17152003
WLAN Security: Current and Future
Wireless LAN deployment improves users' mobility, but it also brings a range of security issues that affect emerging standards and related technologies.
11332993
Fine-Grained and Scalable Approaches for Message Integrity
When we have multiple users compiling a single message, including shared contents, metadata, policy, and so on, the integrity of the contents created by individual users needs to be maintained in an effective manner. There is an urgent need for new mechanisms in a trusted content-sharing environment to support multiple signers for the same message, which can be dynamically updated with autonomous protection and maintenance mechanisms. In our previous work we identified and compared three different binding mechanisms including monolithic, autonomous, and chained binding mechanisms, using digital signatures. The original work was designed and implemented for digital certificates. In this paper we apply those schemes with extension to the organization-to-organization messaging services that require effective integrity verification and tracking mechanisms at the user-level in the receiving organization in a scalable manner with fine granularity. We implement our ideas in the Java remote method invocation (RMI) platform and discuss the trade-offs of the signature schemes based on our experimental results
13486405
Static vs. dynamic recovery models for survivable distributed systems
The need for survivability is more pressing for mission-critical systems, especially when they are integrated with other COTS products or services. As information systems became more complex and the interdependence of these systems became higher, the survivability picture became more complicated. In this paper, we introduce two basic models with respect to static and dynamic models, where each model has restart and continue modes. We describe each approach and compare the trade-offs in terms of simplicity, resource efficiency, adaptation, service downtime, immunization, and robustness. Later, we introduce a hybrid model by combining these two basic models. Our approaches are transparent to the client side and can be applied to existing distributed systems by extending the server side with the components necessary for the schemes.
11119047
Component-abnormality detection and immunization for survivable systems in large distributed environments
44345092
Accurate object contour tracking based on boundary edge selection
In this paper, a novel method for accurate subject tracking, by selecting only tracked subject boundary edges in a video stream with a changing background and moving camera, is proposed. This boundary edge selection is achieved in two steps: (1) removing background edges using edge motion, and from the output of the previous step, (2) selecting boundary edges using a normal direction derivative of the tracked contour. Accurate tracking is based on reduction of the effects of irrelevant edges, by only selecting boundary edge pixels. In order to remove background edges using edge motion, the tracked subject motion is computed and edge motions and edges having different motion directions from the subjects are removed. In selecting boundary edges using the normal contour direction, the image gradient values on every edge pixel are computed, and edge pixels with large gradient values are selected. Multi-level Canny edge maps are used to obtain proper details of a scene. Multi-level edge maps allow tracking, even though the tracked object boundary has complex edges, since the detail level of an edge map for the scene can be adjusted. A process of final routing is deployed in order to obtain a detailed contour. The computed contour is improved by checking against a strong Canny edge map and hiring strong Canny edge pixels around the computed contour using Dijkstra's minimum cost routing. The experimental results demonstrate that the proposed tracking approach is robust enough to handle a complex-textured scene in a mobile camera environment.
8794763
Video Retrieval of Human Interactions Using Model-Based Motion Tracking and Multi-layer Finite State Automata
Recognition of human interactions in a video is useful for video annotation, automated surveillance, and content-based video retrieval. This paper presents a model-based approach to motion tracking and recognition of human interactions using multi-layer finite state automata (FA). The system is used for widely-available, static-background monocular surveillance videos. A three-dimensional human body model is built using a sphere and cylinders and is projected on a two-dimensional image plane to fit the foreground image silhouette. We convert the human motion tracking problem into a parameter optimization problem without the need to compute inverse kinematics. A cost functional is used to estimate the degree of the overlap between the foreground input image silhouette and a projected three-dimensional body model silhouette. Motion data obtained from the tracker is analyzed in terms of feet, torso, and hands by a behavior recognition system. The recognition model represents human behavior as a sequence of states that register the configuration of individual body parts in space and time. In order to overcome the exponential growth of the number of states that usually occurs in single-level FA, we propose a multi-layer FA that abstracts states and events from motion data at multiple levels: low-level FA analyzes body parts only, and high-level FA analyzes the human interaction. Motion tracking results from video sequences are presented. Our recognition framework successfully recognizes various human interactions such as approaching, departing, pushing, pointing, and handshaking.
15806644
Attribute Mutability in Usage Control
The notion of Usage Control (UCON) has been introduced recently to extend traditional access controls by including three decision factors called authorizations, obligations, and conditions. Usage control also recognize two important decision properties of continuity and mutability. In access control literature, an authorization decision is commonly made by utilizing some form of subject and object attributes. Identities, security labels and roles are some examples of attributes. Traditionally these attributes are assigned to subjects and objects by a security officer and can be modified only by administrative actions. However, in modern information systems these attributes are often required to be changed as a side effect of subject’s usage on object. This requirement of updates has been recognized and defined as mutability property in usage control. In this paper, we discuss issues of this attribute mutability and show how usage control can apply this mutability property in various traditional and modern access control policies.
16088118
An effective hash-based algorithm for mining association rules
In this paper, we examine the issue of mining association rules among items in a large database of sales transactions. The mining of association rules can be mapped into the problem of discovering large itemsets where a large itemset is a group of items which appear in a sufficient number of transactions. The problem of discovering large itemsets can be solved by constructing a candidate set of itemsets first and then, identifying, within this candidate set, those itemsets that meet the large itemset requirement. Generally this is done iteratively for each large k-itemset in increasing order of k where a large k-itemset is a large itemset with k items. To determine large itemsets from a huge number of candidate large itemsets in early iterations is usually the dominating factor for the overall data mining performance. To address this issue, we propose an effective hash-based algorithm for the candidate set generation. Explicitly, the number of candidate 2-itemsets generated by the proposed algorithm is, in orders of magnitude, smaller than that by previous methods, thus resolving the performance bottleneck. Note that the generation of smaller candidate sets enables us to effectively trim the transaction database size at a much earlier stage of the iterations, thereby reducing the computational cost for later iterations significantly. Extensive simulation study is conducted to evaluate performance of the proposed algorithm.
10180647
Specularity elimination in range sensing for accurate 3D modeling of specular objects
We present a novel range sensing method that is capable of constructing accurate 3D models of specular objects. Our method utilizes a new range imaging concept called multipeak range imaging, which accounts for the effects of mutual reflections. False measurements generated by mutual reflections are then eliminated by applying a series of constraint tests based on local smoothness, global coordinate consistency and visibility consistency. We show the usefulness of our method by applying the method to three real objects with specular surfaces. The ground truth data for those three objects were also acquired in order to evaluate the elimination of false measurements and to justify the selection of the parameters in the constraint tests. Experimental results indicate that our method significantly improves upon the traditional methods for constructing reliable 3D models of specular objects with complex shapes.