Machine learning based hybrid behavior model for Android malware analysis
碩士 === 國立臺灣大學 === 電機工程學研究所 === 102 === Malware analysis on the Android platform has been an important issue as the platform is prevalent. We proposed a detection approach based on a static analysis and machine learning techniques to obtain a considerably accurate Android malware classifier. By condu...
Main Authors: | Hsin-Yu Chuang, 莊欣瑜 |
---|---|
Other Authors: | Sheng-De Wang |
Format: | Others |
Language: | en_US |
Published: |
2014
|
Online Access: | http://ndltd.ncl.edu.tw/handle/13979250239359695096 |
Similar Items
-
Study on Android Hybrid Malware Detection Based on Machine Learning
by: LIU, TSUNG-PING, et al.
Published: (2018) -
An Android Behavior-Based Malware Detection using Machine Learning
by: Chang, Wei-Ling, et al.
Published: (2015) -
Android Malware Detection Based on Machine Learning
by: Chun-Hsuan Chang, et al.
Published: (2016) -
Android malware detection based on machine learning analysis
by: Wen-Chuan Chang, et al.
Published: (2013) -
Android Malware Detection Based on a Hybrid Deep Learning Model
by: Tianliang Lu, et al.
Published: (2020-01-01)