242170
Active security support for active networks
Active networks aim to provide a software framework that enables network applications to customize the processing of their communication packets. Security is of critical importance to the success of active networking. This paper presents a design and a description of the implementation for securing the node of an active network using active networking principles. The secure node architecture includes an active node operating system security API, an active security guardian, and quality of protection (QoP) provisions. The architecture supports highly customized and situational policies created by users and applications dynamically. It permits active nodes to satisfy the application-specific dynamic security and protection requirements. The secure node architecture can provide a fundamental base for securing the active network infrastructure. We describe the integration of secure node architecture into an active network software system to demonstrate its flexible and innovative features.
34025553
Security as services in active networks
This paper discusses the design and implementation for supporting customized security services in active networks using active networking principles. The customized security services support is based on a secure node architecture that includes an active node operating system security API, an active security guardian, and quality of protection provisions. The support of highly customized security services permits active nodes to satisfy the application-specific dynamic security and protection requirements. It associates quality of protection with network software and application security. Applications can dynamically select the suitable security configurations and services at each active routing node, based on their security and performance requirements. The secure node architecture, together with the support of dynamically customized security services, can provide a fundamental base for securing the active network infrastructure and active applications.
27151074
Integrated Support for Location Aware Security Services in Enterprise Wireless Networks
In wireless computing environments limiting network access to authorized users is paramount for the overall security of network. In addition to basic authentication framework, network access is also governed by the context in which it is being used. In this work, we address security issues based on one such context: location. Location sensitivity is increasingly becoming an integral aspect of wireless and pervasive applications. As user moves around in an ubiquitous environment, access rights and other security services provided to her need to be evaluated accordingly. For such purposes we need a security mechanism that controls the authentication and other security services based on location, in addition to basic identity information. In this paper, we present an architecture of location aware security services for enterprise wireless networks. Our implementation is integrated into the RADIUS system, an Authentication, Authorization and Accounting (AAA) framework. Performace evaluation shows that our implementation is efficient for location based security services.
2853015
On the capacity of hybrid wireless networks
This paper involves the study of the throughput capacity of hybrid wireless networks. A hybrid network is formed by placing a sparse network of base stations in an ad hoc network. These base stations are assumed to be connected by a high-bandwidth wired network and act as relays for wireless nodes. They are not data sources nor data receivers. Hybrid networks present a tradeoff between traditional cellular networks and pure ad hoc networks in that data may be forwarded in a multihop fashion or through the infrastructure. It has been shown that the capacity of a random ad hoc network does not scale well with the number of nodes in the system. In this work, we consider two different routing strategies and study the scaling behavior of the throughput capacity of a hybrid network. Analytical expressions of the throughput capacity are obtained. For a hybrid network of n nodes and m base stations, the results show that if m grows asymptotically slower than √n, the benefit of adding base stations on capacity is insignificant. However, if m grows faster than √n, the throughput capacity increases linearly with the number of base stations, providing an effective improvement over a pure ad hoc network. Therefore, in order to achieve nonnegligible capacity gain, the investment in the wired infrastructure should be high enough.
3730862
Distributed Resource Allocation in Stream Processing Systems
Distributed stream processing architecture has emerged as appealing solution to coping with the analysis of large amount of data from dispersed sources. A fundamental problem in such stream processing systems is how to best utilize the available resources so that the overall system performance is optimized. We consider a distributed stream processing system that consists of a network of cooperating servers, collectively providing processing services for multiple data streams. Each stream is required to complete a series of operations on various servers. We assume all servers have finite computing resources and all communication links have finite available bandwidth. The problem is to find distributed schemes to allocate the limited computing resources as well as the communication bandwidth in the system so as to achieve a maximum concurrent throughput for all output streams. We present a generalized multicommodity flow model for the above problem. We develop a distributed resource allocation algorithm that guarantees the optimality. We also provide detailed analysis on the complexity of the algorithm and demonstrate the performance using numerical experiments.
16274304
Face detection and tracking in video using dynamic programming
Face detection and tracking are important in video content analysis since the most important objects in most video are human beings. This paper proposes a new approach for combined face detection and tracking in video. The face detection algorithm is a fast template matching procedure using iterative dynamic programming (DP). Although the face detection algorithm is designed for frontal face, the same mechanism can also be applied to track non-frontal faces with online adapted face models. Due to the essence of template matching, the algorithm is capable of comparing the similarity among different faces, which makes it suitable for tracking the same face that occur at disjointed temporal locations in video. While the proposed face detection method provides comparable accuracy as the neural network based approach, it is much faster.
5176095
Pattern-based texture metamorphosis
In this paper we study texture metamorphosis, or how to generate texture samples that smoothly transform from a source texture image to a target. We propose a pattern-based approach to specify the feature correspondence between two textures, based on the observation that man), texture images have stochastically distributed patterns which are similar to each other First, the user selects a pattern in the source and target textures, and establishes the "local feature correspondence" between these two patterns by specifying landmarks. Then, repeated patterns are automatically detected and localized in the source and target textures. The "pattern correspondence" between two textures is formulated as an integer programming problem and solved using the Hungarian algorithm. Finally, we obtain a warp function between two textures by combining "local feature correspondence" and "pattern correspondence". Experiments demonstrate that our technique produces visually appealing morphing sequences, with moderate amount of user interaction.
17193716
Detecting news reporting using audio/visual information
This paper proposes an integrated approach to discriminate news reporting from everything else in broadcast news data based on both audio and visual information. The separation of news reporting segments from others not only can provide useful indices for video streams but also serves as a pre-processing step for tasks such as speaker identification and speech recognition so that only speech segments are passed on for further processing. A set of audio and visual features are adopted that aim at capturing the intrinsic properties of the underlying classes. Four types of classifiers (threshold fuzzy, Gaussian Mixture Model based, and Support Vector Machine) are tested. Some of the experimental results are presented and discussed in the paper.