Quantum privacy and quantum wiretap channels
Problems of Information Transmission
On the blind estimation of baud-rate equalizer performance
EURASIP Journal on Applied Signal Processing
Maximizing Privacy under Data Distortion Constraints in Noise Perturbation Methods
Privacy, Security, and Trust in KDD
Security implications of selective encryption
Proceedings of the 6th International Workshop on Security Measurements and Metrics
Physical layer authentication over an OFDM fading wiretap channel
Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools
CT-RSA'07 Proceedings of the 7th Cryptographers' track at the RSA conference on Topics in Cryptology
Investigating the distribution of password choices
Proceedings of the 21st international conference on World Wide Web
Some inequalities and their application for estimating the moments of guessing mappings
Mathematical and Computer Modelling: An International Journal
Estimation of arithmetic means and their applications in guessing theory
Mathematical and Computer Modelling: An International Journal
Numerical evaluation of the average number of successive guesses
UCNC'12 Proceedings of the 11th international conference on Unconventional Computation and Natural Computation
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Let (X,Y) be a pair of discrete random variables with X taking one of M possible values, Suppose the value of X is to be determined, given the value of Y, by asking questions of the form “Is X equal to x?” until the answer is “Yes”. Let G(x|y) denote the number of guesses in any such guessing scheme when X=x, Y=y. We prove that E[G(X|Y)ρ]⩾(1+lnM)-ρΣy [ΣxPX,Y(x,y)1/1+ρ] 1+ρ for any ρ⩾0. This provides an operational characterization of Renyi's entropy. Next we apply this inequality to the estimation of the computational complexity of sequential decoding. For this, we regard X as the input, Y as the output of a communication channel. Given Y, the sequential decoding algorithm works essentially by guessing X, one value at a time, until the guess is correct. Thus the computational complexity of sequential decoding, which is a random variable, is given by a guessing function G(X|Y) that is defined by the order in which nodes in the tree code are hypothesized by the decoder. This observation, combined with the above lower bound on moments of G(X|Y), yields lower bounds on moments of computation in sequential decoding. The present approach enables the determination of the (previously known) cutoff rate of sequential decoding in a simple manner; it also yields the (previously unknown) cutoff rate region of sequential decoding for multiaccess channels. These results hold for memoryless channels with finite input alphabets