Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/522109
Title: Efficient network attack detection based on deep learning techniques
Researcher: Poornima,R
Guide(s): Singaravel,G
Keywords: Deep Learning
Information And Communication Engineering
Machine Learning
University: Anna University
Completed Date: 2023
Abstract: The significant growth in the use of the Internet and the rapid newlinedevelopment of network technologies are associated with an increased risk of newlinenetwork attacks. Network attacks refer to all types of unauthorized access to a newlinenetwork including any attempts to damage and disrupt the network, often newlineleading to serious consequences. The Internet helps foster connection and newlinecommunication, but the integrity and confidentiality of these connections and newlineinformation exchanges can be violated and compromised by attackers who newlineseek to damage and disrupt network connections and network security. newlineEvolution of different types of network attacks and an increase in the data newlineexchange between the computing devices pose the requirement to secure newlinenetwork and computing devices. newline newline
Pagination: xxii,195p.
URI: http://hdl.handle.net/10603/522109
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File46.8 kBAdobe PDFView/Open
02_prelim_pages.pdf1.2 MBAdobe PDFView/Open
03_content.pdf219.04 kBAdobe PDFView/Open
04_abstract.pdf217.42 kBAdobe PDFView/Open
05_chapter 1.pdf1.06 MBAdobe PDFView/Open
06_chapter 2.pdf436.53 kBAdobe PDFView/Open
07_chapter 3.pdf1.11 MBAdobe PDFView/Open
08_chapter 4.pdf857.13 kBAdobe PDFView/Open
09_chapter 5.pdf1.16 MBAdobe PDFView/Open
10_chapter 6.pdf899.11 kBAdobe PDFView/Open
11_annexures.pdf421.24 kBAdobe PDFView/Open
80_recommendation.pdf178.88 kBAdobe PDFView/Open
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