Android malware detection using big data analytics techniques
Date of Issue2016
School of Electrical and Electronic Engineering
Application clones have been found in many third party markets, which not only make damage to the interest of original application developers, but also pose threats to security and privacy of mobile users. This project implements 3DCFG, which is a centroid-based clone detection method. Experiments on 10,000 Android applications demonstrate the effectiveness and scalability of the 3DCFG method. To further improve the detection speed and accuracy, a combination usage of three library detection tools is used to filter third party libraries before clone detection. A clustering-based library detection method proposed from WuKong is implemented and it is used as a library detection tool in 3DCFG library filtering part.
Final Year Project (FYP)
Nanyang Technological University