scholarly journals Towards Relations Between the Hitting-Set Attack and the Statistical Disclosure Attack

Author(s):  
Dang Vinh Pham ◽  
Dogan Kesdogan
Author(s):  
Huisi Zhou ◽  
Dantong Ouyang ◽  
Liming Zhang ◽  
Naiyu Tian
Keyword(s):  

2014 ◽  
Vol 23 (2) ◽  
pp. 190-217 ◽  
Author(s):  
Gary McGuire ◽  
Bastian Tugemann ◽  
Gilles Civario
Keyword(s):  

2010 ◽  
Vol 37 (4) ◽  
pp. 3256-3263 ◽  
Author(s):  
Jun-Lin Lin ◽  
Tsung-Hsien Wen ◽  
Jui-Chien Hsieh ◽  
Pei-Chann Chang

1994 ◽  
Vol 1 (2) ◽  
Author(s):  
Alexander E. Andreev

The complexity of a nondeterministic function is the minimum possible complexity of its determinisation. The entropy of a nondeterministic function, F, is minus the logarithm of the ratio between the number of determinisations of F and the number of all deterministic functions.<br /> <br />We obtain an upper bound on the complexity of a nondeterministic function with restricted entropy for the worst case.<br /> <br /> These bounds have strong applications in the problem of algorithm derandomization. A lot of randomized algorithms can be converted to deterministic ones if we have an effective hitting set with certain parameters (a set is hitting for a set system if it has a nonempty intersection with any set from the system).<br /> <br />Linial, Luby, Saks and Zuckerman (1993) constructed the best effective hitting set for the system of k-value, n-dimensional rectangles. The set size is polynomial in k log n / epsilon.<br /> <br />Our bounds of nondeterministic functions complexity offer a possibility to construct an effective hitting set for this system with almost linear size in k log n / epsilon.


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