title: ÐÐ½Ð°Ð»Ð¸Ð· Ð¿Ð¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ Android-Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ð¹ Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸ÐµÐ¼ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° ÑÐ¿ÐµÑÐ¸Ð°Ð»Ð¸ÑÑÐ°
titleType: Subtitle
title: Analysis of the behavior of Android applications using machine learning methods
Creators: name: ÐÐ²Ð°Ð½Ð¾Ð², ÐÐ²Ð³ÐµÐ½Ð¸Ð¹
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: ÐÐ°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð°Ð½Ð°Ð»Ð¸Ð· Ð¿Ð¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ
Ð²ÑÑÐ²Ð»ÐµÐ½Ð¸Ðµ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½ÑÑ Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ð¹
behavior analysis
detection of malic apps

description: Ð¢ÐµÐ¼Ð° Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ: Â«ÐÐ½Ð°Ð»Ð¸Ð· Ð¿Ð¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ Android-Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ð¹ Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸ÐµÐ¼ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸ÑÂ». Ð¦ÐµÐ»ÑÑ ÑÐ°Ð±Ð¾ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Android-Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ð¹ Ð¿ÑÐ¸ Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð¼ Ð°Ð½Ð°Ð»Ð¸Ð·Ðµ Ð¿Ð¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ, Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ. ÐÑÐµÐ´Ð¼ÐµÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÐµÑÑÑ Ð¼ÐµÑÐ¾Ð´Ñ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¿Ð¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½ÑÑ Android-Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ð¹ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ. ÐÐ°Ð´Ð°ÑÐ¸, ÑÐµÑÐ°ÐµÐ¼ÑÐµ Ð² ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ: 1. ÐÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¾ÑÐ½Ð¾Ð²Ð½ÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½ÑÑ Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ñ Ð² ÐÐ¡ Android. 2. ÐÑÐ±Ð¾Ñ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² Ð¸ Ð¼ÐµÑÐ¾Ð´Ð° Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¿Ð¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ Ð·Ð»Ð¾Ð²ÑÐµÐ´Ð½Ð¾Ð³Ð¾ Ð¿Ð¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ð¹. 3. ÐÐ¾Ð´Ð³Ð¾ÑÐ¾Ð²ÐºÐ° Ð¾Ð±ÑÑÐ°ÑÑÐµÐ¹ Ð²ÑÐ±Ð¾ÑÐºÐ¸ Ð´Ð»Ñ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ð¹. 4. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð³Ð¾ Ð¿ÑÐ¾ÑÐ¾ÑÐ¸Ð¿Ð° ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾ÑÐ° Ð´Ð»Ñ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð³Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¿Ð¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ. 5. ÐÑÐµÐ½ÐºÐ° ÐºÐ°ÑÐµÑÑÐ²Ð° ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½Ð¾Ð³Ð¾ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾ÑÐ°. Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ»Ð° Ð¿ÑÐ¾Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ñ Ð¼ÐµÑÐ¾Ð´Ñ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½ÑÑ Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ð¹ Ð² ÐÐ¡ Android. Ð ÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð° Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½Ð°Ñ Ð¿ÐµÑÐ¾ÑÐ½Ð¸ÑÐ° Ð¸Ð·Ð²Ð»ÐµÑÐµÐ½Ð¸Ñ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² Ð¸Ð· apk-ÑÐ°Ð¹Ð»Ð¾Ð². Ð¡Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð° ÑÐ½Ð¸ÐºÐ°Ð»ÑÐ½Ð°Ñ Ð¾Ð±ÑÑÐ°ÑÑÐ°Ñ Ð²ÑÐ±Ð¾ÑÐºÐ°, ÐºÐ¾ÑÐ¾ÑÐ°Ñ Ð²ÐºÐ»ÑÑÐ°ÐµÑ Ð² ÑÐµÐ±Ñ 215 Ð»ÐµÐ³Ð¸ÑÐ¸Ð¼Ð½ÑÑ Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ð¹ Ð¸ 203 Ð·Ð»Ð¾Ð²ÑÐµÐ´Ð½ÑÑ Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ñ. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÐ¹ Ð¿ÑÐ¾ÑÐ¾ÑÐ¸Ð¿ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾ÑÐ°, Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÐ¸Ð¹ Ð¼Ð¾Ð´ÐµÐ»Ñ ÑÐ»ÑÑÐ°Ð¹Ð½Ð¾Ð³Ð¾ Ð»ÐµÑÐ° Ð´Ð»Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Android-Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ð¹. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½ÑÐ¹ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾Ñ ÑÐ¿Ð¾ÑÐ¾Ð±ÐµÐ½ Ð²ÐµÑÐ½Ð¾ Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÑÑÑ Ð·Ð»Ð¾Ð²ÑÐµÐ´Ð½ÑÐµ Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ñ Ð² 97,4% ÑÐ»ÑÑÐ°Ñ.
description: The topic of the graduate qualification work: Â«Analysis of the behavior of Android applications using machine learning methodsÂ». The purpose of the work is to create a classification model for Android apps in automated behavior analysis using machine learning methods. The subject of the research is methods for analyzing the behavior of malicious Android applications using machine learning. 1. Research of the main methods for analyzing malicious applications in the Android OS. 2. Choice of parameters and machine learning method for analyzing the behavior of malicious application behavior. 3. Preparing a training sample for investigating applications. 4. Development of a classifier software prototype for automated behavior analysis. 5. Quality assessment of the developed classifier. As a result of the work, the main methods for analyzing malicious applications in the Android OS were analyzed. Implemented an automated sandbox, extracting parameters of apk-files. A unique training sample has been compiled, which includes 215 legitimate applications and 203 malicious applications. A software prototype of a classifier has been developed that uses a random forest model to classification Android applications. The developed classifier reliably detects malicious applications in 97.4% of detections.