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Measuring the risk value of sensitive dataflow path in Android applications.

, , and . Secur. Commun. Networks, 9 (18): 5918-5933 (2016)

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Enhancing malware analysis sandboxes with emulated user behavior., , , , and . Comput. Secur., (2022)Android Malware Detection Based on Call Graph via Graph Neural Network., , , , , and . NaNA, page 368-374. IEEE, (2020)Compositional Information Flow Verification for Inter Application Communications in Android System., , , and . ML4CS, volume 11806 of Lecture Notes in Computer Science, page 239-252. Springer, (2019)Lightweight Security Authentication Mechanism Towards UAV Networks., , , , , , , and . NaNA, page 379-384. IEEE, (2019)Measuring the risk value of sensitive dataflow path in Android applications., , and . Secur. Commun. Networks, 9 (18): 5918-5933 (2016)ACDroid: Detecting Collusion Applications on Smart Devices., , , , and . SciSec, volume 14299 of Lecture Notes in Computer Science, page 3-22. Springer, (2023)BejaGNN: behavior-based Java malware detection via graph neural network., , , , and . J. Supercomput., 79 (14): 15390-15414 (September 2023)Selecting Critical Data Flows in Android Applications for Abnormal Behavior Detection., , and . Mob. Inf. Syst., (2017)PatchDB: A Large-Scale Security Patch Dataset., , , , and . DSN, page 149-160. IEEE, (2021)Android Malware Detection via Graph Representation Learning., , , , , and . Mob. Inf. Syst., (2021)