15910986
Approximation Hardness and Secure Communication in Broadcast Channels
Problems of secure communication and computation have been studied extensively in network models. Goldreich, Goldwasser, and Linial, Franklin and Yung, and Franklin and Wright have initiated the study of secure communication and secure computation in multi-recipient (broadcast) models. A “broadcast channel” (such as Ethernet) enables one processor to send the same message–simultaneously and privately–to a fixed subset of processors. Franklin and Wright, and Wang and Desmedt have shown that if there are at most k malicious (Byzantine style) processors, then there is an efficient protocol for achieving probabilisticly reliable and perfectly private communication in a strongly n-connected network where n≥ k+1. While these results are unconditional, we will consider these problems in the scenario of conditional reliability, and then improve the bounds. In this paper, using the results for hardness of approximation and optimization problems, we will design communication protocols (with broadcast channels) which could defeat more faults than possible with the state of the art. Specifically, assuming certain approximation hardness result, we will construct strongly n-connected graphs which could defeat a k-active adversary (whose computation power is polynomially bounded) for k=cn, where c>1 is any given constant. This result improves a great deal on the results of Franklin and Wright, and Wang and Desmedt.
8247434
NP-Hard Sets are Superterse Unless NP is Small
Abstract We show that the class P- mc ( n ) of polynomial time n -membership comparable sets (defined by Ogihara, 1995) has p -measure 0. Using this result, we will show that the class of sets which are ⩽ tt P -reducible to some P-selective set has p -measure 0. Furthermore, we will show that if NP does not have p -measure 0 then no ⩽ tt p -hard set for NP is P-approximable.
5215725
Linear Complexity versus Pseudorandomness: On Beth and Dai's Result
Beth and Dai studied in their Eurocrypt paper [1] the relationship between linear complexity (that is, the length of the shortest Linear Feedback Shift Register that generates the given strings) of strings and the Kolmogorov complexity of strings. Though their results are correct, some of their proofs are incorrect. In this note, we demonstrate with a counterexample the reason why their proofs are incorrect and we prove a stronger result. We conclude our note with some comments on the use of the LIL test (the law of the iterated logarithm) for pseudorandom bits generated by pseudorandom generators.
8968053
Resource-Bounded Balanced Genericity, Stochasticity and Weak Randomness
We introduce balanced t(n)-genericity which is a refinement of the genericity concept of Ambos-Spies, Fleischhack and Huwig [2] and which in addition controls the frequency with which a condition is met. We show that this concept coincides with the resource-bounded version of Church's stochasticity [6]. By uniformly describing these concepts and weaker notions of stochasticity introduced by Wilber [19] and Ko [11] in terms of prediction functions, we clarify the relations among these resource-bounded stochasticity concepts. Moreover, we give descriptions of these concepts in the framework of Lutz's resource-bounded measure theory [13] based on martingales: We show that t(n)-stochasticity coincides with a weak notion of t(n)-randomness based on so-called simple martingales but that it is strictly weaker than t(n)-randomness in the sense of Lutz.
5782664
A Separation of Two Randomness Concepts
In this paper we give an affirmative answer to a conjecture by Lutz (1992). That is, we will show that there is a Schnorr random sequence which is not rec-random.
8204880
Privacy aware data generation for testing database applications
Testing of database applications is of great importance. A significant issue in database application testing consists in the availability of representative data. In this paper, we investigate the problem of generating a synthetic database based on a-priori knowledge about a production database. Our approach is to fit general location model using various characteristics (e.g., constraints, statistics, rules) extracted from the production database and then generate the synthetic data using model learnt. The generated data is valid and similar to real data in terms of statistical distribution, hence it can be used for functional and performance testing. As characteristics extracted may contain information which may be used by attacker to derive some confidential information about individuals, we present our disclosure analysis method which applies cell suppression technique for identity disclosure analysis and perturbation for value disclosure.
6693323
Automated Surface Matching Using Mutual Information Applied to Riemann Surface Structures
Many medical imaging applications require the computation of dense correspondence vector fields that match one surface with another. To avoid the need for a large set of manually-defined landmarks to constrain these surface correspondences, we developed an algorithm to automate the matching of surface features. It extends the mutual information method to automatically match general 3D surfaces (including surfaces with a branching topology). First, we use holomorphic 1-forms to induce consistent conformal grids on both surfaces. High genus surfaces are mapped to a set of rectangles in the Euclidean plane, and closed genus-zero surfaces are mapped to the sphere. Mutual information is used as a cost functional to drive a fluid flow in the parameter domain that optimally aligns stable geometric features (mean curvature and the conformal factor) in the 2D parameter domains. A diffeomorphic surface-to-surface mapping is then recovered that matches anatomy in 3D. We also present a spectral method that ensures that the grids induced on the target surface remain conformal when pulled through the correspondence field. Using the chain rule, we express the gradient of the mutual information between surfaces in the conformal basis of the source surface. This finite-dimensional linear space generates all conformal reparameterizations of the surface. We apply the method to hippocampal surface registration, a key step in subcortical shape analysis in Alzheimer's disease and schizophrenia.
17279570
Protocol Design and Optimization for Delay/Fault-Tolerant Mobile Sensor Networks
While extensive studies have been carried out in the past several years for many sensor applications, they cannot be applied to the network with extremely low and intermittent connectivity, dubbed the delay/fault-tolerant mobile sensor network (DFT-MSN). Without end-to-end connections due to sparse network density and sensor node mobility, routing in DFT-MSN becomes localized and ties closely to medium access control, which naturally calls for merging Layer 3 and Layer 2 protocols in order to reduce overhead and improve network efficiency. DFT-MSN is fundamentally an opportunistic network, where the communication links exist only with certain probabilities and become the scarcest resource. At the same time, the sensor nodes in DFT-MSN have very limited battery power like those in other sensor networks. Clearly, there is a tradeoff between link utilization and energy efficiency. To address this tradeoff, we develop a cross-layer data delivery protocol for DFT-MSN, which includes two phases, i.e., the asynchronous phase and the synchronous phase. In the first phase, the sender contacts its neighbors to identify a set of appropriate receivers. Since no central control exists, the communication in the first phase is contention-based. In the second phase, the sender gains channel control and multicasts its data message to the receivers. Furthermore, several optimization issues in these two phases are identified, with solutions provided to reduce the collision probability and to balance between link utilization and energy efficiency. Our results show that the proposed cross-layer data delivery protocol for DFT-MSN achieves a high message delivery ratio with low energy consumption and an acceptable delay.
10668110
Evaluating the effects of real world distraction on user performance in virtual environments
Although many virtual environment (VE) technologies such as the four-screen CAVE™ are described as immersive, users can still perceive distractions from the real world. This exposure to real-world distraction may reduce users' sense of presence, and if presence is correlated with performance as some have claimed, the real-world distractions may also hinder performance. Thus, VE designers may want to consider ways to reduce real-world distraction. This paper presents an experiment to investigate the effect of reduced visual stimulus in the peripheral area on user performance and the usability of an immersive VE. We carefully designed three tasks that cause different levels of awareness of the real-world distraction. Using these tasks, we evaluated users' performance and preference in two conditions. The low-stimulus condition was created by hanging a black cloth across the missing back wall of a CAVE. The high-stimulus condition was created by projected animations and real human motion outside the CAVE. The experiments show that reduced distraction may have a positive or negative effect on user performance, depending on the specific tasks and environments.
13902697
A Novel Rule Ordering Approach in Classification Association Rule Mining
A Classification Association Rule (CAR), a common type of mined knowledge in Data Mining, describes an implicative co-occurring relationship between a set of binary-valued data-attributes (items) and a pre-defined class, expressed in the form of an "antecedent $\Rightarrow$ (consequent-class" rule. Classification Association Rule Mining (CARM) is a recent Classification Rule Mining (CRM) approach that builds an Association Rule Mining (ARM) based classifier using CARs. Regardless of which particular methodology is used to build it, a classifier is usually presented as an ordered CAR list, based on an applied rule ordering strategy. Five existing rule ordering mechanisms can be identified: (1) Confi-dence-Support-size_of_Antecedent (CSA), (2) size_of_Antecedent-Confidence-Support (ACS), (3) Weighted Relative Accuracy (WRA), (4) Laplace Accuracy, and (5) (i¾?2Testing. In this paper, we divide the above mechanisms into two groups: (i) pure "support-confidence" framework like, and (ii) additive score assigning like. We consequently propose a hybrid rule ordering approach by combining one approach taken from (i) and another approach taken from (ii). The experimental results show that the proposed rule ordering approach performs well with respect to the accuracy of classification.
15897925
Error exponents for channel coding with side information
Capacity formulas and random-coding and sphere-packing exponents are derived for a generalized family of Gel'fand-Pinsker coding problems. Information is to be reliably transmitted through a noisy channel with random state sequence. Partial information about the state sequence is available to the encoder and decoder. Two families of channels are considered: (1) compound discrete memoryless channels (C-DMC); and (2) channels with arbitrary memory, subject to an additive cost constraint, or more generally to a constraint on the conditional type of the channel output given the input. Both problems are closely connected. For the C-DMC case, our random-coding and sphere-packing exponents coincide at high rates, thereby determining the reliability function of the channel family. The random-coding exponent is achieved using a 3D binning scheme and a maximum penalized mutual information decoder. In the case of arbitrary channels, with memory, a larger random-coding error exponent than in the C-DMC case is obtained. Applications of this study include watermarking, data hiding, communication in presence of partially known interferers, and problems such as broadcast channels, all of which involve the fundamental idea of binning.