Advances in Network Management

Ding, Jianguo

doi:10.1201/9781420064551

Cited by 29 publications

(36 citation statements)

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“…Swarm intelligence (SI) is a type of artificial intelligence based on the decentralized collective behavior, self-organized systems [23]. Number of simple agents is interacting locally with each other and within specific dimensional environment in a way that no centralized control structure must be obeyed by the involved agents in their behavior.…”

Section: Mobile Agent With Artificial Intelligence Theorymentioning

confidence: 99%

An overview of different techniques and algorithms for network topology discovery

Alhanani

Abouchabaka

2014

2014 Second World Conference on Complex Systems (WCCS)

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Network topology discovery describes the physical structure of the network, which in turn reflects the purpose of this network design. Used tools and techniques vary depending on that structure in order to choose the optimal methods for implementing the appropriate distributed applications. Mobile agents have become a focus of attention for implementing distributed management architectures because of their autonomy, flexibility and ability of asynchronous communication, while centralized models affect on the network performance such as latency, throughput and jitter. The main objective of this study is to discuss the use of mobile agent for discover the network topology either by traditional methods, protocols or by graphic theory, Genetic and Swarm algorithms that belong to the artificial intelligence filed and compare between them. As a result, identify the appropriate technique for extracting the network management information to obtain optimal itineraries for mobile agents.

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Section: Mobile Agent With Artificial Intelligence Theorymentioning

confidence: 99%

An overview of different techniques and algorithms for network topology discovery

Alhanani

Abouchabaka

2014

2014 Second World Conference on Complex Systems (WCCS)

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“…The SPPI (Structure of Policy Provisioning Information) [1,9]; and The CIM (Common Informational Model) [8,9].…”

Section: A Informational Modelmentioning

confidence: 99%

“…Other improved versions as SMIv2 (RFC 1442) and SMIng (RFC 3781) have been proposed in 1993 and 2004 respectively [8]. The SPPI model has been proposed in the early 1990s for policy based management [5].…”

Section: A Informational Modelmentioning

confidence: 99%

“…The SPPI model presents many disadvantages in terms of resolution of the management problems summarized in [6]. The managed information defined in the current CIM model are limited in accordance with the new requirements of management needs listed in [8].…”

Section: A Informational Modelmentioning

confidence: 99%

“…Table I of the appendix provides detailed explanations of the problems of these three informational models in terms of the new management challenges according to [6,8,10].…”

Section: A Informational Modelmentioning

confidence: 99%

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A survey of the distributed network management models and architectures: Assessment and challenges

Moindze

Konaté

2014

2014 IEEE 6th International Conference on Adaptive Science &Amp; Technology (ICAST)

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In this work, we'll strive to present a survey about the important traditional and modern telecommunication management network (TMN) on one hand; and information and communication technology (ICT) management on the other hand. In this review, we classify all the major networks and technology management systems known to date in order to provide guidelines for network management architectures design. This paper shows an assessment of the current technology management in terms of models, architectures and methods. This assessment allowed us to trace out their strengths and weaknesses according to the managing of the next generation networks. We are going to build a taxonomy based on three-criteria for all these technologies, especially the new ones. The main guidelines for the proposal of innovative architectures to be able to control the emerging networks of the 21 st century requirements are addressed.

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Intrusion detection system based on GA‐fuzzy classifier for detecting malicious attacks

Kumar

Saravanan

Thenmozhi

et al. 2019

Concurrency and Computation

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Summary Usage of computer resources, being a very important part in day to day life, it is to be noticed that the security threats have also increased. Hence, Intrusion Detection System (IDS) is used for detection and prevention of computer resources from security threats generated by malicious attackers. Existing techniques like encryption mechanism, authentication mechanism, and access control do not support for analyzing large volume of data and it is efficient only in the case of limited number of attacks. Attackers attack the computer resources based on the weakness of the security level in the Information system and they can violate the rules and regulation of computer system (Confidentiality, Integrity, and Availability) easily. Handling threats on computer resources still remains a challenging issue. Distributed Denial of Service attacks (DDoS) is an important attack that sends more than one number of requests to the destination server from multiple compromised systems that makes the Information system unable to process the request thereby resulting in non‐response to the attacker as well as normal end user, which results in large number of false alarms and less detection accuracy rates. We propose a new model called hybrid‐based intrusion detection system (GA‐Fuzzy) for handling large volume NSL‐KDD Dataset for detecting attacks effectively and for reducing misclassification alarm rate. Here, Genetic algorithm (GA) is used for creating new pattern (new features, records) for training the Fuzzy classifier effectively. We use Principle Component Analysis (PCA) as a feature selection method that eliminates irrelevant and redundant data from the NSL‐KDD dataset that improves the efficiency and to attain 99.96% detection accuracy and 0.04% false alarm rate.

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Advances in Network Management

Cited by 29 publications

References 0 publications

An overview of different techniques and algorithms for network topology discovery

An overview of different techniques and algorithms for network topology discovery

A survey of the distributed network management models and architectures: Assessment and challenges

Intrusion detection system based on GA‐fuzzy classifier for detecting malicious attacks

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