A Static API Analysis and Installation Advisory System for Android Applications

• Main Authors: Chih-An Chang, 張至安
• Other Authors: 王勝德
• Format: Others
• Language: en_US
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/48947107099887469221

碩士 === 國立臺灣大學 === 電機工程學研究所 === 102 === Android has been one of the most popular operating systems for the mobile devices. And the Android’s permission system can inform users the privacy information used by the applications to be installed, but it only tells the very basic information. In this paper, the goal is to make sure users can understand the risks of installing an application. When users upload an .apk file, the proposed system extracts information about this application, including using API calls, permissions, and selected features. To analyze individual privacy breach or possibility of attack, with selected features and heuristic rules, we used static analysis and focused on analyzing the disassembled code. The analytic results are kept in the database, and then the results are translated into understandable sentences and displayed on a webpage for users to access. For the non-technical users, we make an assessment for them. We calculate the risk score for each individual application, and set a threshold to determine if it is a malware or not. The risk score is heuristic-based. We applied the analytic tools on part of the benign and malware datasets, and examined the results to find the pattern of determining the malicious applications, and then gave them a weighted function, which is adjusted by knowledge and the test results, to achieve the highest accuracy. Our dataset contains 936 applications, including 200 malwares and 736 benign applications. The result is 85.15% accuracy with 81.5% true positive rate and 13.86% false positive rate.