An empirical evaluation of the interpretation methods on Malware analysis

Malware (malicious software) is a type of software design to damage or abuse any programmable system or network. Most malware do not draw attention to themselves and cannot be seen with the naked eye. Therefore, malware analysis is needed as it is the process of getting to know the behavior and moti...

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Main Author: Lee, Andrew Jian Hao
Other Authors: Liu Yang
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/157254
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1572542022-05-11T13:18:21Z An empirical evaluation of the interpretation methods on Malware analysis Lee, Andrew Jian Hao Liu Yang School of Computer Science and Engineering yangliu@ntu.edu.sg Engineering::Computer science and engineering Malware (malicious software) is a type of software design to damage or abuse any programmable system or network. Most malware do not draw attention to themselves and cannot be seen with the naked eye. Therefore, malware analysis is needed as it is the process of getting to know the behavior and motive of suspicious files or Uniform Resource Locator (URL). Malware analysis can be conducted in 2 manners, static, dynamic, or even both. Static analysis is the testing and evaluation of the internal structure of the application while running it. Dynamic analysis does the total opposite of static analysis where it tests and evaluate on the application during runtime. Throughout the period of my FYP, we will be building up a machine learning model. We will be applying interpretation method of Tensorflow as our source platform for machine learning. To generate our model, we use Keras as training for deep learning models. To evaluate the accuracy of the model, we will be using functional model which allows to build random graphs of layers. Bachelor of Engineering (Computer Engineering) 2022-05-11T13:18:21Z 2022-05-11T13:18:21Z 2022 Final Year Project (FYP) Lee, A. J. H. (2022). An empirical evaluation of the interpretation methods on Malware analysis. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157254 https://hdl.handle.net/10356/157254 en SCSE21-0220 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
spellingShingle Engineering::Computer science and engineering
Lee, Andrew Jian Hao
An empirical evaluation of the interpretation methods on Malware analysis
description Malware (malicious software) is a type of software design to damage or abuse any programmable system or network. Most malware do not draw attention to themselves and cannot be seen with the naked eye. Therefore, malware analysis is needed as it is the process of getting to know the behavior and motive of suspicious files or Uniform Resource Locator (URL). Malware analysis can be conducted in 2 manners, static, dynamic, or even both. Static analysis is the testing and evaluation of the internal structure of the application while running it. Dynamic analysis does the total opposite of static analysis where it tests and evaluate on the application during runtime. Throughout the period of my FYP, we will be building up a machine learning model. We will be applying interpretation method of Tensorflow as our source platform for machine learning. To generate our model, we use Keras as training for deep learning models. To evaluate the accuracy of the model, we will be using functional model which allows to build random graphs of layers.
author2 Liu Yang
author_facet Liu Yang
Lee, Andrew Jian Hao
format Final Year Project
author Lee, Andrew Jian Hao
author_sort Lee, Andrew Jian Hao
title An empirical evaluation of the interpretation methods on Malware analysis
title_short An empirical evaluation of the interpretation methods on Malware analysis
title_full An empirical evaluation of the interpretation methods on Malware analysis
title_fullStr An empirical evaluation of the interpretation methods on Malware analysis
title_full_unstemmed An empirical evaluation of the interpretation methods on Malware analysis
title_sort empirical evaluation of the interpretation methods on malware analysis
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/157254
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