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Integration of Multi-modal Features for Android Malware Detection Using Linear SVM.

, , , , and . AsiaJCIS, page 141-146. IEEE, (2016)

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A new approach to discover interlacing data structures in high-dimensional space., , and . J. Intell. Inf. Syst., 33 (1): 3-22 (2009)The Effects of Different Representations on Malware Motif Identification., , , and . CIS, page 86-90. IEEE Computer Society, (2012)A Provably Secure Two-Party Attribute-Based Key Agreement Protocol., , and . IIH-MSP, page 1042-1045. IEEE Computer Society, (2009)A study on association rule mining of darknet big data., , , , , and . IJCNN, page 1-7. IEEE, (2015)A Darknet Traffic Analysis for IoT Malwares Using Association Rule Learning., , , , and . INNS Conference on Big Data, volume 144 of Procedia Computer Science, page 118-123. Elsevier, (2018)Mining interlacing manifolds in high dimensional spaces., , , , and . SAC, page 942-949. ACM, (2011)A Cross-Platform Study on IoT Malware., , , and . ICMU, page 1-2. IEEE, (2018)Detecting Malicious Spam Mails: An Online Machine Learning Approach., , , , , and . ICONIP (3), volume 8836 of Lecture Notes in Computer Science, page 365-372. Springer, (2014)Combat Security Alert Fatigue with AI-Assisted Techniques., , , and . CSET @ USENIX Security Symposium, page 9-16. ACM, (2021)A Machine Learning Approach to Detection of Critical Alerts from Imbalanced Multi-Appliance Threat Alert Logs., , , and . IEEE BigData, page 2119-2127. IEEE, (2021)