Remarks on breaking the Vigenère autokey cipher

Abstract

It has been mentioned by Shannon that a Vigenère autokey ciphertext can be transformed into a Vigenère ciphertext, provided the length of the priming key is known. We revisit this transformation and argue that combining it with the Friedman test, in fact, allows revealing of the length of the priming key. Thus, Shannon’s transformation together with the Friedman test allow transforming a Vigenère autokey ciphertext into a Vigenère ciphertext without any prior information. This allows an adversary to solve a Vigenère autokey ciphertext as if it was a Vigenère ciphertext. In addition, we show that the same method can be used to solve a modification of the Vigenère autokey cipher used in the Russian Civil War in 1917–1922.     

Cryptanalyzing an image encryption algorithm based on scrambling and Veginère cipher

Recently, an image encryption algorithm based on scrambling and Veginère cipher has been proposed. However, it was soon cryptanalyzed by Zhang et al. using a method composed of both chosen-plaintext attack and differential attacks. This paper briefly reviews the two attack approaches proposed by Zhang et al. and outlines their mathematical interpretations. Based on these approaches, we present an improved chosen-plaintext attack to further reduce the number of chosen-plaintexts required, which is proved to be optimal. Moreover, it is found that an elaborately designed known-plaintext attack can efficiently compromise the image cipher under study. This finding is confirmed by both mathematical analysis and numerical simulations. The cryptanalyzing techniques developed in this paper provide some insights for designing secure and efficient multimedia ciphers.     

Efficient implementation of a generalized polak-ribière algorithm for nonlinear optimization

We have recently developed a new conjugate gradient type method, the Generalized Polak-Ribière (GPR) method, for unconstrained minimization. It is based on search directions that are parallel to the Newton direction of the restriction of the objective function f on the two dimensional subspace span{?g p}, with p a suitable direction in span{? g,s^?}, where g and s ^? are the current gradient and previous search direction respectively. The new approach proved to be considerably more efficient than the original Polak-Ribière method.

In this paper, various implementations of the GPR method are compared with a currently available standard NAG software routine and also with the Nocedal, Buckley-LeNir and Shanno's limited memory algorithms. The results demonstrate the general effectiveness of the new algorithm. We also give a very brief discussion of extensions of the GPR method that generate search directions parallel to Newton directions in subspaces of dimension greater than two.     

How to “alternatize” a clustering algorithm

Given a clustering algorithm, how can we adapt it to find multiple, nonredundant, high-quality clusterings? We focus on algorithms based on vector quantization and describe a framework for automatic ‘alternatization’ of such algorithms. Our framework works in both simultaneous and sequential learning formulations and can mine an arbitrary number of alternative clusterings. We demonstrate its applicability to various clustering algorithms—k-means, spectral clustering, constrained clustering, and co-clustering—and effectiveness in mining a variety of datasets.     

An extension to ‘an algorithm for rinding a circuit of even length in a directed graph’

Most of the empirical studies modelling the association between slock returns and accounting earnings assume a homogeneous return-earnings relation across firms and over time. However, in recent years some studies have reported that this association significantly varies across firms and also over time. Whether macro-economic factors explain the intertemporal variation of earnings response coefficients (ERCs), i.e. the slope coefficients between stock returns and corporate earnings in the Finnish stock market is studied. In the theoretical part of the study it is shown that there exists a relationship between macroeconomic variables affecting future cash flows/dividends or pricing operator and the intertemporal variation of earnings response coefficients. The empirical analysis reveals some time-series variation of ERCs in the Finnish stock market. A significant proportion of this variation is observed to be due to the changes in the underlying macroeconomic characteristics.     

Mental rotation: a key to mitigation of motion sickness in the virtual environment?

Some of our recent observations suggest that mental rotation may be important for reduction of motion sickness in microgravity as well as in the microgravity simulator. Therefore, we suggest that development of the ability to perform mental rotation may be important for adaptation to many virtual environments. Training virtual environment operators to perform mental rotation may enhance operator performance both by increasing their ability to "locomote in" and manipulate that environment and by reducing motion sickness associated with transitions between virtual and normal environments.     

How do we measure and improve the quality of a hierarchical ontology?

Hierarchical ontologies enable organising information in a human-machine understandable form, but constructing them for reuse and maintainability remains difficult. Often supporting tools available lack formal methodological underpinning and their developers are not supported by any concomitant metrics. The paper presents a formal underpinning to provide quality metrics of a taxonomy hierarchical ontology and proposes a methodology for semi-automatic building of maintainable taxonomies. Users provide terms to be used to describe different ontological elements as well as their attributes and their ranges of values. The methodology uses the formalised metrics to assess the quality of the users input and proposes changes according to given quality constraints. The paper illustrates the metrics and the methodology in constructing and repairing two medium size well-known taxonomies.     

Analysis of Galerkin Methods for the Fully Nonlinear Monge-Ampère Equation

This paper develops and analyzes finite element Galerkin and spectral Galerkin methods for approximating viscosity solutions of the fully nonlinear Monge-Ampère equation det (D ² u ⁰)=f (>0) based on the vanishing moment method which was developed by the authors in Feng and Neilan (J. Sci. Comput. 38:74–98, 2009) and Feng (Convergence of the vanishing moment method for the Monge-Ampère equation, submitted). In this approach, the Monge-Ampère equation is approximated by the fourth order quasilinear equation −εΔ² u ^ε +det D ² u ^ε =f accompanied by appropriate boundary conditions. This new approach enables us to construct convergent Galerkin numerical methods for the fully nonlinear Monge-Ampère equation (and other fully nonlinear second order partial differential equations), a task which has been impracticable before. In this paper, we first develop some finite element and spectral Galerkin methods for approximating the solution u ^ε of the regularized problem. We then derive optimal order error estimates for the proposed numerical methods. In particular, we track explicitly the dependence of the error bounds on the parameter ε, for the error u^e-u^e_hu^{\varepsilon}-u^{\varepsilon}_{h}. Due to the strong nonlinearity of the underlying equation, the standard error estimate technique, which has been widely used for error analysis of finite element approximations of nonlinear problems, does not work here. To overcome the difficulty, we employ a fixed point technique which strongly makes use of the stability property of the linearized problem and its finite element approximations. Finally, using the Argyris finite element method as an example, we present a detailed numerical study of the rates of convergence in terms of powers of ε for the error u⁰-u_h^eu^{0}-u_{h}^{\varepsilon}, and numerically examine what is the “best” mesh size h in relation to ε in order to achieve these rates.     

Breaking “Tirpitz”: Cryptanalysis of the Japanese-German joint naval cipher

This article gives the solutions of the only four messages known to still exist from the previously unbroken Japanese-German joint naval radio communications traffic in the system known as “Tirpitz,” which used the specially-designed model T Enigma machine. It also explains the methods used by the author to break the messages, and gives some background on the model T Enigma and its usages.     

A simpler counterexample to a long-standing conjecture on the complexity of Bryantʼs apply algorithm

In 1986 in his seminal paper Bryant has introduced Ordered Binary Decision Diagrams (OBDDs) as a dynamic data structure for the representation and manipulation of Boolean functions which allow efficient algorithms for important operations like synthesis, the combination of two Boolean functions by a Boolean operator, and equivalence checking. Based on his empirical evaluation he has conjectured that his apply algorithm for the synthesis works in linear time with respect to the input and output size. Recently in 2012, Yoshinaka et al. have presented a counterexample which contradicts this conjecture but their example has the drawback that the chosen variable ordering for the OBDD representation of the input and output is bad. Therefore, they have raised the question whether Bryant?s conjecture may still stand for reasonable variable orderings. Here, a negative answer is given by presenting a simple counterexample which works for such kind of variable orderings.     

Mean and variance of the arc length of a Gaussian process on a finite interval†

The first and second moments of the distribution function of the arc length of a Gaussian process on a finite interval are obtained in terms of the covariance function of the derivative process. A closed expression (in terms of a modified Bessel function) was obtained for the first moment; however, the second moment had to be evaluated numerically. Numerical calculations were carried out for three typical covariance functions.     

Economic-statistical design of the X¯ chart used to control a wandering process mean using genetic algorithm

This research considers the process mean wanders according to a first-order autoregressive model. During the in-control period the process mean wanders around its target value, and after the assignable cause occurrence, around an off-target value. The cost model proposed by Duncan was used to select the X bar chart’s parameters and the genetic algorithm to meet their optimum values. The wandering movement required a Markov chain to obtain the properties of the control chart. The autocorrelation among mean values increases the monitoring costs and reduces significantly the chart’s efficiency.     

Entanglement sudden death: a threat to advanced quantum key distribution?

Entanglement is a global characteristic unique to quantum states that depends on quantum coherence and may allow one to carry out communications and information processing tasks that are either impossible or less efficient using classical states. Because environmental noise, even when entirely local in spatial extent, can fully destroy entanglement in finite time, an effect referred to as “entanglement sudden death” (ESD), it may threaten quantum information processing tasks. Although it may be possible to “distill” entanglement from a collection of noise-affected systems under appropriate circumstances, once entanglement has been completely lost no amount of distillation can recover it. It is therefore extremely important to avoid its complete destruction in times comparable to those of information processing tasks. Here, the effect of local noise on a class of entangled states used in entanglement-based quantum key distribution is considered and the threat ESD might pose to it is assessed.     

Risk management — a key to security in the electronic funds transfer system

The problems associated with security in the electronic funds transfer systems (EFTS) have been the subject of much research and concern in the business community. Consumers are especially wary of the possibilities of loss through EFTS transactions. Before widespread acceptance of the EPTS by consumers can occur, consumer anxiety about EFTS must be reduced.This article suggests a new approach to providing security in the EFTS based on the risk management process which provides techniques for the identification, evaluation, and handling of exposures to risk in the business enterprise. The risk management process can be very effective when applied to the problems associated with EFTS.     

How sensitive is a vineyard crop model to the uncertainty of its runoff module?

Many crop models use the NRCS Curve Number method to estimate runoff, but the simplified assumptions of this method are rarely considered in model uncertainty assessments. The associated uncertainty may be high for cropping systems with a significant part of bare soil like vineyards, specifically under a Mediterranean climate. In this work, we evaluate for a vineyard crop model the structure uncertainty coming from its uncertain runoff module. We introduce a new method based on additional knowledge about the runoff process and on a mathematical property of the model structure. Situations characterized in terms of soil water content and mean runoff conditions are studied for two applications of the vineyard model and guidelines for model users are derived. This work shows that uncertainty quantification can benefit from the knowledge of mathematical properties of a model and provide clear guidelines to model users.     

Usability of a cloud-based collaborative learning framework to improve learners’ experience

Computer-Supported Collaborative Learning (CSCL) is concerned with how Information and Communication Technology (ICT) might facilitate learning in groups which can be co-located or distributed over a network of computers such as Internet. CSCL supports effective learning by means of communication of ideas and information among learners, collaborative access of essential documents, and feedback from instructors and peers on learning activities. As the cloud technologies are increasingly becoming popular and collaborative learning is evolving, new directions for development of collaborative learning tools deployed on cloud are proposed. Development of such learning tools requires access to substantial data stored in the cloud. Ensuring efficient access to such data is hindered by the high latencies of wide-area networks underlying the cloud infrastructures. To improve learners’ experience by accelerating data access, important files can be replicated so a group of learners can access data from nearby locations. Since a cloud environment is highly dynamic, resource availability, network latency, and learner requests may change. In this paper, we present the advantages of collaborative learning and focus on the importance of data replication in the design of such a dynamic cloud-based system that a collaborative learning portal uses. To this end, we introduce a highly distributed replication technique that determines optimal data locations to improve access performance by minimizing replication overhead (access and update). The problem is formulated using dynamic programming. Experimental results demonstrate the usefulness of the proposed collaborative learning system used by institutions in geographically distributed locations.     

Partial Similarity of Objects,or How to Compare a Centaur to a Horse

Similarity is one of the most important abstract concepts in human perception of the world. In computer vision, numerous applications deal with comparing objects observed in a scene with some a priori known patterns. Often, it happens that while two objects are not similar, they have large similar parts, that is, they are partially similar. Here, we present a novel approach to quantify partial similarity using the notion of Pareto optimality. We exemplify our approach on the problems of recognizing non-rigid geometric objects, images, and analyzing text sequences.