961760
Revisiting Colored Networks and Privacy Preserving Censorship
Reliable networks are obviously an important aspect of critical information infrastructures. Dolev-Dwork-Waarts-Yung linked research on reliable point-to-point networks with privacy and authenticity. In their threat model the adversary can only take over a number of nodes bounded by a threshold k. Hirt-Maurer introduced the concept of an adversary structure (i.e. the complement of an access structure). Kumar-Goundan-Srinathan-Rangan and Desmedt-Wang-Burmester generalized Dolev-Dwork-Waarts-Yung scenarios to the case of a general adversary structure. 
 
Burmester-Desmedt introduced a special adversary structure, now called a color based adversary structure. Their argument in favor of their model is that using automated attacks (such as worms), a vulnerability can be exploited on all computers in the network running the same platform (color). In their model the adversary can control all nodes that use up to k different platforms (or colors). 
 
We will demonstrate one of the limitations of their model. Although the family of color based adversary structures has a trivial representation which size grows polynomial in the size of the graph, we will demonstrate in this paper that deciding reliability issues and security issues are co-NP-complete. 
 
In most societies censorship is common. Indeed, for centuries it has often been viewed by authorities as an essential security tool. We apply the computational complexity result to study censorship. Authorities may require network designers to demonstrate the capability to censor the internet. We present a zero-knowledge interactive proof for the case of a color based adversary structure.
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.
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.
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.
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.
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.
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.
40360434
Measurement of the cognitive functional complexity of software
One of the central problems in software engineering is its inherited complexity. It is recognized that cognitive informatics plays an important role in understanding the fundamental characteristics of software. This paper models the cognitive weights of basic control structures of software, and develops a new concept of cognitive functional size for measuring software complexity. Comparative case studies between the cognitive functional size and physical sizes of 20 programs are conducted. It is found that for a given design, although the physical sizes of software may vary in a wide range, the cognitive functional sizes are much stable and independent from implementation technologies and programming languages. Therefore, the cognitive functional size provides a novel, stable and practical software complexity measurement and is helpful to explain the fundamental nature of software complexity in the phase of design, implementation, or maintenance in software engineering.
14088697
Approximate shortest paths in anisotropic regions
Our goal is to find an approximate shortest path for a point robot moving in a planar subdivision with <i>n</i> vertices. Let ρ ≥ 1 be a real number. Distances in each face of this subdivision are measured by a convex distance function whose unit disk is contained in a concentric unit Euclidean disk, and contains a concentric Euclidean disk with radius 1/ρ. Different convex distance functions may be used for different faces, and obstacles are allowed. These convex distance functions may be asymmetric. For all ε ∈ (0, 1), and for any two points <i>v<inf>s</inf></i> and <i>v<inf>d</inf></i>, we give an algorithm that finds a path from <i>v<inf>s</inf></i> to <i>v<inf>d</inf></i> whose cost is at most (1 + ε) times the minimum cost. Our algorithm runs in <i>O</i> (ρ<sub>2</sub>logρ/ε<sup>2</sup>n<sup>3</sup> log (ρn/ε)) time. This bound does not depend on any other parameters; in particular, it does not depend on the minimum angle in the subdivision. We give applications to two special cases that have been considered before: the weighted region problem and motion planning in the presence of uniform flows. For the weighted region problem with weights in [1, ρ] ∪ {∞}, the time bound of our algorithm improves to <i>O</i> (ρ<sub>2</sub>logρ/εn<sup>3</sup> log (ρn/ε)).
3063945
Statistical-based approach to word segmentation
This paper presents a text word extraction algorithm that takes a set of bounding boxes of glyphs and their associated text lines of a given document and partitions the glyphs into a set of text words, using only the geometric information of the input glyphs. The algorithm is probability based. An iterative, relaxation-like method is used to find the partitioning solution that maximizes the joint probability. To evaluate the performance of our test word extraction algorithm, we used a 3-fold validation method and developed a quantitative performance measure. The algorithm was evaluated on the UW-III database of some 1600 scanned document image pages. An area-overlap measure was used to find the correspondence between the detected entities and the ground-truth. For a total of 827, 433 ground truth words, the algorithm identified and segmented 800, 149 words correctly, an accuracy of 97.43%.
1164311
Trust and reputation model in peer-to-peer networks
It is important to enable peers to represent and update their trust in other peers in open networks for sharing files, and especially services. We propose a Bayesian network-based trust model and a method for building reputation based on recommendations in peer-to-peer networks. Since trust is multifaceted, peers need to develop differentiated trust in different aspects of other peers' capability. The peer's needs are different in different situations. Depending on the situation, a peer may need to consider its trust in a specific aspect of another peer's capability or in multiple aspects. Bayesian networks provide a flexible method to present differentiated trust and combine different aspects of trust. The evaluation of the model using a simulation shows that the system where peers communicate their experiences (recommendations) outperforms the system where peers do not share recommendations with each other and that a differentiated trust adds to the performance in terms of percentage of successful interactions.