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Applying Machine Learning Techniques to Detect and Analyze Web Phishing Attacks.

, , and . iiWAS, page 355-359. ACM, (2018)

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Mobile Malware Detection using Op-code Frequency Histograms., , and . SECRYPT, page 27-38. SciTePress, (2015)Real-Time Driver Behaviour Characterization Through Rule-Based Machine Learning., , , , and . SAFECOMP Workshops, volume 11094 of Lecture Notes in Computer Science, page 374-386. Springer, (2018)Applying Machine Learning Techniques to Detect and Analyze Web Phishing Attacks., , and . iiWAS, page 355-359. ACM, (2018)Silent and Continuous Authentication in Mobile Environment., , , and . SECRYPT, page 97-108. SciTePress, (2016)Android malware detection based on system call sequences and LSTM., , , , and . Multimedia Tools Appl., 78 (4): 3979-3999 (2019)A Novel Structural-Entropy-based Classification Technique for Supporting Android Ransomware Detection and Analysis., , and . FUZZ-IEEE, page 1-7. IEEE, (2018)Machine Learning to Identify Gender via Hair Elements., , , , and . IJCNN, page 1-7. IEEE, (2019)Wearable Devices for Human Activity Recognition and User Detection., , , , and . PDP, page 365-372. IEEE, (2019)VizMal: A Visualization Tool for Analyzing the Behavior of Android Malware., , , and . ICISSP, page 517-525. SciTePress, (2018)Identifying Insecure Features in Android Applications using Model Checking., , and . ICISSP, page 589-596. SciTePress, (2018)