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Toplam kayıt 7, listelenen: 1-7
Cryptanalysis of a multi-chaotic systems based image cryptosystem
(Elsevier Science BV, 2010-01-15)
This paper is a cryptanalysis of a recently proposed multi-chaotic systems based image cryptosystem. The cryptosystem is composed of two shuffling stages parameterized by chaotically generated sequences. We propose and ...
Force-directed approaches to sensor localization
(Assoc Computing Machinery, 2010-09)
As the number of applications of sensor networks increases, so does the interest in sensor network localization, that is, in recovering the correct position of each node in a network of sensors from partial connectivity ...
Cryptanalysis of a new substitution-diffusion based image cipher
(Elsevier Science BV, 2010-07)
This paper introduces two different types of attacks on a recently proposed cryptosystem based on chaotic standard and logistic maps. In the two attacks, only a pair of (plaintext/ciphertext) was needed to totally break ...
Cryptanalysis of Fridrich's chaotic image encryption
(World Scientific Publishing, 2010-05)
We cryptanalyze Fridrich's chaotic image encryption algorithm. We show that the algebraic weaknesses of the algorithm make it vulnerable against chosen-ciphertext attacks. We propose an attack that reveals the secret ...
Fully decentralized and collaborative multilateration primitives for uniquely localizing WSNs
(Springer International Publishing AG, 2010)
We provide primitives for uniquely localizing WSN nodes. The goal is to maximize the number of uniquely localized nodes assuming a fully decentralized model of computation. Each node constructs a cluster of its own and ...
Feature extraction from discrete attributes
(IEEE, 2010)
In many pattern recognition applications, first decision trees are used due to their simplicity and easily interpretable nature. In this paper, we extract new features by combining k discrete attributes, where for each ...
Univariate margin tree
(Springer, 2010)
In many pattern recognition applications, first decision trees are used due to their simplicity and easily interpretable nature. In this paper, we propose a new decision tree learning algorithm called univariate margin ...