2012. 4rd issue

Table of contents 

Full issue  (17 MB)


O. Akan, L. Bacsárdi, S. Imre
Special Issue on Quantum Computing- Guest Editorial 

V.A. Vilnrotter
Quantum Receiver for Detecting Binary Coherent-State Signals with Constant-Intensity Local Lasers 

A quantum receiver capable of approaching the fundamental quantum limit on bit error probability is described and evaluated. Conventional optical and abstract quantum mechanical descriptions are provided and the underlying principles derived in both domains, thus providing a bridge to optimum quantum measurements in terms of well-understood optical communications concepts. Receiver performance is evaluated for the case of binary phase-shift keyed modulation, and it is shown that significant gains can be achieved over nearoptimum receivers reported previously in the literature. This new receiver concept can be implemented using practical measurements amenable to high data-rate operation, hence it may enable future deep-space optical communications with performance approaching the greatest possible fidelity allowed by the laws of quantum mechanics.

L. Nagy
Classical and Quantum Genetic Optimization Applied to Coverage Optimization for Indoor Access Point Networks 

The new focus of wireless communication is moving from voice to multimedia services. There is a growing interest in providing and improving radio coverage for mobile phones, short range radios and WLANs inside buildings. The need of such coverage appears mainly in office buildings, shopping malls, train stations where the subscriber density is very high. The cost of cellular systems and also the one of indoor wireless systems depend highly on the number of base stations required to achieve the desired coverage for a given level of field strength. There are already numerous optimization methods published which can be applied to the optimal design of such indoor networks [7,8,9, 10,11]. The fitness function of the optimization problem has nu-merous local optimum and therefore gradient based methods can not be applied. The recently published methods use any heuristic technique for finding the optimal Access Point (AP) positions. Common drawbacks of the methods are the slow convergence in a complex environment like the indoor one.
The complexity of the selection procedure of a classical genetic algorithm is O(NlogN) where N is the size of the population. The Quantum Genetic Algorithm (QGA) exploits the power of quan-tum computation in order to speed up genetic procedures. While the quantum and classical genetic algorithms use the same num-ber of generations, the QGA outperforms the classical one in identifying the high-fitness subpopulation at each generation. In QGA the classical fitness evaluation and selection procedures are replaced by a single quantum procedure.
The article introduces the Quantum inspired Genetic Algo-rithm (QGA) for indoor access point position optimization to maximal coverage and compares with the Classical Genetic Algo-rithm (CGA).

S. Kak
The Problem of Testing a Quantum Gate 

We consider the question of testing of quantum gates as a part of the larger problem of communication through circuits that use a variety of such gates. We argue that the correct outputs for the basic input values to the two-qubit gate are not sufficient to guarantee satisfactory validation of its workings for all values. We present reasons why these gates may not be error free, and as non-ideal gates they need to be tested for a wide range of probability amplitudes, and we argue that the burden of this additional testing is substantial. Experimental implementations of the controlled-NOT gate have substantial non-unitarity and residual errors. Some analytical results on the complexity of the problem of quantum gate testing are presented.


V. Mátyás, Z. RÍha and P. Svenda
Special Issue on Applied Cryptography - Guest Editorial 

M. Stanek
Attacking Scrambled Burrows - Wheeler Transform 

Scrambled Burrows-Wheeler transform [6] is an attempt to combine privacy (encryption) and data compression. We show that the proposed approach is insecure. We present chosen plaintext and known plaintext attacks and estimate their complexity in various scenarios.

J. Kur, V. Mátyás and P. Svenda
Two Improvements of Random Key Predistribution for Wireless Sensor Networks 

Key distribution is of a critical importance to security of wireless sensor networks (WSNs). Random key predistribution is an acknowledged approach to the key distribution problem. In this paper, we propose and analyze two novel improvements that enhance security provided by the random key predistribution schemes. The first improvement exploits limited length collisions in secure hash functions to increase the probability of two nodes sharing a key. The second improvement introduces hash chains into the key pool construction to directly increase the resilience against a node capture attack. Both improvements can be further combined to bring the best performance. We evaluate the improvements both analytically and computationally on a network simulator. The concepts used are not limited to the random key predistribution.

M. Sramka
Privacy Scores: Assessing Privacy Risks Beyond Social Networks 

Assessing privacy risks arising from publishing private information on social networks is challenging for the users. Privacy Scores were proposed in the past to provide each user with a score – a measurement of how much sensitive information a user made available for others on a social network website. We present the privacy scores, discuss their shortcomings, and show several research directions for their extensions. We propose an extension that takes the privacy score metric from a single social network closed system to include background knowledge. Our examples and experimental results show the need to include publicly available background knowledge in the computation of privacy scores in order to get scores that more truthfully reflect the privacy risks of the users. We add background knowledge about users by means of combining several social networks together or by using simple web search for detecting publicly known information about the evaluated users.

D. Naccache and Z. Ríha
Accelerating Biometric Identification 

By opposition to biometric matching, biometric identification is a relatively costly process. Let B = {b1, ...,bn} be a database of n biometric templates and let b be a given individual biometric acquisition. The biometric identification problem consists in finding the most likely bi corresponding to b. This paper assumes the existence of an oracle A taking as b and bi, and responding with true or false. Considering A as an atomic operation, any system-level optimization must necessarily minimize the number of calls to A per identification session. This is the parameter that we optimize in this paper.


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