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StackDroid: Evaluation of a Multi-level Approach for Detecting the Malware on Android Using Stacked Generalization

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Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1035))

Abstract

Attackers or cyber criminals are getting encouraged to develop android malware because of the rapidly growing rate of android users. To detect android malware, researchers and security specialist have been started to contribute on android malware analysis and detection related tasks using machine learning algorithms. In this paper, Stacked Generalization has been used to minimize the error rate and a multi-level architecture based approach named StackDroid has been presented and evaluated. In this experiment, Extremely Randomized Tree (ET), Random Forest (RF), Multi-Layer Perceptron (MLP) and Stochastic Gradient Descent (SGD) classifiers have been used as base classifiers in level 1 and Extreme Gradient Boosting (EGB) has been used as final predictor in level 2. It’s been found that StackDroid provides 99% of Area Under Curve (AUC), 1.67% of False Positive Rate (FPR) and 97% detection accuracy on DREBIN dataset which provides a strong basement to the development of android malware scanner.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Jahangirnagar University, Savar, Dhaka, Bangladesh

    Sheikh Shah Mohammad Motiur Rahman & Sanjit Kumar Saha

  2. Department of Software Engineering, Daffodil International University, Dhaka, Bangladesh

    Sheikh Shah Mohammad Motiur Rahman

Authors
  1. Sheikh Shah Mohammad Motiur Rahman
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  2. Sanjit Kumar Saha
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Correspondence to Sheikh Shah Mohammad Motiur Rahman .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of South Dakota, Vermillion, SD, USA

    K. C. Santosh

  2. Solapur University, Solapur, India

    Ravindra S. Hegadi

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Motiur Rahman, S.S.M., Saha, S.K. (2019). StackDroid: Evaluation of a Multi-level Approach for Detecting the Malware on Android Using Stacked Generalization. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1035. Springer, Singapore. https://doi.org/10.1007/978-981-13-9181-1_53

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  • DOI: https://doi.org/10.1007/978-981-13-9181-1_53

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  • Print ISBN: 978-981-13-9180-4

  • Online ISBN: 978-981-13-9181-1

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