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Dissertations / Theses on the topic 'Network intrusion detection system'

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Published: 4 June 2021

Last updated: 25 July 2025

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1

Maharjan, Nadim, and Paria Moazzemi. "Telemetry Network Intrusion Detection System." International Foundation for Telemetering, 2012. http://hdl.handle.net/10150/581632.

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ITC/USA 2012 Conference Proceedings / The Forty-Eighth Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2012 / Town and Country Resort & Convention Center, San Diego, California<br>Telemetry systems are migrating from links to networks. Security solutions that simply encrypt radio links no longer protect the network of Test Articles or the networks that support them. The use of network telemetry is dramatically expanding and new risks and vulnerabilities are challenging issues for telemetry networks. Most of these vulnerabilities are silent in nature and c

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2

Moten, Daryl, and Farhad Moazzami. "Telemetry Network Intrusion Detection Test Bed." International Foundation for Telemetering, 2013. http://hdl.handle.net/10150/579527.

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ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV<br>The transition of telemetry from link-based to network-based architectures opens these systems to new security risks. Tools such as intrusion detection systems and vulnerability scanners will be required for emerging telemetry networks. Intrusion detection systems protect networks against attacks that occur once the network boundary has been breached. An intrusion detection model was developed in

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3

Langin, Chester Louis. "A SOM+ Diagnostic System for Network Intrusion Detection." OpenSIUC, 2011. https://opensiuc.lib.siu.edu/dissertations/389.

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This research created a new theoretical Soft Computing (SC) hybridized network intrusion detection diagnostic system including complex hybridization of a 3D full color Self-Organizing Map (SOM), Artificial Immune System Danger Theory (AISDT), and a Fuzzy Inference System (FIS). This SOM+ diagnostic archetype includes newly defined intrusion types to facilitate diagnostic analysis, a descriptive computational model, and an Invisible Mobile Network Bridge (IMNB) to collect data, while maintaining compatibility with traditional packet analysis. This system is modular, multitaskable, scalable, i

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4

Ademi, Muhamet. "Web-Based Intrusion Detection System." Thesis, Malmö högskola, Fakulteten för teknik och samhälle (TS), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20271.

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Web applications are growing rapidly and as the amount of web sites globallyincreases so do security threats. Complex applications often interact with thirdparty services and databases to fetch information and often interactions requireuser input. Intruders are targeting web applications specifically and they are ahuge security threat to organizations and a way to combat this is to haveintrusion detection systems. Most common web attack methods are wellresearched and documented however due to time constraints developers oftenwrite applications fast and may not implement the best security pract

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5

Fleming, Theodor, and Hjalmar Wilander. "Network Intrusion and Detection : An evaluation of SNORT." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-144335.

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Network security has become a vital part for computer networks to ensure that they operate as expected. With many of today's services relying on networks it is of great importance that the usage of networks are not being compromised. One way to increase the security of a computer network is to implement a Network Intrusion Detection System (NIDS). This system monitors the traffic sent to, from and within the network. This study investigates how a NIDS called SNORT with different configurations handles common network attacks. The knowledge of how SNORT managed the attacks is used to evaluate an

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6

Hashmi, Adeel. "Hardware Acceleration of Network Intrusion Detection System Using FPGA." Thesis, Manchester Metropolitan University, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.526973.

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7

Stanley, Fred Philip. "Intrusion detection and response for system and network attacks." [Ames, Iowa : Iowa State University], 2009.

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8

Caulkins, Bruce. "SESSION-BASED INTRUSION DETECTION SYSTEM TO MAP ANOMALOUS NETWORK TRAFFIC." Doctoral diss., University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3466.

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Computer crime is a large problem (CSI, 2004; Kabay, 2001a; Kabay, 2001b). Security managers have a variety of tools at their disposal  firewalls, Intrusion Detection Systems (IDSs), encryption, authentication, and other hardware and software solutions to combat computer crime. Many IDS variants exist which allow security managers and engineers to identify attack network packets primarily through the use of signature detection; i.e., the IDS recognizes attack packets due to their well-known "fingerprints" or signatures as those packets cross the network's gateway threshold. On the other

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9

Goh, Vik Tor. "Intrusion detection framework for encrypted networks." Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/41733/1/Vik_Tor_Goh_Thesis.pdf.

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Network-based Intrusion Detection Systems (NIDSs) monitor network traffic for signs of malicious activities that have the potential to disrupt entire network infrastructures and services. NIDS can only operate when the network traffic is available and can be extracted for analysis. However, with the growing use of encrypted networks such as Virtual Private Networks (VPNs) that encrypt and conceal network traffic, a traditional NIDS can no longer access network traffic for analysis. The goal of this research is to address this problem by proposing a detection framework that allows a commercial

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10

Karkera, Akhil Narayan. "Design and implementation of a policy-based intrusion detection system generic intrusion detection model for a distributed network /." [Gainesville, Fla.] : University of Florida, 2002. http://purl.fcla.edu/fcla/etd/UFE0000550.

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11

Sonbul, O., M. Byamukama, S. Alzebda, and A. N. Kalashnikov. "Autonomous intrusion detection information system." Thesis, Сумський державний університет, 2012. http://essuir.sumdu.edu.ua/handle/123456789/28777.

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Abstract – Implementation of security arrangements for insecure premises, for example, for temporary exhibitions or infrequent public events, usually results in substantial security personnel costs which can be potentially reduced by employing an easily installable ad hoc intrusion detection information system. In the paper we described the architecture, design and experimental results for a fully prototyped information system that utilizes ultrasonic sensors operating in the pulse echo mode for the perimeter control and ZigBee transceivers for wireless networking. The system consists of inexp

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12

Zhou, Ying. "M-AdaBoost-A Based Ensemble System for Network Intrusion Detection." Thesis, The George Washington University, 2021. http://pqdtopen.proquest.com/#viewpdf?dispub=28256014.

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Network intrusion detection remains a challenging research area as it involves learning from large-scale imbalanced multiclass datasets. While machine learning algorithms have been widely used for network intrusion detection, most standard techniques cannot achieve consistent good performance across multiple classes. In this dissertation, a novel ensemble system was proposed based on the Modified Adaptive Boosting with Area under the curve (M-AdaBoost-A) algorithm to detect network intrusions more effectively. Multiple M-AdaBoost-A-based classifiers were combined into an ensemble by employing

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13

Stefanova, Zheni Svetoslavova. "Machine Learning Methods for Network Intrusion Detection and Intrusion Prevention Systems." Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7367.

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Given the continuing advancement of networking applications and our increased dependence upon software-based systems, there is a pressing need to develop improved security techniques for defending modern information technology (IT) systems from malicious cyber-attacks. Indeed, anyone can be impacted by such activities, including individuals, corporations, and governments. Furthermore, the sustained expansion of the network user base and its associated set of applications is also introducing additional vulnerabilities which can lead to criminal breaches and loss of critical data. As a result, t

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14

Techateerawat, Piya, and piyat33@yahoo com. "Key distribution and distributed intrusion detection system in wireless sensor network." RMIT University. Electrical and Computer Systems Engineering, 2008. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080729.162610.

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This thesis proposes a security solution in key management and Intrusion Detection System (IDS) for wireless sensor networks. It addresses challenges of designing in energy and security requirement. Since wireless communication consumes the most energy in sensor network, transmissions must be used efficiently. We propose Hint Key Distribution (HKD) for key management and Adaptive IDS for distributing activated IDS nodes and cooperative operation of these two protocols. HKD protocol focuses on the challenges of energy, computation and security. It uses a hint message and key chain to consume

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15

Li, Zhe. "A Neural Network Based Distributed Intrusion Detection System on Cloud Platform." University of Toledo / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1364835027.

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Chatprechakul, Nattapron. "Improving performance of distributed network intrusion intrusion detection systems using mobile agents." Thesis, Cranfield University, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.423508.

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Gandre, Amit Prafullachandra. "Implementation of a policy-based intrusion detection system--Generic Intrusion Detection Model (GIDEM version 1.1)." [Gainesville, Fla.] : University of Florida, 2001. http://purl.fcla.edu/fcla/etd/UFE0000317.

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Thesis (M.S.)--University of Florida, 2001.<br>Title from title page of source document. Document formatted into pages; contains vi, 66 p.; also contains graphics. Includes vita. Includes bibliographical references.

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18

Tucker, Christopher John. "Performance metrics for network intrusion systems." Thesis, University of Plymouth, 2013. http://hdl.handle.net/10026.1/1547.

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Intrusion systems have been the subject of considerable research during the past 33 years, since the original work of Anderson. Much has been published attempting to improve their performance using advanced data processing techniques including neural nets, statistical pattern recognition and genetic algorithms. Whilst some significant improvements have been achieved they are often the result of assumptions that are difficult to justify and comparing performance between different research groups is difficult. The thesis develops a new approach to defining performance focussed on comparing intru

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19

Satam, Pratik. "An Anomaly Behavior Analysis Intrusion Detection System for Wireless Networks." Thesis, The University of Arizona, 2015. http://hdl.handle.net/10150/595654.

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Wireless networks have become ubiquitous, where a wide range of mobile devices are connected to a larger network like the Internet via wireless communications. One widely used wireless communication standard is the IEEE 802.11 protocol, popularly called Wi-Fi. Over the years, the 802.11 has been upgraded to different versions. But most of these upgrades have been focused on the improvement of the throughput of the protocol and not enhancing the security of the protocol, thus leaving the protocol vulnerable to attacks. The goal of this research is to develop and implement an intrusion detection

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20

Ahmed, Abdulbasit. "Online network intrusion detection system using temporal logic and stream data processing." Thesis, University of Liverpool, 2013. http://livrepository.liverpool.ac.uk/12153/.

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These days, the world is becoming more interconnected, and the Internet has dominated the ways to communicate or to do business. Network security measures must be taken to protect the organization environment. Among these security measures are the intrusion detection systems. These systems aim to detect the actions that attempt to compromise the confidentiality, availability, and integrity of a resource by monitoring the events occurring in computer systems and/or networks. The increasing amounts of data that are transmitted at higher and higher speed networks created a challenging problem for

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Yang, Yi. "Intrusion detection for communication network security in power systems." Thesis, Queen's University Belfast, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.603572.

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In response to the emergence of cybersecurity issues in smarter grids, a number of IT security approaches have been presented. However, in practice, power networks with legacy systems are more difficult to update, patch and protect using conventional IT security techniques. This research presents a contribution to cybersecurity using Intrusion Detection Systems (IDS) in power systems. An intrusion detection methodology provides an approach to identify evidence of abnormal communication behaviours in a passive mode that does not impact normal operation of power systems but provides pre-emptive

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22

ANSARI, NAZLI. "MACHINE LEARNING METHODS TO IMPROVE NETWORK INTRUSION DETECTION SYSTEMS." OpenSIUC, 2019. https://opensiuc.lib.siu.edu/theses/2605.

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23

Koc, Levent. "Application of a Hidden Bayes Naive Multiclass Classifier in Network Intrusion Detection." The George Washington University, 2013.

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24

Chuluundorj, Zorigtbaatar. "Augmenting Network Flows with User Interface Context to Inform Access Control Decisions." Digital WPI, 2019. https://digitalcommons.wpi.edu/etd-theses/1331.

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Whitelisting IP addresses and hostnames allow organizations to employ a default-deny approach to network traffic. Organizations employing a default-deny approach can stop many malicious threats, even including zero-day attacks, because it only allows explicitly stated legitimate activities. However, creating a comprehensive whitelist for a default-deny approach is difficult due to user-supplied destinations that can only be known at the time of usage. Whitelists, therefore, interfere with user experience by denying network traffic to user-supplied legitimate destinations. In this thesis, we fo

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25

Sohal, Amandeep Kaur. "A taxonomy-based approach to intrusion detection system." abstract and full text PDF (free order & download UNR users only), 2007. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1446428.

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26

Trivisonno, Alessio. "Studio di un Intrusion Detection System basato su packet sampling." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15413/.

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27

Judd, John David. "Stream splitting in support of intrusion detection." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2003. http://library.nps.navy.mil/uhtbin/hyperion-image/03Jun%5FJudd.pdf.

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28

Alalade, Emmanuel. "Intrusion Detection System in Smart Home Network Using Artificial Immune System and Extreme Learning Machine." University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592135245260224.

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29

Cetin, Burak. "Wireless Network Intrusion Detection and Analysis using Federated Learning." Youngstown State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1588778320687729.

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30

Huang, Yi-an. "Intrusion Detection and Response Systems for Mobile Ad Hoc Networks." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14053.

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A mobile ad hoc network (MANET) consists of a group of autonomous mobile nodes with no infrastructure support. In this research, we develop a distributed intrusion detection and response system for MANET, and we believe it presents a second line of defense that cannot be replaced by prevention schemes. We based our detection framework on the study of attack taxonomy. We then propose a set of detection methods suitable of detecting different attack categories. Our approaches are based on protocol specification analysis with categorical and statistical measures. Node-based approaches may be to

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31

Song, Jungsuk. "Studies on High-Performance Network Intrusion Detection System Based on Unsupervised Machine Learning." 京都大学 (Kyoto University), 2009. http://hdl.handle.net/2433/123840.

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32

Zhang, Yichi. "Distributed Intrusion Detection System in A Multi-Layer Network Architecture of Smart Grids." University of Toledo / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1309783705.

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33

Yun, Ronald E. "Network defense-in-dept : evaluating host-based intrusion detection systems /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2001. http://handle.dtic.mil/100.2/ADA395808.

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34

Atakan, Mustafa. "Improving Performance Of Network Intrusion Detection Systems Through Concurrent Mechanisms." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/1061399/index.pdf.

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As the bandwidth of present networks gets larger than the past, the demand of Network Intrusion Detection Systems (NIDS) that function in real time becomes the major requirement for high-speed networks. If these systems are not fast enough to process all network traffic passing, some malicious security violations may take role using this drawback. In order to make that kind of applications schedulable, some concurrency mechanism is introduced to the general flowchart of their algorithm. The principal aim is to fully utilize each resource of the platform and overlap the independent parts of the

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Mahajan, Atul. "High speed circuit techniques for network intrusion detection systems (NIDS) /." Available to subscribers only, 2008. http://proquest.umi.com/pqdweb?did=1650508461&sid=1&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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36

Siddiqui, Abdul Jabbar. "Securing Connected and Automated Surveillance Systems Against Network Intrusions and Adversarial Attacks." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42345.

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In the recent years, connected surveillance systems have been witnessing an unprecedented evolution owing to the advancements in internet of things and deep learning technologies. However, vulnerabilities to various kinds of attacks both at the cyber network-level and at the physical worldlevel are also rising. This poses danger not only to the devices but also to human life and property. The goal of this thesis is to enhance the security of an internet of things, focusing on connected video-based surveillance systems, by proposing multiple novel solutions to address security issues at the c

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37

Pikoulas, John. "An agent-based Bayesian method for network intrusion detection." Thesis, Edinburgh Napier University, 2003. http://researchrepository.napier.ac.uk/Output/4057.

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Security is one of the major issues in any network and on the Internet. It encapsulates many different areas, such as protecting individual users against intruders, protecting corporate systems against damage, and protecting data from intrusion. It is obviously impossible to make a network totally secure, as there are so many areas that must be protected. This thesis includes an evaluation of current techniques for internal misuse of computer systems, and tries to propose a new way of dealing with this problem. This thesis proposes that it is impossible to fully protect a computer network from

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38

Augustsson, Christian, Jacobson Pontus Egeberg, and Erik Scherqvist. "Evaluating Machine Learning Intrusion Detection System classifiers : Using a transparent experiment approach." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-17192.

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There have been many studies performing experiments that showcase the potential of machine learning solutions for intrusion detection, but their experimental approaches are non-transparent and vague, making it difficult to replicate their trained methods and results. In this thesis we exemplify a healthier experimental methodology. A survey was performed to investigate evaluation metrics. Three experiments implementing and benchmarking machine learning classifiers, using different optimization techniques, were performed to set up a frame of reference for future work, as well as signify the imp

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Chang, Yen-Cheng, and 張延丞. "Network Intrusion Detection System Using Neural Network." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/01201520857843686216.

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碩士<br>國立臺灣科技大學<br>電機工程系<br>91<br>With the growth of computer networking and e-commerce climate, people have heavy relied on the internet. For this reason, more and more important information on the internet, security of networking systems has become an important research issue. TCP port 80 is the default port for HTTP Protocol. Web servers purposely listen for requests on this port. This provides hackers a good chance to attack on the Web server, and that poses a serious security threat. A Web server provides logs about every interaction between a site visitor and Web server. If an intrusion a

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Mgabile, Tinny. "Network intrusion detection system using neural networks approach in networked biometrics system." Thesis, 2014. http://hdl.handle.net/10210/10054.

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M.Phil. (Electrical and Electronic Engineering)<br>Network security has become increasingly important as more and more applica- tions are making their way into the market. The research community has proposed various methods to build a reliable network intrusion detection system to detect unauthorised activities in networked systems. However many network intrusion detection systems that have been reported in literature su er from an excessive number of false positives, false negatives, and are unable to cope with new, elegant and structured attacks. This is mainly because most network intrusion

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Chen, Sout-Fong, and 陳少鋒. "Building Intrusion Pattern Miner for Snort Network Intrusion Detection System." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/01429644317481328466.

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碩士<br>國立雲林科技大學<br>電子與資訊工程研究所碩士班<br>91<br>Snort is an open source network intrusion detection system, capable of performing real-time traffic analysis and packet logging on IP networks. However, Snort cannot generate intrusion pattern automatically. It means that experts must first analyze and categorize attack packets, and hand-code the corresponding patterns and rules for misuse detection. After that, system administrators configure Snort detection rules manually to the network intrusion detection system. This results in Snort having limited extensibility and adaptability. In this paper,

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Liao, Jheng-Mo, and 廖證模. "A Hybrid Intrusion Detection System for Contemporary Network Intrusion Dataset." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/81532931082800259784.

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碩士<br>國立臺灣大學<br>電機工程學研究所<br>105<br>As the Internet technology advances, the modern network traffic is different from the past. Our study is aimed at the contemporary network intrusion detection dataset. By constructing a hybrid intrusion detection system to detect network anomalies, we propose using a feature discretization method and a cluster analysis algorithm to separate the training samples into two groups, the normal group and the anomaly group and then the new classification model is built to improve the performance of the anomaly group classification. The feature discretization method

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Ming, Chou Jyh, and 周志明. "Design of Network-based Intrusion Detection System." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/81848088279867854005.

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碩士<br>國立交通大學<br>資訊科學系<br>90<br>In recent years, various network-based applications have been developed to provide services in many different areas. A variety of network abnormal behavior also appeared because of many causes. The famous abnormal behavior, intrusion, causes damage for many purposes. However, every application has its own behavior on network. The behaviors of network are concerned by protocols operations of applications. In this thesis, we propose an offline method to extract users’ behavior from connections and a detecting module to recognize connections online. We design the Pr

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Saha, Siddharth, and Telugu Praveen Kumar. "Network intrusion detection system using string matching." Thesis, 2010. http://ethesis.nitrkl.ac.in/1652/1/Project_Thesis.pdf.

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Network intrusion detection system is a retrofit approach for providing a sense of security in existing computers and data networks, while allowing them to operate in their current open mode. The goal of a network intrusion detection system is to identify, preferably in real time, unauthorized use, misuse and abuse of computer systems by insiders as well as from outside perpetrators. At the heart of every network intrusion detection system is packet inspection which employs nothing but string matching. This string matching is the bottleneck of performance for the whole network intrusion det

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Bapna, Deependra. "Intrusion detection system for wireless sensor network." Thesis, 2014. http://ethesis.nitrkl.ac.in/6408/1/E-94.pdf.

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A Wireless Sensor Network (WSN) is a group of sensor nodes, they monitor a certain environmental information (sound, temperature, motion, pressure, light, etc.), and transmit the information to the base station. Its important to protect the data while information transmitted into the wireless environment. Data can be protected by using cryptographic scheme. a number of attacks can be possible on WSN because of its broadcasting nature, resource restrictions, and remote area of deployment. cryptograpic security can secure network from outside attacks, but fails to protect from inside attack. so

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Yau, Wei-Chuen, and 丘偉權. "Building an Intrusion Detection System with Neural Network." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/07344852846045593073.

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碩士<br>國立成功大學<br>電機工程學系<br>89<br>Previous researches have shown that neural network (NN) is a feasible approach for developing an intrusion detection system (IDS). However, we observe that most of the previous work is valid only for detecting limited kinds of attacks. In addition, there are also little previous efforts in the implementation of a real-time NN-based IDS. This motivates us to investigate the possible methodologies and implementation techniques for developing an NN-based IDS that scale up the detection scope and can perform in real time. This thesis describes the design

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Lee, Lun-Chuan, and 李倫銓. "A Clustered Architecture for Network Intrusion Detection System." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/84755191627609925020.

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碩士<br>國立交通大學<br>資訊工程系<br>90<br>Network intrusion detection system (NIDS) can detect anomaly behaviors and attacks over the networks. In a high speed network, NIDS cannot handle the large amount of packets, and will eventually drop packets and fail to detect intrusions. In this thesis, we propose the cluster NIDS architecture for high-speed networks. The clustered architecture uses session dispatching schemes to distribute packets to its cluster nodes, where each node runs the intrusion detection system. The dispatcher in the high-speed network segment can balance the bi-directional traffic to

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Sherwood, Michael E. "System and network security : the potential of intrusion detection systems /." 2004. http://emp3.hbg.psu.edu/theses/available/etd-05072004-124842/.

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49

Gao, Jun. "Omni SCADA intrusion detection." Thesis, 2020. http://hdl.handle.net/1828/11745.

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We investigate deep learning based omni intrusion detection system (IDS) for supervisory control and data acquisition (SCADA) networks that are capable of detecting both temporally uncorrelated and correlated attacks. Regarding the IDSs developed in this paper, a feedforward neural network (FNN) can detect temporally uncorrelated attacks at an F1 of 99.967±0.005% but correlated attacks as low as 58±2%. In contrast, long-short term memory (LSTM) detects correlated attacks at 99.56±0.01% while uncorrelated attacks at 99.3±0.1%. Combining LSTM and FNN through an ensemble approach further imp

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Chen, Chun-Li, and 陳俊利. "A Study on Network Intrusion Detection System Based on Neural Network." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/78782475661244597783.

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碩士<br>國立高雄第一科技大學<br>電腦與通訊工程所<br>94<br>ABSTRACT In the e-business environment, business information is stored in computer and accessed through the Internet . That has become the new way of communication today and is the most attack service of network . Besides the known vulnerabilities, more application-level web securities have been exploited recently, such as parameter tampering, application buffer overflow, and backdoor program etc. Unfortunately, they can’t be detected by traditional intrusion detection system effectively. Thus, distributed denial of service attack not only successful on o

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