Behaviour-based/Trend-based malware analysis on the Android Application

Malicious software, as known as malware, has raised an increasing concern over the recent years. This paper outlines the trend and static behaviour of various malware that are commonly found in the android application. Static behaviour of the malicious application can be reverse-engineer into mul...

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Main Author: Siow, Jing Kai
Other Authors: Liu Yang
Format: Final Year Project
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/10356/70271
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-702712023-03-03T20:28:54Z Behaviour-based/Trend-based malware analysis on the Android Application Siow, Jing Kai Liu Yang School of Computer Science and Engineering DRNTU::Engineering::Computer science and engineering Malicious software, as known as malware, has raised an increasing concern over the recent years. This paper outlines the trend and static behaviour of various malware that are commonly found in the android application. Static behaviour of the malicious application can be reverse-engineer into multiple phase. This can be done using various tools that are available in the internet. With understanding of the smali and Java programming language, the static behaviour of any Android application can be learned easily. Trend analysis can be carried out using the dataset that are gathered throughout various android market, such as wangyi, googleplay, QQ etc. This paper also outlines the techniques and aspects that are used in analysing the trends and the behaviour of the malicious application. Using various analysing aspects and techniques, several statistics data was inferred from the database. These results can be useful for more future study and statistical analysis. This information can be valuable to the community of the malware researchers. Bachelor of Engineering (Computer Science) 2017-04-18T06:57:54Z 2017-04-18T06:57:54Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/70271 en Nanyang Technological University 71 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Siow, Jing Kai
Behaviour-based/Trend-based malware analysis on the Android Application
description Malicious software, as known as malware, has raised an increasing concern over the recent years. This paper outlines the trend and static behaviour of various malware that are commonly found in the android application. Static behaviour of the malicious application can be reverse-engineer into multiple phase. This can be done using various tools that are available in the internet. With understanding of the smali and Java programming language, the static behaviour of any Android application can be learned easily. Trend analysis can be carried out using the dataset that are gathered throughout various android market, such as wangyi, googleplay, QQ etc. This paper also outlines the techniques and aspects that are used in analysing the trends and the behaviour of the malicious application. Using various analysing aspects and techniques, several statistics data was inferred from the database. These results can be useful for more future study and statistical analysis. This information can be valuable to the community of the malware researchers.
author2 Liu Yang
author_facet Liu Yang
Siow, Jing Kai
format Final Year Project
author Siow, Jing Kai
author_sort Siow, Jing Kai
title Behaviour-based/Trend-based malware analysis on the Android Application
title_short Behaviour-based/Trend-based malware analysis on the Android Application
title_full Behaviour-based/Trend-based malware analysis on the Android Application
title_fullStr Behaviour-based/Trend-based malware analysis on the Android Application
title_full_unstemmed Behaviour-based/Trend-based malware analysis on the Android Application
title_sort behaviour-based/trend-based malware analysis on the android application
publishDate 2017
url http://hdl.handle.net/10356/70271
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