461605
Grouping Verifiable Content for Selective Disclosure
This paper addresses the issue of selective disclosure of verifiable content. It extends previous work relating to Content Extraction Signatures [21] to implement a more complex structure that encodes a richer, more flexible fragment extraction policy, which includes fragment grouping. The new extraction policy enables the signer to specify both optional and mandatory fragment associations (or groupings) for verifying extracted content.
14223982
Statistical Database Modeling for Privacy Preserving Database Generation
Testing of database applications is of great importance. Although various studies have been conducted to investigate testing techniques for database design, relatively few efforts have been made to explicitly address the testing of database applications which requires a large amount of representative data available. As testing over live production databases is often infeasible in many situations due to the high risks of disclosure of confidential information or incorrect updating of real data, in this paper we investigate the problem of generating synthetic database based on a-priori knowledge about production database. Our approach is to fit general location model using various characteristics (e.g., constraints, statistics, rules) extracted from production database and then generate synthetic data using model learnt. As characteristics extracted may contain information which may be used by attacker to derive some confidential information, we present a disclosure analysis method which is based on cell suppression technique. Our method is effective and efficient to remove aggregate private information during data generation.
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.
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.
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.
105147
Digital Watermarking Robust Against JPEG Compression
Digital watermarking has been considered as an important technique to protect the copyright of digital content. For a digital watermarking method to be effective, it is essential that a watermark embedded in a still or moving image resists against various attacks ranging from compression, filtering to cropping. As JPEG is a dominant still image compression standard for Internet applications, digital watermarking methods that are robust against the JPEG compression are especially useful. Most digital watermarking methods proposed so far work by modulating pixels/coefficients without considering the quality level of JPEG, which renders watermarks readily removable. In this paper, we propose a new method that actively uses the JPEG quality level as a parameter in embedding a watermark into an image. A useful feature of the new method is that the watermark can be extracted even when the image is compressed using JPEG.
6106156
Unsupervised Image Segmentation with Fuzzy Connectedness
In this paper, we report a method to do unsupervised image segmentations based on fuzzy connectedness with scale space theory. A new measure for doing segmented regions' mergence is also proposed. The method can be used in many applications like content based image retrieval and medical image analysis, etc.
10569326
Intelligent compliant motion control
The role of a compliant motion scheme is to control a robot manipulator in contact with its environment. By accommodating with the interaction force, the manipulator can be used to accomplish tasks that involve constrained motions. This paper presents a new work on the compliant motion control for position-controlled manipulator. A new method for achieving efficient interaction between the manipulator and its environment is developed. The interaction force is reduced using a quadratic cost function. In this method, the compliance is formulated as function of the interaction force. An adaptive element is used to update the compliance. The stability of the system is investigated using the Lyapunov approach. Experiments are conducted in our laboratory to demonstrate the use of such scheme.
11180883
An approach to multimodal biomedical image registration utilizing particle swarm optimization
Biomedical image registration, or geometric alignment of two-dimensional and/or three-dimensional (3D) image data, is becoming increasingly important in diagnosis, treatment planning, functional studies, computer-guided therapies, and in biomedical research. Registration based on intensity values usually requires optimization of some similarity metric between the images. Local optimization techniques frequently fail because functions of these metrics with respect to transformation parameters are generally nonconvex and irregular and, therefore, global methods are often required. In this paper, a new evolutionary approach, particle swarm optimization, is adapted for single-slice 3D-to-3D biomedical image registration. A new hybrid particle swarm technique is proposed that incorporates initial user guidance. Multimodal registrations with initial orientations far from the ground truth were performed on three volumes from different modalities. Results of optimizing the normalized mutual information similarity metric were compared with various evolutionary strategies. The hybrid particle swarm technique produced more accurate registrations than the evolutionary strategies in many cases, with comparable convergence. These results demonstrate that particle swarm approaches, along with evolutionary techniques and local methods, are useful in image registration, and emphasize the need for hybrid approaches for difficult registration problems.
5415824
Shared memory programming for large scale machines
This paper describes the design and implementation of a scalable run-time system and an optimizing compiler for Unified Parallel C (UPC). An experimental evaluation on BlueGene/L®, a distributed-memory machine, demonstrates that the combination of the compiler with the runtime system produces programs with performance comparable to that of efficient MPI programs and good performance scalability up to hundreds of thousands of processors.Our runtime system design solves the problem of maintaining shared object consistency efficiently in a distributed memory machine. Our compiler infrastructure simplifies the code generated for parallel loops in UPC through the elimination of affinity tests, eliminates several levels of indirection for accesses to segments of shared arrays that the compiler can prove to be local, and implements remote update operations through a lower-cost asynchronous message. The performance evaluation uses three well-known benchmarks --- HPC RandomAccess, HPC STREAM and NAS CG --- to obtain scaling and absolute performance numbers for these benchmarks on up to 131072 processors, the full BlueGene/L machine. These results were used to win the HPC Challenge Competition at SC05 in Seattle WA, demonstrating that PGAS languages support both productivity and performance.
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.