Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/70271
Title: Behaviour-based/Trend-based malware analysis on the Android Application
Authors: Siow, Jing Kai
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2017
Abstract: 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.
URI: http://hdl.handle.net/10356/70271
Schools: School of Computer Science and Engineering 
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
SCE16_0265_SIOW_JING_KAI_REPORT.pdf
  Restricted Access
3.47 MBAdobe PDFView/Open

Page view(s)

404
Updated on May 7, 2025

Download(s) 50

34
Updated on May 7, 2025

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.