Malware detection method based on TPE optimized stacking

Dongbo Zhao; Zesong Yuan; Nannan Xie

doi:10.1117/12.3026447

9 February 2024 Malware detection method based on TPE optimized stacking

Dongbo Zhao, Zesong Yuan, Nannan Xie

Proceedings Volume 13073, Third International Conference on High Performance Computing and Communication Engineering (HPCCE 2023); 130730D (2024) https://doi.org/10.1117/12.3026447
Event: Third International Conference on High Performance Computing and Communication Engineering (HPCCE 2023), 2023, Changsha, China

Abstract

Fast detection and categorization of malware are increasingly important for securing hosts and networks. Although many Machine Learning models have been utilized to detect malware, single-model detection may not remain efficient in the face of diverse datasets. The continuously increasing size of malware need the distributed storage systems and distributed computing. The distributed methods and ensemble learning are introduced into malware detection, and an optimal combination of base classifiers suitable for stacking are designed. A hyperparameter optimization method based on the Tree-structured Parzen Estimator (TPE) approach to enhance malware detection. The proposed method is implemented on Apache Spark and Hadoop Distributed File System(HDFS). Experiments conducted on four independent datasets, including Android and Windows, demonstrate that the proposed method can achieve 99.41% accuracy on the Android dataset and 96.96% accuracy on the Windows dataset.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Dongbo Zhao, Zesong Yuan, and Nannan Xie "Malware detection method based on TPE optimized stacking", Proc. SPIE 13073, Third International Conference on High Performance Computing and Communication Engineering (HPCCE 2023), 130730D (9 February 2024); https://doi.org/10.1117/12.3026447

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