M. Ryan, James R. Gattiker, David HigdonAbstract:It has become commonplace to use complex computer models to predict outcomes in regions where data does not exist. Typically these models need to be calibrated and validated using some experimental data, which often consists of multiple correlated outcomes. In addition, some of the model parameters may be categorical in nature, such as a Pointer Variable to alternate models (or submodels) for some of the physics of the system. Here we present a general approach for calibration in such situations where an emulator of the computationally demanding models and a discrepancy term from the model to reality are represented within a Bayesian Smoothing Spline (BSS) ANOVA framework. The BSS-ANOVA framework has several advantages over the traditional Gaussian Process, including ease of handling categorical inputs and correlated outputs, and improved computational efficiency. Finally this framework is then applied to the problem that motivated its design; a calibration of a computational fluid dynamics model of a bubbling fluidized which is used as an absorber in a CO2 capture system.
Curtis B. Storlie - One of the best experts on this subject based on the ideXlab platform.
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Calibration of Computational Models With Categorical Parameters and Correlated Outputs via Bayesian Smoothing Spline ANOVA
Journal of the American Statistical Association, 2015Co-Authors: Curtis B. Storlie, William A. Lane, Emily M. Ryan, James R. Gattiker, David HigdonAbstract:It has become commonplace to use complex computer models to predict outcomes in regions where data do not exist. Typically these models need to be calibrated and validated using some experimental data, which often consists of multiple correlated outcomes. In addition, some of the model parameters may be categorical in nature, such as a Pointer Variable to alternate models (or submodels) for some of the physics of the system. Here, we present a general approach for calibration in such situations where an emulator of the computationally demanding models and a discrepancy term from the model to reality are represented within a Bayesian smoothing spline (BSS) ANOVA framework. The BSS-ANOVA framework has several advantages over the traditional Gaussian process, including ease of handling categorical inputs and correlated outputs, and improved computational efficiency. Finally, this framework is then applied to the problem that motivated its design; a calibration of a computational fluid dynamics (CFD) model of...
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Calibration of Computational Models with Categorical Parameters and Correlated Outputs via Bayesian Smoothing Spline ANOVA
arXiv: Methodology, 2014Co-Authors: Curtis B. Storlie, William A. Lane, Emily M. Ryan, James R. Gattiker, David HigdonAbstract:It has become commonplace to use complex computer models to predict outcomes in regions where data does not exist. Typically these models need to be calibrated and validated using some experimental data, which often consists of multiple correlated outcomes. In addition, some of the model parameters may be categorical in nature, such as a Pointer Variable to alternate models (or submodels) for some of the physics of the system. Here we present a general approach for calibration in such situations where an emulator of the computationally demanding models and a discrepancy term from the model to reality are represented within a Bayesian Smoothing Spline (BSS) ANOVA framework. The BSS-ANOVA framework has several advantages over the traditional Gaussian Process, including ease of handling categorical inputs and correlated outputs, and improved computational efficiency. Finally this framework is then applied to the problem that motivated its design; a calibration of a computational fluid dynamics model of a bubbling fluidized which is used as an absorber in a CO2 capture system.
Theo M. Nieuwenhuizen - One of the best experts on this subject based on the ideXlab platform.
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Lectures on dynamical models for quantum measurements
International Journal of Modern Physics B, 2014Co-Authors: Theo M. Nieuwenhuizen, Martí Perarnau-llobet, Roger BalianAbstract:In textbooks, ideal quantum measurements are described in terms of the tested system only by the collapse postulate and Born's rule. This level of description offers a rather flexible position for the interpretation of quantum mechanics. Here we analyse an ideal measurement as a process of interaction between the tested system S and an apparatus A, so as to derive the properties postulated in textbooks. We thus consider within standard quantum mechanics the measurement of a quantum spin component ŝz by an apparatus A, being a magnet coupled to a bath. We first consider the evolution of the density operator of S + A describing a large set of runs of the measurement process. The approach describes the disappearance of the off-diagonal terms ("truncation") of the density matrix as a physical effect due to A, while the registration of the outcome has classical features due to the large size of the Pointer Variable, the magnetization. A quantum ambiguity implies that the density matrix at the final time can be...
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Phase transitions and quantum measurements
AIP Conference Proceedings, 2006Co-Authors: Armen E. Allahverdyan, Roger Balian, Theo M. NieuwenhuizenAbstract:In a quantum measurement, a coupling $g$ between the system S and the apparatus A triggers the establishment of correlations, which provide statistical information about S. Robust registration requires A to be macroscopic, and a dynamical symmetry breaking of A governed by S allows the absence of any bias. Phase transitions are thus a paradigm for quantum measurement apparatuses, with the order parameter as Pointer Variable. The coupling $g$ behaves as the source of symmetry breaking. The exact solution of a model where S is a single spin and A a magnetic dot (consisting of $N$ interacting spins and a phonon thermal bath) exhibits the reduction of the state as a relaxation process of the off-diagonal elements of S+A, rapid due to the large size of $N$. The registration of the diagonal elements involves a slower relaxation from the initial paramagnetic state of A to either one of its ferromagnetic states. If $g$ is too weak, the measurement fails due to a ``Buridan's ass'' effect. The probability distribution for the magnetization then develops not one but two narrow peaks at the ferromagnetic values. During its evolution it goes through wide shapes extending between these values.
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Quantum measurement as a driven phase transition: An exactly solvable model
Physical Review A, 2001Co-Authors: Armen E. Allahverdyan, Roger Balian, Theo M. NieuwenhuizenAbstract:A model of quantum measurement is proposed, which aims to describe statistical mechanical aspects of this phenomenon, starting from a purely Hamiltonian formulation. The macroscopic measurement apparatus is modeled as an ideal Bose gas, the order parameter of which, that is, the amplitude of the condensate, is the Pointer Variable. It is shown that properties of irreversibility and ergodicity breaking, which are inherent in the model apparatus, ensure the appearance of definite results of the measurement, and provide a dynamical realization of wave-function reduction or collapse. The measurement process takes place in two steps: First, the reduction of the state of the tested system occurs over a time of order $\hbar /(TN1/4)$, where T is the temperature of the apparatus, and N is the number of its degrees of freedom. This decoherence process is governed by the apparatus-system interaction. During the second step classical correlations are established between the apparatus and the tested system over the much longer time scale of equilibration of the apparatus. The influence of the parameters of the model on nonideality of the measurement is discussed. Schr\"odinger kittens, EPR setups, and information transfer are analyzed.