Reduced Complexity Attacks on the Alternating Step Generator
In this paper, we present some reduced complexity attacks on the Alternating Step Generator (ASG). The attacks are based on a quite general framework and mostly benefit from the low sampling resistance of the ASG, and of an abnormal behavior related to the distribution of the initial states of the stop/go LFSR's which produce a given segment of the output sequence. Our results compare well with previous results as they show a greater flexibility with regard to known output of the ASG, which amounts in reduced complexity. We will also give a closed form for the complexity of attacks on ASG (and SG) as presented in .

title: New Features of Latin Dances: Analysis of Salsa, ChaCha, and Rumba
abstract: The stream cipher Salsa20 was introduced by Bernstein in 2005 as a candidate in the eSTREAM project, accompanied by the reduced versions Salsa20/8 and Salsa20/12. ChaCha is a variant of Salsa20 aiming at bringing better diffusion for similar performance. Variants of Salsa20 with up to 7 rounds (instead of 20) have been broken by differential cryptanalysis, while ChaCha has not been analyzed yet. We introduce a novel method for differential cryptanalysis of Salsa20 and ChaCha, inspired by correlation attacks and related to the notion of neutral bits. This is the first application of neutral bits in stream cipher cryptanalysis. It allows us to break the 256-bit version of Salsa20/8, to bring faster attacks on the 7-round variant, and to break 6- and 7-round ChaCha. In a second part, we analyze the compression function Rumba, built as the XOR of four Salsa20 instances and returning a 512-bit output. We find collision and preimage attacks for two simplified variants, then we discuss differential attacks on the original version, and exploit a high-probability differential to reduce complexity of collision search from 2256to 279for 3-round Rumba. To prove the correctness of our approach we provide examples of collisions and near-collisions on simplified versions.

title: Algebraic Immunity of S-Boxes and Augmented Functions
abstract: In this paper, the algebraic immunity of S-boxes and augmented functions of stream ciphers is investigated. Augmented functions are shown to have some algebraic properties that are not covered by previous measures of immunity. As a result, efficient algebraic attacks with very low data complexity on certain filter generators become possible. In a similar line, the algebraic immunity of the augmented function of the eSTREAM candidate Trivium is experimentally tested. These tests suggest that Trivium has some immunity against algebraic attacks on augmented functions.

title: Non-randomness in eSTREAM Candidates Salsa20 and TSC-4
abstract: Stream cipher initialisation should ensure that the initial state or keystream is not detectably related to the key and initialisation vector. In this paper we analyse the key/IV setup of the eSTREAM Phase 2 candidates Salsa20 and TSC-4. In the case of Salsa20 we demonstrate a key recovery attack on six rounds and observe non-randomness after seven. For TSC-4, non-randomness over the full eight-round initialisation phase is detected, but would also persist for more rounds.

title: Chosen IV Statistical Analysis for Key Recovery Attacks on Stream Ciphers
abstract: A recent framework for chosen IV statistical distinguishing analysis of stream ciphers is exploited and formalized to provide new methods for key recovery attacks. As an application, a key recovery attack on simplified versions of two eSTREAM Phase 3 candidates is given: For Grain-128 with IV initialization reduced to up to 180 of its 256 iterations, and for Trivium with IV initialization reduced to up to 672 of its 1152 iterations, it is experimentally demonstrated how to deduce a few key bits. Evidence is given that the present analysis is not applicable on Grain-128 or Trivium with full IV initialization.

title: Symmetry based indexing of diatoms in an image database
abstract: We introduce several methods for symmetry detection and present results of their experimental evaluation on diatom images. The methods are based on distance lists, cyclic string matching, and gray level gradient direction histograms. From the experimental results it can be concluded that symmetry information is useful for various indexing tasks in image databases. Types of symmetry considered in this paper are rotational and reflectional symmetry of the shape as well as symmetry of the gray level distribution of the internal structure of objects. Using the symmetry based indexing scheme proposed, the effort for the subsequent task of diatom classification can significantly be reduced.

title: Optimizing the catalog search process for e-procurement platforms
abstract: Many e-procurement platforms support XML-based e-catalogs combined with standardized feature descriptions. Beyond the usual keyword search this opens the arena for attribute-based search engines, including parametric search and preference search. We analyze the impact of different search techniques for such e-catalogs on the overall search process costs. It turns out that preference search has a high potential to significantly reduce the process costs. A large-scale use case with the MAN2B e-procurement platform supports our claim. We identify improvements achievable by using preference search, in particular less navigation steps during the product search and better search results due to the BMO query model. Expensive cases, where frustrated users accept bad search results or phone up the company's purchasing department, should decrease significantly. This in turn will enable the purchasing department to focus more on strategic issues like supplier relationship management than on operative issues as it still happens widely today.

title: Automatic Identification of Diatoms Using Decision Forests
abstract: A feature based identification scheme for microscopic images of diatoms is presented in this paper. Diatoms are unicellular algae found in water and other places wherever there is humidity and enough light for photo synthesis. The proposed automatic identification scheme follows a decision tree based classification approach. In this paper two different ensemble learning methods are evaluated and results are compared with those of single decision trees. As test sets two different diatom image databases are used. For each image in the databases general features like symmetry, geometric properties, moment invariants, and Fourier descriptors as well as diatom specific features like striae density and direction are computed.

title: Automatic Identification of Diatoms Using Visual Human-Interpretable Features
abstract: In this paper we present an identification scheme for diatoms using visual human-interpretable features. Diatoms are unicellular algae found in water and other places wherever there is humidity and enough light for photosynthesis. The automatic identification of diatoms has applications in a number of areas, for example, environmental monitoring and climate research. The overall identification is performed by an ensemble of multiple decision trees following the bagging approach. The use of human-interpretable features in contrast to traditional features, such as Fourier descriptors or moment invariants, makes it possible for a human expert to verify the induced decision trees and opens up the possibility of integrating human expert knowledge into automatically derived decision trees.

title: COSIMA- your smart, speaking E-salesperson
abstract: We present a new cooperative user interface for e-shopping. COSIMA is an intelligent Internet avatar with dynamic voice output that assists customers through their e-shopping tours and advises them like a real salesperson. COSIMA uses a meta search engine based on Preference SQL, computing best matching results to the customer's wishes. COSIMA can qualify these results and generates proper voice output. Our presentation shows COSIMA in action for comparison shopping.