17331850
A Systematic Approach to Uncover Security Flaws in GUI Logic
To achieve end-to-end security, traditional machine-to-machine security measures are insufficient if the integrity of the human-computer interface is compromised. GUI logic flaws are a category of software vulnerabilities that result from logic bugs in GUI design/implementation. Visual spoofing attacks that exploit these flaws can lure even security- conscious users to perform unintended actions. The focus of this paper is to formulate the problem of GUI logic flaws and to develop a methodology for uncovering them in software implementations. Specifically, based on an in-depth study of key subsets of Internet Explorer (IE) browser source code, we have developed a formal model for the browser GUI logic and have applied formal reasoning to uncover new spoofing scenarios, including nine for status bar spoofing and four for address bar spoofing. The IE development team has confirmed all these scenarios and has fixed most of them in their latest build. Through this work, we demonstrate that a crucial subset of visual spoofing vulnerabilities originate from GUI logic flaws, which have a well-defined mathematical meaning allowing a systematic analysis.
8456748
Friends Troubleshooting Network: Towards Privacy-Preserving, Automatic Troubleshooting
Content sharing is a popular usage of peer-to-peer systems for its inherent scalability and low cost of maintenance. In this paper, we leverage this nature of peer-to-peer systems to tackle a new problem: automatic misconfiguration troubleshooting. In this setting, machine configurations from the peers are “shared” to diagnose the misconfigurations on a sick machine. A key challenge for such a troubleshooting system is privacy preservation. To this end, we construct Friends Troubleshooting Network (FTN), a peer-to-peer overlay network, where the links between peer machines reflect the friendship of their owners. To preserve privacy, we use historyless and futureless random-walk in the FTN, during which search along with parameter aggregation are carried out for the purpose of troubleshooting. Many of our techniques can be applied to other application scenarios that require privacy-preserving distributed computing and information aggregation. We have also identified a number of open challenges that remain to be addressed.
6932570
3D Surface Matching and Recognition Using Conformal Geometry
3D surface matching is a fundamental issue in computer vision with many applications such as shape registration, 3D object recognition and classification. However, surface matching with noise, occlusion and clutter is a challenging problem. In this paper, we analyze a family of conformal geometric maps including harmonic maps, conformal maps and least squares conformal maps with regards to 3D surface matching. As a result, we propose a novel and computationally efficient surface matching framework that uses least squares conformal maps. According to conformal geometry theory, each 3D surface with disk topology can be mapped to a 2D domain through a global optimization and the resulting map is a diffeomorphism, i.e., one-to-one and onto. This allows us to simplify the 3D surface-matching problem to a 2D image-matching problem, by comparing the resulting 2D conformal geometric maps, which are stable, insensitive to resolution changes and robust to occlusion and noise. Therefore, highly accurate and efficient 3D surface matching algorithms can be achieved by using conformal geometric maps. Finally, the performance of conformal geometric maps is evaluated and analyzed comprehensively in 3D surface matching with occlusion, noise and resolution variation. We also provide a series of experiments on real 3D face data that achieve high recognition rates.
29450095
Cognitive models of the brain
The human brain is the most complicated organ in the universe and a new frontier yet to be explored in an interdisciplinary approach. Investigation of the brain is a unique problem that requires recursive mental power to explore the brain using the brain. This paper attempts to develop functional and cognitive models of the brain by using cognitive informatics and formal methodologies. This paper adopts a memory-based approach to explore the brain, and to demonstrate that memory is the foundation for any natural intelligence. Structures of memories are explored and cognitive models of the natural intelligence are proposed. Cognitive mechanisms of the brain, including hypotheses and theories on the thinking engine of the brain, long-term memory establishment, and roles of sleep in long-term memory development, are investigated. The models and theories are applied to explain a number of fundamental physiological and psychological phenomena.
7748348
Shape fitting with outliers
Given a set <i>H</i> of <i>n</i> hyperplanes in <i>R<sup>d</sup></i>, we present an algorithm that <i>e</i>-approximates the extent between the top and bottom <i>k</i> levels of the arrangement of <i>H</i> in time <i>O(n + (k/e)<sup>c</sup>)</i>, where <i>c</i> is a constant depending on <i>d</i>. The algorithm relies on computing a subset of <i>H</i> of size.<i>O(k/e<sup>d-1</sup>)</i>, in near linear time, such that the <i>k</i>-level of the arrangement of the subset approximates that of the original arrangement. Using this algorithm, we propose efficient approximation algorithms for shape fitting with outliers for various shapes. This is the first algorithms to handle outliers efficiently for the shape fitting problems considered.
5987381
Algorithm performance contest
This contest involved the running and evaluation of computer vision and pattern recognition techniques on different data sets with known groundwidth. The contest included three areas; binary shape recognition, symbol recognition and image flow estimation. A package was made available for each area. Each package contained either real images with manual groundtruth or programs to generate data sets of ideal as well as noisy images with known groundtruth. They also contained programs to evaluate the results of an algorithm according to the given groundtruth. These evaluation criteria included the generation of confusion matrices, computation of the misdetection and false alarm rates and other performance measures suitable for the problems. The paper summarizes the data generation for each area and experimental results for a total of six participating algorithms.
21184887
The cognitive processes of abstraction and formal inferences
Theoretical research is predominately an inductive process; while applied research is mainly a deductive process. Both inference processes are based on the cognitive process and means of abstraction. This paper describes the cognitive processes of abstraction and formal inferences such as deduction, induction, abduction, and analogy. The hierarchy of abstraction and the descriptivity of abstract means at different levels are analyzed. A set of mathematical models of formal inference methodologies are developed. Formal descriptions of the five cognitive processes of abstraction and inferences are presented using real-time process algebra (RTPA). Applications of abstraction and formal inferences in dealing with complicated problems in large-scale software system development in software engineering are discussed.