Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/204333
Title: Malware in Internet A study on Botnets
Researcher: Singh, Harvinder
Guide(s): Bijalwan, Anchit
Keywords: Botnets
Internet Security
Network Security
University: Uttaranchal University
Completed Date: 31.08.2017
Abstract: In the present information age of internet, botnets are becoming a challenge for the community of internet. The internet users are troubled because of these malicious activities which cause a lot of problem for the users, administrators and the internet service providers. The present research work aims to investigate the presence of BOT in the system, different types of Botnets and their harmful effects suggest the suitable technique for safeguard against particular type of bot attack. By analyzing and comparing known malware and normal processes, the study exploited differences in their network activity behavior and produced accurate and effective malware detection with minimal false positives and false negatives. Result also indicates significant improvement in detecting Malware as after observation, O1, occurred the most in the malware samples with 49% followed by O2 with 21% and O4 with 18%.The study will contribute significantly to the future research as the researchers can use the current safeguard techniques and novel designing of the app for detection of the presence of botnets and bot both together. results successfully classified a diverse group of malware and Normal process with very high accuracy and minimal false positives and false negatives. Classification algorithms correctly detected newly introduced malware samples also with minimal false negatives and false positives. Most interestingly, our data set included 31 malware samples are not detected by any tools. These undetected malware were correctly identified using our analysis in classification algorithms with few exceptions. This provides strong evidence that our identified behaviors can be added to existing behavior-based bots and malware detection solutions to help stop zero-day attacks on a host machine newline
Pagination: 132
URI: http://hdl.handle.net/10603/204333
Appears in Departments:Faculty of Uttaranchal Institute of Technology - Computer Science Engineering

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01_title_page.pdfAttached File107.44 kBAdobe PDFView/Open
02_certificate.pdf119.24 kBAdobe PDFView/Open
03_declaration.pdf105.42 kBAdobe PDFView/Open
04_preface.pdf551.97 kBAdobe PDFView/Open
05_list of tables.pdf83.79 kBAdobe PDFView/Open
06_list of figures.pdf92.72 kBAdobe PDFView/Open
07_abbreviations.pdf151.6 kBAdobe PDFView/Open
08_table of contents.pdf171.31 kBAdobe PDFView/Open
09_chapter 1.pdf439.74 kBAdobe PDFView/Open
10_chapter 2.pdf507.37 kBAdobe PDFView/Open
11_chapter 3.pdf728.42 kBAdobe PDFView/Open
12_chapter 4.pdf505.77 kBAdobe PDFView/Open
13_chapter 5.pdf282.5 kBAdobe PDFView/Open
14_chapter 6.pdf89.37 kBAdobe PDFView/Open
15_bibilography.pdf284.59 kBAdobe PDFView/Open


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