An xception convolutional neural network for malware classification with transfer learning

Wai Weng Lo, Xu Yang, Yapeng Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

69 Citations (Scopus)

Abstract

In this work, we applied a deep Convolutional Neural Network (CNN) with Xception model to perform malware image classification. The Xception model is a recently developed special CNN architecture that is more powerful with less over- fitting problems than the current popular CNN models such as VGG16. However only a few use cases of the Xception model can be found in literature, and it has never been used to solve the malware classification problem. The performance of our approach was compared with other methods including KNN, SVM, VGG16 etc. The experiments on two datasets (Malimg and Microsoft Malware Dataset) demonstrated that the Xception model can achieve the highest training accuracy than all other approaches including the champion approach, and highest validation accuracy than all other approaches including VGG16 model which are using image-based malware classification (except the champion solution as this information was not provided). Additionally, we proposed a novel ensemble model to combine the predictions from.bytes files and.asm files, showing that a lower logloss can be achieved. Although the champion on the Microsoft Malware Dataset achieved a bit lower logloss, our approach does not require any features engineering, making it more effective to adapt to any future evolution in malware, and very much less time consuming than the champion's solution.

Original languageEnglish
Title of host publication2019 10th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2019 - Proceedings and Workshop
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728115429
DOIs
Publication statusPublished - Jun 2019
Event10th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2019 - Canary Islands, Spain
Duration: 24 Jun 201926 Jun 2019

Publication series

Name2019 10th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2019 - Proceedings and Workshop

Conference

Conference10th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2019
Country/TerritorySpain
CityCanary Islands
Period24/06/1926/06/19

Keywords

  • Convolutional neural network (CNN)
  • Image classification
  • Malware classification
  • Transfer learning
  • Xception

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