116 research outputs found

    Ideal bases in constructions defined by directed graphs

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    The present article continues the investigation of visible ideal bases in constructions defined using directed graphs. Our main theorem establishes that, for every balanced digraph D and each idempotent semiring R with 1, the incidence semiring ID(R) of the digraph D has a convenient visible ideal basis BD(R). It also shows that the elements of BD(R) can always be used to generate two-sided ideals with the largest possible weight among the weights of all two-sided ideals in the incidence semiring

    Automatic generation of meta classifiers with large levels for distributed computing and networking

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    This paper is devoted to a case study of a new construction of classifiers. These classifiers are called automatically generated multi-level meta classifiers, AGMLMC. The construction combines diverse meta classifiers in a new way to create a unified system. This original construction can be generated automatically producing classifiers with large levels. Different meta classifiers are incorporated as low-level integral parts of another meta classifier at the top level. It is intended for the distributed computing and networking. The AGMLMC classifiers are unified classifiers with many parts that can operate in parallel. This make it easy to adopt them in distributed applications. This paper introduces new construction of classifiers and undertakes an experimental study of their performance. We look at a case study of their effectiveness in the special case of the detection and filtering of phishing emails. This is a possible important application area for such large and distributed classification systems. Our experiments investigate the effectiveness of combining diverse meta classifiers into one AGMLMC classifier in the case study of detection and filtering of phishing emails. The results show that new classifiers with large levels achieved better performance compared to the base classifiers and simple meta classifiers classifiers. This demonstrates that the new technique can be applied to increase the performance if diverse meta classifiers are included in the system

    Prevention of information harvesting in a cloud services environment

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    We consider a cloud data storage involving three entities, the cloud customer, the cloud business centre which provides services, and the cloud data storage centre. Data stored in the data storage centre comes from a variety of customers and some of these customers may compete with each other in the market place or may own data which comprises confidential information about their own clients. Cloud staff have access to data in the data storage centre which could be used to steal identities or to compromise cloud customers. In this paper, we provide an efficient method of data storage which prevents staff from accessing data which can be abused as described above. We also suggest a method of securing access to data which requires more than one staff member to access it at any given time. This ensures that, in case of a dispute, a staff member always has a witness to the fact that she accessed data

    Investigation of stakeholders commitment to information security awaremess programs

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    Organisations have become increasingly dependent on technology in order to compete in their respective markets. As IT technology advances at a rapid pace, so does its complexity, giving rise to new IT security vulnerabilities and methods of attack. Even though the human factors have been recognized to have a crucial role in information security management, the effects of weakness of will and lack of commitment on the stakeholders (i.e., employers and employees) parts has never been factored into the design and delivery of awareness programs. To this end, this paper investigates the impacts of the availability of awareness programs and end-user drive and lack of commitment to information security awareness program design, delivery and success.<br /

    Guest editorial : In Journal of networks, v.7 n.3

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    Networking of computing devices has been going through rapid evolution and thus continuing to be an ever expanding area of importance in recent years. New technologies, protocols, services and usage patterns have contributed to the major research interests in this area of computer science. The current special issue is an effort to bring forward some of these interesting developments that are being pursued by researchers at present in different parts of the globe. Our objective is to provide the readership with some insight into the latest innovations in computer networking through this. This Special Issue presents selected papers from the thirteenth conference of the series (ICCIT 2010) held during December 23-25, 2010 at the Ahsanullah University of Science and Technology. The first ICCIT was held in Dhaka, Bangladesh, in 1998. Since then the conference has grown to be one of the largest computer and IT related research conferences in the South Asian region, with participation of academics and researchers from many countries around the world. Starting in 2008 the proceedings of ICCIT are included in IEEExplore. In 2010, a total of 410 full papers were submitted to the conference of which 136 were accepted after reviews conducted by an international program committee comprising 81 members from 16 countries. This was tantamount to an acceptance rate of 33%. From these 136 papers, 14 highly ranked manuscripts were invited for this Special Issue. The authors were advised to enhance their papers significantly and submit them to undergo review for suitability of inclusion into this publication. Of those, eight papers survived the review process and have been selected for inclusion in this Special Issue. The authors of these papers represent academic and/or research institutions from Australia, Bangladesh, Japan, Korea and USA. These papers address issues concerning different domains of networks namely, optical fiber communication, wireless and interconnection networks, issues related to networking hardware and software and network mobility. The paper titled &ldquo;Virtualization in Wireless Sensor Network: Challenges and Opportunities&rdquo; argues in favor of bringing in different heterogeneous sensors under a common virtual framework so that the issues like flexibility, diversity, management and security can be handled practically. The authors Md. Motaharul Islam and Eui-Num Huh propose an architecture for sensor virtualization. They also present the current status and the challenges and opportunities for further research on the topic. The manuscript &ldquo;Effect of Polarization Mode Dispersion on the BER Performance of Optical CDMA&rdquo; deals with impact of polarization mode dispersion on the bit error rate performance of direct sequence optical code division multiple access. The authors, Md. Jahedul Islam and Md. Rafiqul Islam present an analytical approach toward determining the impact of different performance parameters. The authors show that the bit error rate performance improves significantly by the third order polarization mode dispersion than its first or second order counterparts. The authors Md. Shohrab Hossain, Mohammed Atiquzzaman and William Ivancic of the paper &ldquo;Cost and Efficiency Analysis of NEMO Protocol Entities&rdquo; present an analytical model for estimating the cost incurred by major mobility entities of a NEMO. The authors define a new metric for cost calculation in the process. Both the newly developed metric and the analytical model are likely to be useful to network engineers in estimating the resource requirement at the key entities while designing such a network. The article titled &ldquo;A Highly Flexible LDPC Decoder using Hierarchical Quasi-Cyclic Matrix with Layered Permutation&rdquo; deals with Low Density Parity Check decoders. The authors, Vikram Arkalgud Chandrasetty and Syed Mahfuzul Aziz propose a novel multi-level structured hierarchical matrix approach for generating codes of different lengths flexibly depending upon the requirement of the application. The manuscript &ldquo;Analysis of Performance Limitations in Fiber Bragg Grating Based Optical Add-Drop Multiplexer due to Crosstalk&rdquo; has been contributed by M. Mahiuddin and M. S. Islam. The paper proposes a new method of handling crosstalk with a fiber Bragg grating based optical add drop multiplexer (OADM). The authors show with an analytical model that different parameters improve using their proposed OADM. The paper &ldquo;High Performance Hierarchical Torus Network Under Adverse Traffic Patterns&rdquo; addresses issues related to hierarchical torus network (HTN) under adverse traffic patterns. The authors, M.M. Hafizur Rahman, Yukinori Sato, and Yasushi Inoguchi observe that dynamic communication performance of an HTN under adverse traffic conditions has not yet been addressed. The authors evaluate the performance of HTN for comparison with some other relevant networks. It is interesting to see that HTN outperforms these counterparts in terms of throughput and data transfer under adverse traffic. The manuscript titled &ldquo;Dynamic Communication Performance Enhancement in Hierarchical Torus Network by Selection Algorithm&rdquo; has been contributed by M.M. Hafizur Rahman, Yukinori Sato, and Yasushi Inoguchi. The authors introduce three simple adapting routing algorithms for efficient use of physical links and virtual channels in hierarchical torus network. The authors show that their approaches yield better performance for such networks. The final title &ldquo;An Optimization Technique for Improved VoIP Performance over Wireless LAN&rdquo; has been contributed by five authors, namely, Tamal Chakraborty, Atri Mukhopadhyay, Suman Bhunia, Iti Saha Misra and Salil K. Sanyal. The authors propose an optimization technique for configuring the parameters of the access points. In addition, they come up with an optimization mechanism in order to tune the threshold of active queue management system appropriately. Put together, the mechanisms improve the VoIP performance significantly under congestion. Finally, the Guest Editors would like to express their sincere gratitude to the 15 reviewers besides the guest editors themselves (Khalid M. Awan, Mukaddim Pathan, Ben Townsend, Morshed Chowdhury, Iftekhar Ahmad, Gour Karmakar, Shivali Goel, Hairulnizam Mahdin, Abdullah A Yusuf, Kashif Sattar, A.K.M. Azad, F. Rahman, Bahman Javadi, Abdelrahman Desoky, Lenin Mehedy) from several countries (Australia, Bangladesh, Japan, Pakistan, UK and USA) who have given immensely to this process. They have responded to the Guest Editors in the shortest possible time and dedicated their valuable time to ensure that the Special Issue contains high-quality papers with significant novelty and contributions

    Ideal Basis in Constructions Defined by Directed Graphs

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    The present article continues the investigation of visible ideal bases in constructions defined using directed graphs. This notion is motivated by its applications for the design of classication systems. Our main theorem establishes that, for every balanced digraph and each idempotent semiring with identity element, the incidence semiring of the digraph has a convenient visible ideal basis. It also shows that the elements of the basis can always be used to generate ideals with the largest possible weight among the weights of all ideals in the incidence semiring

    Enhancing Trust Management in Cloud Environment

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    AbstractTrust management has been identified as vital component for establishing and maintaining successful relational exchanges between e-commerce trading partners in cloud environment. In this highly competitive and distributed service environment, the assurances are insufficient for the consumers to identify the dependable and trustworthy Cloud providers. Due to these limitations, potential consumers are not sure whether they can trust the Cloud providers in offering dependable services. In this paper, we propose a multi-faceted trust management system architecture for cloud computing marketplaces, to support customers in identifying trustworthy cloud providers. This paper presents the important threats to a trust system and proposed a method for tackling these threats. It described the desired feature of a trust management system. It security components to determine the trustworthiness of e- commerce participants to helps online customers to decide whether or not to proceed with a transaction. Based on this framework, we proposed an approach for filtering out malicious feedbacks and a trust metric to evaluate the trustworthiness of service provider. Results of various simulation experiments show that the proposed multi-attribute trust management system can be highly effective in identifying risky transaction in electronic market places

    Decision trees and multi-level ensemble classifiers for neurological diagnostics

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    Cardiac autonomic neuropathy (CAN) is a well known complication of diabetes leading to impaired regulation of blood pressure and heart rate, and increases the risk of cardiac associated mortality of diabetes patients. The neurological diagnostics of CAN progression is an important problem that is being actively investigated. This paper uses data collected as part of a large and unique Diabetes Screening Complications Research Initiative (DiScRi) in Australia with data from numerous tests related to diabetes to classify CAN progression. The present paper is devoted to recent experimental investigations of the effectiveness of applications of decision trees, ensemble classifiers and multi-level ensemble classifiers for neurological diagnostics of CAN. We present the results of experiments comparing the effectiveness of ADTree, J48, NBTree, RandomTree, REPTree and SimpleCart decision tree classifiers. Our results show that SimpleCart was the most effective for the DiScRi data set in classifying CAN. We also investigated and compared the effectiveness of AdaBoost, Bagging, MultiBoost, Stacking, Decorate, Dagging, and Grading, based on Ripple Down Rules as examples of ensemble classifiers. Further, we investigated the effectiveness of these ensemble methods as a function of the base classifiers, and determined that Random Forest performed best as a base classifier, and AdaBoost, Bagging and Decorate achieved the best outcomes as meta-classifiers in this setting. Finally, we investigated the meta-classifiers that performed best in their ability to enhance the performance further within the framework of a multi-level classification paradigm. Experimental results show that the multi-level paradigm performed best when Bagging and Decorate were combined in the construction of a multi-level ensemble classifier

    Improving classifications for cardiac autonomic neuropathy using multi-level ensemble classifiers and feature selection based on random forest

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    This paper is devoted to empirical investigation of novel multi-level ensemble meta classifiers for the detection and monitoring of progression of cardiac autonomic neuropathy, CAN, in diabetes patients. Our experiments relied on an extensive database and concentrated on ensembles of ensembles, or multi-level meta classifiers, for the classification of cardiac autonomic neuropathy progression. First, we carried out a thorough investigation comparing the performance of various base classifiers for several known sets of the most essential features in this database and determined that Random Forest significantly and consistently outperforms all other base classifiers in this new application. Second, we used feature selection and ranking implemented in Random Forest. It was able to identify a new set of features, which has turned out better than all other sets considered for this large and well-known database previously. Random Forest remained the very best classier for the new set of features too. Third, we investigated meta classifiers and new multi-level meta classifiers based on Random Forest, which have improved its performance. The results obtained show that novel multi-level meta classifiers achieved further improvement and obtained new outcomes that are significantly better compared with the outcomes published in the literature previously for cardiac autonomic neuropathy

    Using response action with Intelligent Intrusion detection and prevention System against web application malware

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    Findings: After evaluating the new system, a better result was generated in line with detection efficiency and the false alarm rate. This demonstrates the value of direct response action in an intrusion detection system
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