9346791
On the Security of RSA with Primes Sharing Least-Significant Bits
Abstract.We investigate the security of a variant of the RSA public-key cryptosystem called LSBS-RSA, in which the modulus primes share a large number of least-significant bits. We show that low public-exponent LSBS-RSA is inherently resistant to Partial Key Exposure (PKE) attacks in which least-significant bits of the secret exponent are revealed to the attacker, and in particular that the Boneh-Durfee-Frankel PKE attack [5] on low public-exponent RSA is less effective for LSBS-RSA systems than for standard RSA. On the other hand, we show that large public-exponent LSBS-RSA is more vulnerable to such attacks than standard RSA. An application to server-aided RSA signature generation is proposed.
266815
Unconditionally Secure Digital Signature Schemes Admitting Transferability
A potentially serious problem with current digital signature schemes is that their underlying hard problems from number theory may be solved by an innovative technique or a new generation of computing devices such as quantum computers. Therefore while these signature schemes represent an efficient solution to the short term integrity (unforgeability and non-repudiation) of digital data, they provide no confidence on the long term (say of 20 years) integrity of data signed by these schemes. In this work, we focus on signature schemes whose security does not rely on any unproven assumption. More specifically, we establish a model for unconditionally secure digital signatures in a group, and demonstrate practical schemes in that model. An added advantage of the schemes is that they allow unlimited transfer of signatures without compromising the security of the schemes. Our scheme represents the first unconditionally secure signature that admits provably secure transfer of signatures.
36265866
A Security Acceleration Using XML Signcryption Scheme in Mobile Grid Web Services
Today's grid architecture encompasses a far greater breadth of applications than the traditional grid, which focused on distributed applications processing large amounts of data. Newer grid applications are more data-centric and more focused on distributed services. As these trends, mobile internet and the grid, are likely to find each other the resource constraints that wireless devices pose today affect the level of interoperability between them. The goal of this paper is to investigate how well the most limited wireless devices can make the use of grid security services. This paper describes a novel security approach on fast mobile grid services based on current mobile web services platform environment using XML signcryption mechanism.
17666125
Plateaued Functions
The focus of this paper is on nonlinear characteristics of cryptographic Boolean functions First we introduce the notion of plateaued functions that have many cryptographically desirable properties Second we establish a sequence of strengthened inequalities on some of the most important nonlinearity criteria including nonlinearity propagation and correlation immunity and prove that critical cases of the inequalities co incide with characterizations of plateaued functions We then proceed to prove that plateaued functions include as a proper subset all partially bent functions that were introduced earlier by Carlet This settles an open question that arises from previously known results on partially bent functions In addition we construct plateaued but not partially bent functions that have many properties useful in cryptography
6962958
Characterising user data protection of software components
Proposes a scheme to characterise non-functional security properties that are embedded within the functionality of software components. The security properties may be attached to various aspects of a component, such as resource allocation, user data protection, communication, and so on. In this paper, we are particularly interested in characterising the user data protection of software components. It is often reported that software components usually suffer from security and reliability problems. It is now widely recognised that the characterisation of the security properties of software components is an important issue to boost the confidence and trust in component technology. To address this issue, the characterisation of the security properties of components is the first challenging step. The work proposed in this paper is partially based on the functional requirements defined in the Common Criteria for Information Technology Security Evaluation endorsed by NIST. The applicability of the proposed scheme is demonstrated with a simple example.
7417533
Cryptographically resilient functions
This correspondence studies resilient functions which have applications in fault-tolerant distributed computing, quantum cryptographic key distribution, and random sequence generation for stream ciphers. We present a number of new methods for synthesizing resilient functions. An interesting aspect of these methods is that they are applicable both to linear and nonlinear resilient functions. Our second major contribution is to show that every linear resilient function can be transformed into a large number of nonlinear resilient functions with the same parameters. As a result, we obtain resilient functions that are highly nonlinear and have a high algebraic degree.
6047065
Efficiently Supporting Structure Queries on Phylogenetic Trees
With phylogenetics becoming increasingly important in biomedical research, the number of phylogenetic studies is increasing rapidly and huge mount of phylogenetic data has been generated and stored in databases. How to efficiently extract information from the data has become an important research problem. In this paper, we focus on a class of important queries on phylogenetic trees: structure queries which include least common ancestor, minimal spanning clade, tree pattern match and tree projection. After analyzing the characteristics of the phylogenetic tree as well as structure queries, we propose a storage system based on labeling using RDBMS and design algorithms for query evaluation. We implement these algorithms and compare them with existing techniques. Performance studies prove the efficiency of our strategy.
7580725
Kosha: A Peer-to-Peer Enhancement for the Network File System
The storage needs of modern scientific applications are growing exponentially, and designing economical storage solutions for such applications – especially in Grid environments – is an important research topic. This work presents Kosha, a system that aims to harvest redundant storage space on cluster nodes and user desktops to provide a reliable, shared file system that acts as a large distributed storage. Kosha utilizes peer-to-peer (p2p) mechanisms to enhance the widely-used Network File System (NFS). P2P storage systems provide location transparency, mobility transparency, load balancing, and file replication – features that are not available in NFS. On the other hand, NFS provides hierarchical file organization, directory listings, and file permissions, which are missing from p2p storage systems. By blending the strengths of NFS and p2p storage systems, Kosha provides a low overhead storage solution. Our experiments show that compared to unmodified NFS, Kosha introduces a 3.3% fixed overhead and 4.5% additional overhead as nodes are increased from two to sixteen. For larger number of nodes, the additional overhead increases slowly. Kosha achieves load balancing in distributed directories, and guarantees $99.99\%$ or better file availability.
2500181
Video object segmentation and tracking using /spl psi/-learning classification
As a requisite of the emerging content-based multimedia technologies, video object (VO) extraction is of great importance. This paper presents a novel semiautomatic segmentation and tracking method for single VO extraction. Unlike traditional approaches, the proposed method formulates the separation of the VO from the background as a classification problem. Each frame is divided into small blocks of uniform size, which are called object blocks if the centering pixels belong to the object, or background blocks otherwise. After a manual segmentation of the first frame, the blocks of this frame are used as the training samples for the object-background classifier. A newly developed learning tool called /spl psi/-learning is employed to train the classifier which outperforms the conventional Support Vector Machines in linearly nonseparable cases. To deal with large and complex objects, a multilayer approach constructing a so-called hyperplane tree is proposed. Each node of the tree represents a hyperplane, responsible for classifying only a subset of the training samples. Multiple hyperplanes are thus needed to classify the entire set. Through the combination of the multilayer scheme and /spl psi/-learning, one can avoid the complexity of nonlinear mapping as well as achieve high classification accuracy. During the tracking phase, the pixel in the center of every block in a successive frame is classified by a sequence of hyperplanes from the root to a leaf node of the hyperplane tree, and the class of the block is identified accordingly. All the object blocks thus form the object of interest, whose boundary unfortunately is stair-like due to the block effect. In order to obtain the pixel-wise boundary in a cost efficient way, a pyramid boundary refining algorithm is designed, which iteratively selects a few informative pixels for class label checking, and reduces uncertainty about the actual boundary of the object. The proposed method has been applied on video sequences with various spatial and temporal characteristics, and experimental results demonstrate it to be effective, efficient, and robust.
1828938
Crimson: a data management system to support evaluating phylogenetic tree reconstruction algorithms
Evolutionary and systems biology increasingly rely on the construction of large phylogenetic trees which represent the relationships between species of interest. As the number and size of such trees increases, so does the need for efficient data storage and query capabilities. Although much attention has been focused on XML as a tree data model, phylogenetic trees differ from document-oriented applications in their size and depth, and their need for structure-based queries rather than path-based queries.This paper focuses on Crimson, a tree storage system for phylogenetic trees used to evaluate phylogenetic tree reconstruction algorithms within the context of the NSF CIPRes project. A goal of the modeling component of the CIPRes project is to construct a huge simulation tree representing a "gold standard" of evolutionary history against which phylogenetic tree reconstruction algorithms can be tested.In this demonstration, we highlight our storage and indexing strategies and show how Crimson is used for benchmarking phylogenetic tree reconstruction algorithms. We also show how our design can be used to support more general queries over phylogenetic trees.
33641222
Object tracking using the Gabor wavelet transform and the golden section algorithm
The paper presents an object tracking method for object-based video processing which uses a two-dimensional (2D) Gabor wavelet transform (GWT) and a 2D golden section algorithm. An object in the current frame is modeled by local features from a number of the selected feature points, and the global placement of these feature points. The feature points are stochastically selected based on the energy of their GWT coefficients. Points with higher energy have a higher probability of being selected since they are visually more important. The amplitudes of the GWT coefficients of a feature point are then used as the local feature. The global placement of the feature points is determined by a 2D mesh whose feature is the area of the triangles formed by the feature points. In this way, a local feature is represented by a GWT coefficient amplitude vector, and a global feature is represented by a triangle area vector. One advantage of the 2D mesh is that the direction of its triangle area vector is invariant to affine transform. Consequently, the similarity between two local features or two global features can be defined as a function of the angle and the length ratio between two vectors, and the overall similarity between two objects is a weighted sum of the local and global similarities. In order to find the corresponding object in the next frame, the 2D golden section algorithm is employed. Our results show that the method is robust to object deformation and supports object tracking in noisy video sequences.