Intrusion detection thesis 2012

Introduction In spite of the many developments in network security over the past decade, the Internet remains a hostile environment for our networked computer systems.

Intrusion detection thesis 2012

A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features

Jumping emerging patterns JEPs for a test instance are minimal patterns that match the test instance but they do not match any normal instances. OCLEP was based on the observation that one needs long JEPs to differentiate an instance of one class from instances of the same class, but needs short JEPs to differentiate an instance of one class from instances of a different class.

Advisor ; Junjie Zhang, Ph. Committee Member ; Bin Wang, Ph.

Cyber Training, and Intrusion Detection and Response - Norfolk State University

Computer Science; Information Systems Keywords: Alqallaf, Maha Software Defined Secure Ad Hoc Wireless Networks Doctor of Philosophy PhDWright State University,Computer Science and Engineering PhD Software defined networking SDNa new networking paradigm that separates the network data plane from the control plane, has been considered as a flexible, layered, modular, and efficient approach to managing and controlling networks ranging from wired, infrastructure-based wireless e.

Wireless networks have become increasingly more heterogeneous. Secure and collab- orative operation of mobile wireless ad-hoc networks poses significant challenges due to the decentralized nature of mobile ad hoc wireless networks, mobility of nodes, and re- source constraints.

Recent developments in software defined networking shed new light on how to control and manage an ad hoc wireless network. Given the wide deployment and availability of heterogeneous wireless technologies, the control and management of ad hoc wireless networks with the new software defined networking paradigm is offered more flexibility and opportunities to deal with trust and security issues and to enable new features and services.

Specifically, I We have proposed four design options for software defined secure collaborative ad hoc wireless network architecture.

The de- sign options are organized into a centralized SDN controller architecture with controller replication and b distributed SDN controller architecture. While these proposed architec- ture options exhibit different characteristics, many common challenges are shared amongst these options.

Challenges include fault-tolerance, scalability, efficiency, and security. The unstructured nature of ad hoc wireless networks exacerbates these challenges.

We have studied the pros and cons of these different design options and their applicability in differ- ent practical scenarios via simulations. II Establishing the initial trust among participating devices in an SDN based wireless mobile ad hoc network will serve as a basis for enabling ensuing secure communication of the network.

Advisor ; Yong Pei, Ph. Committee Member ; Krishnaprasad Thirunarayan, Ph. Committee Member ; Zhiqiang Wu, Ph. Computer Engineering; Computer Science Keywords: Anomaly-based intrusion detection systems detect attacks by analyzing either computer or network data and flagging abnormalities as intrusions.

The abnormalities are detected by analyzing certain parameters that are present in the data. Our approach analyzes certain network parameters, which characterize either a connection or a network service on a monitored host or a network service on a monitored network.

This categorization of parameters helps detect varied classes of attacks including denial-of-service, port scan and buffer overflow attacks. Anomaly-based systems use various analysis techniques to detect parameter anomalies. A new approach based on Bayesian Networks technique for analyzing and detecting anomalies is presented here.

The advantage of Bayesian Networks lies in their ability to adaptively learn normal values of parameters without much training, which makes it suitable for real-time analysis. Bayesian Network can be used to combine current evidence and previous knowledge to obtain the probability of anomaly.

This property helps in detecting previously seen attacks faster, since the previous knowledge provides strong evidence of an attack. The same property helps reduce the number of false positives, since considerable evidence needs to accumulate for the Bayesian Network to report high probability of anomaly.Computational Intelligence in Intrusion Detection System Thesis Submitted to Department of Mathematics, Faculty of Science, Al-Azhar iii.

Abstract Intrusion detection system (IDS) is a major research problem in network. Masters Thesis Defense “Deep Learning Approach for Intrusion Detection System(IDS) in an Internet of Things(IoT) network using Gated Recurrent Neural Networks (LSTM and GRU)” By Manoj Kumar Putchala.

Export; Thursday, July 27, , 2 pm to 4 pm. Campus: Dayton. Focus. Develop intrusion detection, mitigation and forensic analysis capabilities for CASE-V to defend against future advanced threats, and develop integrated .

Existing Intrusion Detection Systems (IDS) examine all the network features to detect intrusion or misuse patterns. In feature-based intrusion detection, some selected features may found to be redundant, useless or less important than the rest.

This paper proposes a category-based selection of. Olin mba essays sample research papers title page college essays on fathers essential characteristics good parent essay phd thesis on industrial engineering.

Essays on beauty and media percpetion checking essays master thesis business process management computers and humans essays environmental law research paper. Network Intrusion Detection System (NIDS) mode: This is the most complex mode and allows matching packets against a user defined set of rules and performing several actions like drop, pass, alert etc.

based on what it sees.

Intrusion detection thesis 2012
Research on Intrusion Detection Based on Machine Learning - PhD thesis - Dissertation