Research on sensor network had been focused on security services that provide authentication, confidentiality, integrity and availability until recently, but now there is growing interest in tackling the problem of ac...
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Research on sensor network had been focused on security services that provide authentication, confidentiality, integrity and availability until recently, but now there is growing interest in tackling the problem of actual sensor IDs being exposed. Many techniques for providing anonymity to the source in an ad-hoc network have been proposed, but they are not suitable. Thus, a technique that is well-suited to the characteristics of sensor networks is needed. This paper, limiting the type of attack against a sensor network to that of eavesdropping, proposes a new technique for providing anonymity using Phantom ID and SMAC. The degree of anonymity provided by the proposed technique was analyzed using an entropy-based modeling technique. The results showed that the anonymity is high when the proposed technique is used. The key factor responsible for the improved anonymity had to do with disguising the sensor ID so that it cant be found easily.
Employing multi-level abstraction in modeling refers to representing objects at multiple levels of one or more abstraction hierarchies, mainly classification, aggregation and generalization. Multiple representation, h...
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作者：
Wei DuZhongbo CaoYan WangEnrico BlanzieriChen ZhangYanchun LiangCollege of Mathematics
Jilin University Changchun 130012 China Department of Information and Communication Technology University of Trento Povo 38050 Italy College of Computer Science and Technology
Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China
Based on analysis of relationships between solution qualities and number of initial dynamic points in elastic net algorithm, we propose an improved elastic network algorithm (IENA) introduced in a heuristic cloning st...
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Two-dimensional polyacrylamide gel electrophoresis of proteins is a robust and reproducible technique. It is the most widely used separation tool in proteomics. Current efforts in the field are directed at development...
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Two-dimensional polyacrylamide gel electrophoresis of proteins is a robust and reproducible technique. It is the most widely used separation tool in proteomics. Current efforts in the field are directed at development of tools for expanding the range of proteins accessible with two-dimensional gels. Proteomics was built around the two-dimensional gel. The idea that multiple proteins can be analyzed in parallel grew from two-dimensional gel maps. Proteomics researchers needed to identify interested protein spots by examining the gel. This is time consuming, labor extensive and error prone. It is desired that the computer can analyze the proteins automatically by first detecting then quantifying the protein spots in the 2-D gel images. In our previous work, we presented a new technique for segmentation of 2-D gel images using the fuzzy c-means algorithm using the notion of fuzzy relations. In this paper, we will describe the new relational fuzzy c-means algorithm (RFCM) and use it for automatic protein spots quantification. We will also use two methods to evaluate its performance: the unsupervised evaluation method and comparison with the expert spots quantification.
These days, with the implementation of ubiquitous computing concept, sensor networks that collect analyze and process information of things and environment through sensors have become a huge interest as the technology...
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These days, with the implementation of ubiquitous computing concept, sensor networks that collect analyze and process information of things and environment through sensors have become a huge interest as the technology that would realize this concept. However, sensor network technology has wireless communication infrastructure as its foundation and fundamentally has security weakness with limitations on low computing capacity, power supply and low budget. The core of group telecommunications between sensor network sensor nodes is the group key management. Managing group key requires appreciating group key security and management mechanism efficiency. This paper takes the characteristics of sensor network into consideration and not only increases the group key agreement efficiency through Two-dimension array key set distribution and not the existing group key method to satisfy both the network function and security but also protects information between each nodes thereby enhancing the sense of security.
In this paper, we present a novel multi-resolution approach to efficiently mapping 3D environments. Our representation models the environment as a hierarchy of probabilistic 3D maps, in which each submap is updated an...
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In this paper, we present a novel multi-resolution approach to efficiently mapping 3D environments. Our representation models the environment as a hierarchy of probabilistic 3D maps, in which each submap is updated and transformed individually. In addition to the formal description of the approach, we present an implementation for tabletop manipulation tasks and an information-driven exploration algorithm for autonomously building a hierarchical map from sensor data. We evaluate our approach using real-world as well as simulated data. The results demonstrate that our method is able to efficiently represent 3D environments at high levels of detail. Compared to a monolithic approach, our maps can be generated significantly faster while requiring significantly less memory.
Nowadays, e-mail is one of the most inexpensive and expeditious means of communication. However, a principal problem of any internet user is the increasing number of spam, and therefore an efficient spam filtering met...
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Nowadays, e-mail is one of the most inexpensive and expeditious means of communication. However, a principal problem of any internet user is the increasing number of spam, and therefore an efficient spam filtering method is imperative. Feature selection is one of the most important factors, which can influence the classification accuracy rate. To improve the performance of spam prediction, this paper proposes a new fuzzy adaptive multi-population parallel genetic algorithm (FAMGA) for feature selection. To maintain the diversity of population, a few studies of multi-swarm strategy are reported, whereas the dynamic parameter setting has not been considered further. The proposed method is based on multiple subpopulations and each subpopulation runs in independent memory space. For the purpose of controlling the subpopulations adaptively, we put forward two regulation strategies, namely population adjustment and subpopulation adjustment. In subpopulation adjustment, a controller is designed to adjust the crossover rate for each subpopulation, and in population adjustment, a controller is designed to adjust the size of each subpopulation. Three publicly available benchmark corpora for spam filtering, the PU1, Ling-Spam and Spam Assassin, are used in our experiments. The results of experiments show that the proposed method improves the performance of spam filtering, and is significantly better than other feature selection methods. Thus, it is proved that the multi-population regulation strategy can find the optimal feature subset, and prevent premature convergence of the population.
In order to accommodate different requirements of reliable multicast applications, the real-time reliable multicasting support framework must possess generic yet rich features for detecting and reporting message losse...
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In order to accommodate different requirements of reliable multicast applications, the real-time reliable multicasting support framework must possess generic yet rich features for detecting and reporting message losses with tight latency bounds. One highly promising concrete formulation of a multicast framework is the Real-time Multicast & Memory Replication Channel (RMMC) scheme. In this paper, we present the Delay-Bounded Reliable RMMC (DBR-RMMC) scheme, which extends the RMMC scheme in order to yield tight bounds on the latencies in detecting and reporting message losses over RMMCs and to enable application layer to initiate timely recovery actions. The DBR-RMMC scheme offers an API that allows application developers to freely explore the various design dimensions of reliable multicast applications while assuring timeliness. We also discuss a middleware subsystem devised to support DBRRMMC, followed by a summary of several analytical results on the bounds for latencies in reacting to the occurrence of a message loss. Experiments involving a real-time video streaming application have been conducted and encouraging results are presented.
作者：
[Systems Research Institute
Polish Academy of Sciences Warsaw and University of Gdansk Warsaw Poland Systems Research Institute
Polish Academy of Sciences Warsaw and Management Academy Warsaw Poland Software Engineering Department
Faculty of Automatics Computers and Electronics University of Craiova Bvd.Decebal Craiova Romania University of Duisburg-Essen
Institute for Computer Science and Business Information Systems (ICB) Practical Computer Science Data Management Systems and Knowledge Representation Essen Germany
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