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Risk Measurement Method of Collusion Privilege Escalation Attacks for Android Apps Based on Feature Weight and Behavior Determination
Author(s) -
Hui Li,
Limin Shen,
Yuying Wang,
Jiayin Feng,
Honglei Tan,
Zhiming Li
Publication year - 2021
Publication title -
security and communication networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.446
H-Index - 43
eISSN - 1939-0114
pISSN - 1939-0122
DOI - 10.1155/2021/8814844
Subject(s) - collusion , computer science , analytic hierarchy process , android (operating system) , privilege (computing) , benchmark (surveying) , feature (linguistics) , data mining , computer security , operations research , operating system , mathematics , linguistics , philosophy , geodesy , economics , microeconomics , geography
To solve the issue of measuring the risk of the application-layer collusion privilege escalation attacks in Android apps, this paper proposed a risk measurement method based on the feature weight and behavior determination. Analytic hierarchy process (AHP) is used to calculate the weight of feature in the feature set extracted from the app. App behavior and attack behavior are modeled by process algebra. The weak equivalent and nonequivalent are introduced to determine the behavior of apps, whereas the measurement function is constructed to calculate the app risk measurement value. In an experiment with three known apps, the measurement values are 0.629, 1, and 0.976. These results are consistent with reality, and the effectiveness and feasibility of the proposed method are verified. Through the benchmark and test set experiments, it can be seen that the measurement value of apps that has weak equivalent to attack behavior is distributed between 0.0468 and 1, and the measurement value distribution is reasonable, which verifies the accuracy and rationality of the method.

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