With the widespread use of Internet and the development of information technology, there are a tremendous amount of news information resource. The ability to quickly obtain useful resource from the huge news informati...
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With the widespread use of Internet and the development of information technology, there are a tremendous amount of news information resource. The ability to quickly obtain useful resource from the huge news information is a crucial problem at present. Based on the analysis of news information, this paper introduces an approach of semi-automatically extracting news information from Web resource. Moreover, it gives the system which extracts useful Olympic news information and its experiment results.
An increasingly important requirement for software systems is the capability to evolve dynamically according to the changes of computing environment and users' need during runtime. In this paper, a dynamic softwar...
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An increasingly important requirement for software systems is the capability to evolve dynamically according to the changes of computing environment and users' need during runtime. In this paper, a dynamic software architecture oriented approach is proposed to support online evolution. Notably, architecture information is reified as explicit and manipulable entities to organize a runtime architecture meta-model, which is causally connected to software implementation and specification. By using reflection, the evolved architecture meta-model modifies running system, and updates specification simultaneously. The well-defined architecture meta-model supervises all evolutionary behaviors to ensure system consistency, integrity, and evolution traceability. Based on this model, a visualized integrated development platform entitled Artemis-ARC is also successfully implemented. It supports component and service design, development and assembly, especially dynamic evolution. Furthermore, a simple application case is developed with Artemis-ARC to illustrate the effect of online evolution.
Trusted channel provides various security services for information products in the environment of insecure networks. It has become a focused problem that whether the services of trusted channel provided by security pr...
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Trusted channel provides various security services for information products in the environment of insecure networks. It has become a focused problem that whether the services of trusted channel provided by security products wholly satisfy the security function requirement. Now most evaluation methods are very uncertain and incomplete because they are almost empirical and without theoretical support. This paper proposes an evaluation framework based on the Common Criteria with generalization and reusability in some sense. The formal verification methods are applied in the framework, combined with empirical analysis. As an example, SSH protocol is verified by Cord calculus with type system, cryptographic function, and extended inference rules.
Differing from existed anomaly detection methods which only dealt with the frequencies of system calls or local variation, the paper puts forward a model named DBCPIDS. It took in both dynamic behavior and character p...
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Differing from existed anomaly detection methods which only dealt with the frequencies of system calls or local variation, the paper puts forward a model named DBCPIDS. It took in both dynamic behavior and character patterns of programs. In this model, the authors defined the short sequence of system calls as a character pattern if this sequence satisfied the certain support degree, and propose an improved HMM (IHMM) on this basis. When detecting intrusions, firstly, we would judge whether the program trace is matched character patterns. If not, then the authors would use IHMM to detect. The model can not only reflect the global character of the program normal traces, but also pay much attention to the local warp in the execution. The experiments results show that the authors can get higher detection rate and lower false positive rate with DBCPIDS.
As a matter of fact, most attacks are not single attack action. They are multi-step attacks which are composed by a set of attack actions. How to detect multi-step attack is an important aspect of IDS research. The tr...
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As a matter of fact, most attacks are not single attack action. They are multi-step attacks which are composed by a set of attack actions. How to detect multi-step attack is an important aspect of IDS research. The traditional methods of modeling attack scenario is mainly based on special attack actions. It needs to build a large number of attack models, so that the process is very complex and the models are difficult to maintain. What's more, the detection efficiency is low. In this paper, the authors analyze the insufficiency of the traditional method. Through the study on patterns of the multi-step attack, a detecting and forecasting algorithm based on intrusion intention for multi-step attack is designed. This algorithm give an improvement and expansion of traditional attack modeling method that using Petri Nets. The authors use CTPN to model multi-step attack, and correlate alert records based on it. The method can not only detect multi-step attack, but also forecast the attack which will happen. The algorithm in this paper is more simple and utility than those old methods. In the same time, the experimental results prove the validity of our algorithm.
Wireless sensor networks often face the critical problem of maintaining the sufficient sensing coverage (QoS) at an application specific level while keeping a small number of nodes active at any time to save energy. T...
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Wireless sensor networks often face the critical problem of maintaining the sufficient sensing coverage (QoS) at an application specific level while keeping a small number of nodes active at any time to save energy. To solve this problem, the relationship between the desired QoS requirement and the minimum number of active nodes is analyzed without the knowledge of location or directional information in the randomly deployed sensor networks. Based on the analytical results, an energy efficient and location-independent QoS (ELIQoS) protocol is proposed, which selects the minimum number of active nodes based on the nodes' energy without using any location information. Simulation and analysis study demonstrates that the ELIQoS protocol can not only reduce the network consumption and balance the energy dissipation among nodes, but can provide the desired QoS requirement effectively.
One of the major challenges in constructing WSNs is to maintain long network lifetime as well as sufficient sensing area. In this paper, the broad problems of coverage in WSNs are discussed, and coverage protocols dep...
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One of the major challenges in constructing WSNs is to maintain long network lifetime as well as sufficient sensing area. In this paper, the broad problems of coverage in WSNs are discussed, and coverage protocols dependent on infrastructures (e.g., GPS, directional antennas, etc) or some localization schemes in the existing solutions are identified. To eliminate the reliance on infrastructure, a distributed energy-efficient location-independent coverage protocol (DELIC) is proposed, which aims to preserve coverage based on the local neighborhood information. Comparing its residual energy with its neighborhood, one node can independently make its decision to compete for becoming a working node. The simulation and analysis study demonstrate that the DELIC not only provides the high quality of area coverage and good scalability, but also provides better performance in the energy efficiency. The DELIC outperforms the PEAS, the GAF-like, the sponsor area and OGDC algorithm with respect to the quality of area coverage, total energy-consumption and energy-consumption balance.
Correlation algorithms based on pixel gray value are very popular and widely used in image template matching. However, these algorithms have high time complexity and are sensitive to the variation of image luminance a...
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Correlation algorithms based on pixel gray value are very popular and widely used in image template matching. However, these algorithms have high time complexity and are sensitive to the variation of image luminance and scale. To avoid that, a new algorithm based on coding image grey value is proposed. This algorithm divides the image into certain size blocks called R-block, sums the gray value of each R-block pixel, and codes the R-block according to the sorting result among the neighborhood of R-blocks. Image and template are matched by comparing their R-block coding. The R-block is very rapidly and easily coded and only equality comparison is needed. The new algorithm is robust to the linear transformation of pixel grey value and image noise. Its time complexity is reduced to O(M2log(N)), or namely is improved two order of magnitude in contrast to the current correlation algorithms'.
Enlightened by the behaviors of gregarious ant colonies, an artificial ant movement (AM) model and an adaptive ant clustering (AAC) algorithm for this model are presented. In the algorithm, each ant is treated as an a...
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Enlightened by the behaviors of gregarious ant colonies, an artificial ant movement (AM) model and an adaptive ant clustering (AAC) algorithm for this model are presented. In the algorithm, each ant is treated as an agent to represent a data object. In the AM model, each ant has two states: sleeping state and active state. In the algorithm AAC, the ant's state is controlled by both a function of the ant's fitness to the environment it locates and a probability function for the ants becoming active. By moving dynamically, the ants form different subgroups adaptively, and consequently the whole ant group dynamically self-organizes into distinctive and independent subgroups within which highly similar ants are closely connected. The result of data objects clustering is therefore achieved. This paper also present a method to adaptively update the parameters and the ants' local movement strategies which greatly improve the speed and the quality of clustering. Experimental results show that the AAC algorithm on the AM model is much superior to other ant clustering methods such as BM and LF in terms of computational cost, speed and quality. It is adaptive, robust and efficient, and achieves high autonomy, simplicity and efficiency. It is suitable for solving high dimensional and complicated clustering problems.
Large-scale software development typically requires participation of multiple people. One motivation of the participants to collaborate with others is to maximize the profit they may gain from the software development...
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Large-scale software development typically requires participation of multiple people. One motivation of the participants to collaborate with others is to maximize the profit they may gain from the software development. Therefore, the collaborative relations between the participants should be established through negotiation in order to ensure that all the participants can gain profit. Traditional software process modeling approaches model software collaboration as a set of rules or transactions. When entry criteria are satisfied or operations are explicitly invoked, the collaborations will take place necessarily and are performed in a predefined manner. Negotiation issues are mostly overlooked by these approaches. A negotiation-based approach for software process collaboration is proposed, In this approach, software process is modeled as a group of independent, autonomous, rational, and collaborative process agents. The collaborative relations between the process agents are established through negotiation. Using this approach, software organizations can carry out software development more efficiently and effectively.
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