40955091
Hash channels
It is believed that in authentication protocols where no random numbers are involved, it is hard to introduce subliminal channels. In this paper we show that subliminal channels exist in digital signature schemes where no random numbers are used. The source where the subliminal channels exist is widely acceptable hash functions with their outputs being of some randomness. Because the subliminal channels are established by using hash functions, the subliminal channels are called hash channels in this paper. This indicates that there exist subliminal channels in any authentication protocols that use hash functions.
13639457
On the independence of Boolean functions
Boolean functions are widely used because they can be used to precisely describe logical circuits. Properties of Boolean functions with respect to their applications to cryptography have been studied, but relationship between Boolean functions are rarely studied. This paper studies the independence of Boolean functions, gives necessary and sufficient conditions for judging whether two given Boolean functions are independent. Some enumeration formulae are given.
11048111
Modified Chinese remainder theorem and its application to proxy signatures
Chinese Remainder Theorem has been used for hundreds of years and has been applied to many domains such as integers and polynomials. An assumption made is that the component moduli are pairwise co-prime. In this paper, first we remove this assumption; then we give an algorithm to find whether a given system of congruent equations has a solution, and if so, how to find the solution in an efficient manner. Further we apply the modified Chinese Remainder Theorem to design proxy signatures.
47400657
Construction of correlation immune Boolean functions
It is shown in this paper that every correlation immune Boolean function of n variables can be written as f(x) = g(xGT ), where g is an algebraic non-degenerate Boolean function of k (k ≤ n) variables and G is a generating matrix of an [n, k, d] linear code. It is known that the correlation immunity of f (x) is at least d − 1. In this paper we further prove when the correlation immunity exceeds this lower bound. A method which can theoretically search exhaustively all possible correlation immune functions is proposed, while constructions of higher order correlation immune functions as well as algebraic non-degenerate correlation immune functions are discussed in particular. It is also shown that many cryptographic properties of g can be inherited by the correlation immune function f (x) = g(xGT) which is an important property for choosing useful correlation immune functions.
41090415
Correlation immunity and resiliency of symmetric Boolean functions
Correlation immunity of symmetric Boolean functions is studied in this paper. Lower bounds on the number of constructible correlation immune symmetric functions are given. Constructions for such new balanced functions are presented. These functions are also known as 1-resilient functions. In 1985, Chor et al. conjectured that the only 1-resilient symmetric functions are the exclusive-or of all n variables and its negation. This conjecture, however, was disproved by Gopalakrishnan, Hoffman and Stinson in 1993 by giving a class of infinite counterexamples, and they noted that it does not seem to extend any further in an obvious way. In this paper two more infinite classes of such examples are presented for n being even and being odd, respectively, and consequently one of the two open problems proposed by Gopalakrishnan et al., is addressed by constructing new symmetric resilient functions.
414035
Internet voting: concerns and solutions
Internet voting systems, catering to different requirements, have been widely implemented and used. Some have been successful, while others have experienced unexpected problems. This paper overviews the concerns of using Internet voting and tries to give solutions. Tradeoffs between the advantages and disadvantages of employing Internet voting are also addressed. A simple protocol is designed to show that technical problems identified in the literature can be solved fairly easily, though some seem subtle. This study reveals that the main concerns of adopting Internet voting for critical elections are not cryptographic tools, but hardware and software reliability, and social and political issues. After discussing possible concerns about Internet voting and possible solutions or comments, we propose steps to enable Internet voting to be adopted even for critical elections.
17356448
Web Directory Integration Using Conditional Random Fields
The purpose of integrating web directories is to transfer instances from a source to a target directory. Unlike conventional text categorization, in directory integration, there is extra information about the source directory that can be used to improve the classification accuracy. Many approaches exploit the measured similarity between two corresponding classes to enhance traditional text classifiers. These methods perform well if the topics of two classes are very similar, but they could lead to misclassification if the topics are dissimilar. We propose a directory integration approach based on the conditional random fields (CRFs) model, and model the integration process using a finite-state model. The advantage of using CRFs is that the transition features naturally include information about the relations between classes. Our results show that CRFs outperform conventional text classifiers. In addition, CRFs allow us to apply complex features to integrate the information about the contents of class and their labels. The performance of our approach can be improved by applying these features, especially for instances whose source and target classes are moderately similar
471313
Dependence network modeling for biomarker identification
MOTIVATION
Our purpose is to develop a statistical modeling approach for cancer biomarker discovery and provide new insights into early cancer detection. We propose the concept of dependence network, apply it for identifying cancer biomarkers, and study the difference between the protein or gene samples from cancer and non-cancer subjects based on mass-spectrometry (MS) and microarray data.


RESULTS
Three MS and two gene microarray datasets are studied. Clear differences are observed in the dependence networks for cancer and non-cancer samples. Protein/gene features are examined three at one time through an exhaustive search. Dependence networks are constructed by binding triples identified by the eigenvalue pattern of the dependence model, and are further compared to identify cancer biomarkers. Such dependence-network-based biomarkers show much greater consistency under 10-fold cross-validation than the classification-performance-based biomarkers. Furthermore, the biological relevance of the dependence-network-based biomarkers using microarray data is discussed. The proposed scheme is shown promising for cancer diagnosis and prediction.


AVAILABILITY
See supplements: http://dsplab.eng.umd.edu/~genomics/dependencenetwork/
7443931
Limitation of superscalar microprocessor performance
Today’s microprocessors are striving to get the highest possible performance. A new breed of microprocessors called superscalar which execute multiple instructions per clock cycle. The major problem of executing multiple instructions in a scalar program is the handling of data dependencies. If data dependencies are not effectively handled, it is difficult to achieve an execution rate of more than one instruction per clock cycle. In this study, we use a novel multi-bit control for handling of data dependencies for out-of-order execution and completion of instructions. This paper presents the maximum performance of the superscalar microprocessor using two simulation models and one calculation model. The first simulation model uses real benchmark programs, and the second model uses queuing networks. The calculation model derives the formula for deficiencies from the peak performance.
6603995
Protein family classification and functional annotation
With the accelerated accumulation of genomic sequence data, there is a pressing need to develop computational methods and advanced bioinformatics infrastructure for reliable and large-scale protein annotation and biological knowledge discovery. The Protein Information Resource (PIR) provides an integrated public resource of protein informatics to support genomic and proteomic research. PIR produces the Protein Sequence Database of functionally annotated protein sequences. The annotation problems are addressed by a classification-driven and rule-based method with evidence attribution, coupled with an integrated knowledge base system being developed. The approach allows sensitive identification, consistent and rich annotation, and systematic detection of annotation errors, as well as distinction of experimentally verified and computationally predicted features. The knowledge base consists of two new databases, sequence analysis tools, and graphical interfaces. PIR-NREF, a non-redundant reference database, provides a timely and comprehensive collection of all protein sequences, totaling more than 1,000,000 entries. iProClass, an integrated database of protein family, function, and structure information, provides extensive value-added features for about 830,000 proteins with rich links to over 50 molecular databases. This paper describes our approach to protein functional annotation with case studies and examines common identification errors. It also illustrates that data integration in PIR supports exploration of protein relationships and may reveal protein functional associations beyond sequence homology.
41641437
Network Facility for a Reconfigurable Computer Architecture