title: ÐÐ±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ ÑÑÐ·Ð²Ð¸Ð¼Ð¾ÑÑÐµÐ¹ Ð² Android Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸ÑÑ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð³ÑÐ°ÑÐ° ÑÐ¸ÑÑÐµÐ¼Ð½ÑÑ Ð²ÑÐ·Ð¾Ð²Ð¾Ð²
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: Detection of vulnerabilities in Android applications based on system call graph analysis
Creators: name: ÐÐ°ÑÐ°Ð±Ð°Ð½Ð¾Ð², ÐÐ¼Ð¸ÑÑÐ¸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: 2022
Subjects: ÐºÐ¸Ð±ÐµÑÐ±ÐµÐ·Ð¾Ð¿Ð°ÑÐ½Ð¾ÑÑÑ Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ð¹
Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ ÑÑÐ·Ð²Ð¸Ð¼Ð¾ÑÑÐµÐ¹
Ð²ÑÐµÐ´Ð¾Ð½Ð¾ÑÐ½Ð¾Ðµ Ð¿Ð¾
ÑÐ¸ÑÑÐµÐ¼Ð½ÑÐµ Ð²ÑÐ·Ð¾Ð²Ñ
Ð³ÑÐ°ÑÐ¸ÑÐµÑÐºÐ¸Ðµ ÑÐ¸Ð³Ð½Ð°Ð»Ñ
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
cybersecurity of android applications
vulnerability detection
malware
system calls
graphical signals
machine learning

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description: The subject of the graduate qualification work is Â«Detection of vulnerabilities in Android applications based on the analysis of the system call graphÂ». The purpose of this graduate qualification work is to study the possibility of detecting vulnerabilities in Android applications based on the analysis of the system call graph. The subject of the research is the detection of vulnerabilities in Android applications based on the analysis of the system call graph. When detecting unauthorized access vulnerabilities, the main idea is to indicate and trace the moment where any malicious software is introduced into the normal operation of an application. Ideas practiced with the methods of static and dynamic analysis of software were used for this idea. As a result, a vulnerability detection system model was proposed based on a modification of the GSDroid system, namely the modification of the averaged weighting coefficients. The second modification â named as the expected weighting factor method was found to be inapplicable for detecting vulnerabilities in Android applications. Even so, with a sufficiently large system call log, the result of this method tends to a perfect theoretical prediction of weighting factors at frequencies that can be used to detect malware. Briefly stated, the field of application of the results obtained is vulnerability detection systems and malware detection systems.