"Malware" is an umbrella term that describes a variety of Internet-borne threats, including viruses, spyware,Trojan horses, spam, bots and more. This sophisticated and evolving security threat puts all busin...
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"Malware" is an umbrella term that describes a variety of Internet-borne threats, including viruses, spyware,Trojan horses, spam, bots and more. This sophisticated and evolving security threat puts all businesses at risk, no matter how big or small. Malware creates unique challenges to higher learning institutions (HLI) in protecting their information assets. This is largely due to the fact that HLI information technology (IT) departments must balance between enabling a highly collaborative, non-restrictive environment and ensuring the confidentiality, integrity, and availability of data and computing resources. HLIs can proactively defend the network to reduce the risks associated with this threat by assessing the vulnerabilities and threats present in their networks and implementing appropriate multilayer security. A multilayer approach involves applying countermeasures at every layer of the computer network, from the perimeter routers and firewalls to users' personal computers in order to increase network security. The goal of this study is to propose a framework for network security protection against malware to increase the level of protection using non technical countermeasures.
Particle swarm optimization (PSO) has shown its good performance on numerical function problems. However, on some multimodal functions the PSO easily suffers from premature convergence because of the rapid decline in ...
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Particle swarm optimization (PSO) has shown its good performance on numerical function problems. However, on some multimodal functions the PSO easily suffers from premature convergence because of the rapid decline in velocity. In this paper, a hybrid PSO algorithm, called HPSO, is proposed, which employs a modified velocity model to guarantee a non-zero velocity. In addition, a Cauchy mutation operator conducted on the global best particle is used for improving the global search ability of PSO. Experimental studies on a suite of multimodal functions with many local minima show that the HPSO outperforms the standard PSO, CEP, Gaussian swarm with Gaussian mutation (GPSO+GJ) and Gaussian swarm with Cauchy mutation (GPSO+CJ) on most test functions.
Output-input feedback (OIF) Elman neural network is a dynamic feedback network. An improved model is proposed based on the OIF Elman neural network by introducing direction profit factor in this paper. Moreover, the p...
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Output-input feedback (OIF) Elman neural network is a dynamic feedback network. An improved model is proposed based on the OIF Elman neural network by introducing direction profit factor in this paper. Moreover, the proposed model is applied to forecast the composite index of stock. In addition, some comparisons are also made when the stock exchange is performed using prediction results from OIF Elman neural network. Simulation results show that the proposed model is feasible and effective in the finance field. It shows that the proposed model can not only improve the forecasting precision evidently and possess the characteristic of quick convergence but also provide a good reference tool for investors to obtain more profits.
This paper is devoted to the problem of H filtering for a class of neutral stochastic systems with both discrete and distributed time-varying *** objective is to design a full order filter such that the resulting filt...
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This paper is devoted to the problem of H filtering for a class of neutral stochastic systems with both discrete and distributed time-varying *** objective is to design a full order filter such that the resulting filtering error system is stochastically asymptotically stable with a prescribed H∞performance *** on the stability theory of stochastic systems,a delay-dependent and rate-dependent sufficient condition for the existence of filter is obtained in terms of linear matrix inequalities(LMIs).The corresponding filter design method is also proposed,while the explicit expression for the desired filter is given.A numerical example is finally included to illustrate the effectiveness of the proposed method.
Streaming XML data is often encountered in applications in Medical Biology. So, how to effectively manage and query XML data streams can be a fundamental issue for the quality of those Medical Biology applications. Wi...
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Streaming XML data is often encountered in applications in Medical Biology. So, how to effectively manage and query XML data streams can be a fundamental issue for the quality of those Medical Biology applications. With respect to current methods for XPath query evaluation over XML data streams, adoption of some query rewriting techniques are common when encountering some complex query which can cause ambiguities and redundant query cost. Lots of work can be found in database research community to simplify query and remove its redundancy. However, less attention is paid to make use of query rewriting to benefit the query evaluation process of an efficient XML data stream query system. In other words, the query rewriting is not directly for the purpose of simplicity or redundancy removal;whereas it is for the convenience of an efficient query. In this paper, we propose a normalization process which rewrites the Forward XPath expressions for our XML data stream query system. The proposed normalization is expected to normalize all the complex predicates connected with logic operators into twig structures. With this normalization, queries can be transformed into a well-structured one, the formal way of the normalization makes the query language of our XML data stream query system more precise and the twig structure facilitates the query evaluation of our query system.
An increasing number of institutions require softwareengineering as part of their computing curriculum. Technical managers and hiring personnel of many software development companies cite familiarity with software en...
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An increasing number of institutions require softwareengineering as part of their computing curriculum. Technical managers and hiring personnel of many software development companies cite familiarity with softwareengineering principles among the top skills required for entry-level computing positions. Furthermore, technical managers and hiring personnel often consider experience with real-world group projects to be a necessary part of the computing background of prospective new hires. These conclusions are based on systematic discussions with technical and humanresources personnel at 13 large Midwestern companies (50+ developers) over the past seven years (J. Beck, unpublished data, 2001-2008). Unfortunately, many computing students never benefit from the experience of a real project during their undergraduate studies. The experiences of many students are limited to toy textbook problems assigned to small groups, which means they miss out on a vitally important part of their computing education. Three areas of particular concern for providing students with class projects that incorporate real-world hurdles within the classroom are: the difficulty of managing academic team projects;the risk of unfairness in workload distribution across teams and in grading and evaluation;and a lack of experience for many instructors in how to manage team projects, as well as their fear of failing should they try. This panel will examine some challenges associated with managing semester-long or multi-semester whole-class projects with real clients and will present successful tools and techniques for managing such projects. We strongly believe that all computing students should experience significant and well-managed team projects as part of their programs of study. Together, the members of this panel have over 45 years of experience managing academic real-world team projects for real clients. We believe that tools and techniques such as the ones we will discuss can help instructors
As a fundamental requirement for providing security functionality in sensor networks, key management plays a core supporting role in authentication and encryption. In this paper, we propose the Adaptive Key Selection ...
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As a fundamental requirement for providing security functionality in sensor networks, key management plays a core supporting role in authentication and encryption. In this paper, we propose the Adaptive Key Selection (AKS) scheme and the Adaptive Key Selection algorithm for secure multiple deployment in sensor networks that target at providing high connectivity between different deployment sets of sensor nodes. Our simulation shows that the AKS scheme can greatly improve the connectivity of sensor nodes while maintaining the security of the multiple deployment sets at the same time.
Routing is a fundamental problem in wireless sensor networks. Most previous routing protocols are challenged when used in large dynamic networks as they suffer from either poor scalability or the void problem. In this...
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Routing is a fundamental problem in wireless sensor networks. Most previous routing protocols are challenged when used in large dynamic networks as they suffer from either poor scalability or the void problem. In this paper, we propose a new geographic routing protocol, SBFR (Scoped Bellman-Ford Routing), for large dynamic wireless sensor networks. The basic idea is that each node keeps a view scope of the network by computing distance vectors using the distributed Bellman- Ford method, and maintains a cost for routing to the sink. When forwarding a packet, a node picks the node with minimum cost in its routing table as a temporary landmark. While achieving good sealability, it also solves the void problem in an efficient manner through the combination of Bellman-Ford routing and cost-based geographic routing. Analytical and simulation results show that SBFR outperforms other routing protocols not only because of its robustness and scalability but also its practicality and simplicity.
The emergence of Grid Computing settings lays a solid foundation for designing and constructing a next generation E-commerce environment. This work presents a new E-commerce architecture based on a Grid Computing envi...
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The emergence of Grid Computing settings lays a solid foundation for designing and constructing a next generation E-commerce environment. This work presents a new E-commerce architecture based on a Grid Computing environment, and models and analyzes the architecture using Temporal Petri nets (TPNs). It can make sufficiently use of the Grid resources to implement various electronic bargains between the geographically dispersed users. By means of its TPN model, some main temporal properties are represented and verified formally.
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