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Search Publications by: Raghu N Kacker (Fed)

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Displaying 226 - 250 of 373

A Combinatorial Approach to Detecting Buffer Overflow Vulnerabilities

June 14, 2011
Author(s)
Raghu N. Kacker, Yu Lei, David R. Kuhn, Wenhua Wang
Buffer overflow vulnerabilities are program defects that can cause a buffer overflow to occur at runtime. Many security attacks exploit buffer overflow vulnerabilities to compromise critical data structures. In this paper, we present a black-box testing

A Survey of Binary Covering Arrays

April 7, 2011
Author(s)
James F. Lawrence, Raghu N. Kacker, Yu Lei, David R. Kuhn, Michael Forbes
Two-valued covering arrays of strength t are 0--1 matrices having the property that for each t columns and each of the possible 2t sequences of t 0's and 1's, there exists a row having that sequence in that set of t columns. Covering arrays are an

Measures, Uncertainties, and Significance Test in Operational ROC Analysis

January 31, 2011
Author(s)
Jin Chu Wu, Alvin F. Martin, Raghu N. Kacker
In operational ROC (receiver operating characteristic) analysis of fingerprint-image matching algorithms on large datasets, the measures and their accuracies are investigated in the three scenarios: 1) the true accept rate (TAR) of genuine scores at a

Derivation of Isosceles Trapezoidal Distribution

December 1, 2010
Author(s)
Raghu N. Kacker, James F. Lawrence
It is known that, if the mid-point of a rectangular distribution is specified, the half-width is inexactly known, and the state of knowledge about the half-width may be represented by a narrower rectangular distribution then the resulting distribution

Further Studies of Bootstrap Variability for ROC Analysis on Large Datasets

October 11, 2010
Author(s)
Jin Chu Wu, Alvin F. Martin, Raghu N. Kacker
The nonparametric two-sample bootstrap is successfully applied to computing the measurement uncertainties in receiver operating characteristic (ROC) analysis on large datasets in areas such as biometrics, speaker recognition system, etc. To determine the

Validation of Two-Sample Bootstrap in ROC Analysis on Large Datasets Using AURC

October 11, 2010
Author(s)
Jin Chu Wu, Alvin F. Martin, Raghu N. Kacker
Sampling variability can result in uncertainties of measures. The nonparametric two-sample bootstrap method has been used to compute uncertainties of measures in receiver operating characteristic (ROC) analysis on large datasets, such as the standard error

Practical Combinatorial Testing

October 7, 2010
Author(s)
David R. Kuhn, Raghu N. Kacker, Yu Lei
Combinatorial testing can help detect problems like this early in the testing life cycle. The key insight underlying t-way combinatorial testing is that not every parameter contributes to every fault and most faults are caused by interactions between a

Measurement Uncertainties in Speaker Recognition Evaluation

September 15, 2010
Author(s)
Jin Chu Wu, Alvin F. Martin, Craig S. Greenberg, Raghu N. Kacker
The speaker recognition evaluation is an ongoing series of evaluations conducted by NIST. A detection cost function is computed over the sequence of trials provided and used for all speaker detection tests while measuring speaker detection performance. The

A More General Type A Evaluation

September 9, 2010
Author(s)
Ruediger Kessel, Raghu N. Kacker, Klaus-Dieter Sommer
The evaluation of uncertainty according to the Guide to the Expression of Uncertainty in measurement is the internationally agreed procedure to evaluate the complete result statement in measurement including measurement uncertainty. It distinguishes two