A Comparative Analysis of Performances of Different Ensemble Approaches for Classification of Android Malwares
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-4193-1_8
Reference17 articles.
1. Yang Z, Jin M, Zhang Z, Lu J, Hao K (2017) Classification based on feature extraction for hepatocellular carcinoma diagnosis using high throughput DNA methylation sequencing data. Proc Comput Sci 107:412–417. https://doi.org/10.1016/j.procs.2017.03.130
2. Bhattacharya A, Goswami RT (2017) Comparative analysis of different feature ranking techniques in data mining-based android malware detection. In: Satapathy S, Bhateja V, Udgata S, Pattnaik P (eds) Proceedings of the 5th international conference on frontiers in intelligent computing: theory and applications. Springer. https://doi.org/10.1007/978-981-10-3153-3_5
3. Bhattacharya A, Goswami RT (2017) DMDAM: data mining based detection of android malware. In: Mandal J, Satapathy S, Sanyal M, Bhateja V (eds) Proceedings of the first international conference on intelligent computing and communication. Advances in intelligent systems and computing, vol 458. Springer, Singapore. https://doi.org/10.1007/978-981-10-2035-3_20
4. Bhattacharya A, Goswami RT (2017) Comparative analysis of different feature ranking techniques in data mining-based android malware detection. In: Satapathy S, Bhateja V, Udgata S, Pattnaik P (eds) Proceedings of the 5th international conference on frontiers in intelligent computing: theory and applications. Advances in intelligent systems and computing, vol 515. Springer, Singapore. https://doi.org/10.1007/978-981-10-3153-3_5
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