{'fraction_non_alphanumeric': 0.012036108324974924, 'fraction_numerical': 0.0, 'mean_word_length': 5.397435897435898, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
FlowSlicer - A Hybrid Approach to Detect and Avoid Sensitive Information Leaks in Android Applications using Program Slicing and Instrumentation

With the increasingly amount of private information stored in mobile devices, the need for more secure ways to detect, control and avoid malicious behaviors has become higher. The too coarse-grained permission system implemented in the Android platform does not cover problems regarding the flow of the data acquired by the apps. In order to enhance detection, awareness and avoidance of such unwanted information flows, we propose a hybrid information flow analysis that mixes the benefits of static and dynamic analysis, using slicing and instrumentation. Our results indicate a precise detection and only a small overhead while running the application. The validation of our method has been done by creating a tool called FLOWSLICER and using the category AndroidSpecific from the DROIDBENCH repository of applications with known information leaks.