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A Classic Multi-method Collaborative Obfuscation Strategy

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Data Mining and Big Data (DMBD 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1454))

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Abstract

Code obfuscation is a kind of powerful protection technique for software code. At present, research on obfuscation techniques is mainly focused on analyzing the effect of single obfuscation method, leaving few discussions on cooperative obfuscation of multiple methods. This paper firstly presented a brief introduction of the concept and methods of code obfuscation, then designed and implemented an obfuscator with multiple obfuscation methods. Then, a collaborative obfuscation strategy suitable for multiple obfuscation methods is proposed in detail. Finally, we verified that the obfuscation strategy indeed improves the performance of obfuscation through experiments.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (no. 62072037) and Zhejiang Lab (2020LE0AB02).

Author information

Authors and Affiliations

  1. School of Computer Science, Beijing Institute of Technology, Beijing, 100081, China

    Yujie Ma, Yuanzhang Li, Zhibin Zhang & Lu Liu

  2. Zhejiang Lab, Hangzhou, 310000, China

    Ruyun Zhang

  3. Department of Computer Science and Technology, Tangshan University, Tangshan, 063000, China

    Xiaosong Zhang

Authors
  1. Yujie Ma
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  2. Yuanzhang Li
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  3. Zhibin Zhang
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  4. Ruyun Zhang
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  5. Lu Liu
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  6. Xiaosong Zhang
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Corresponding author

Correspondence to Lu Liu .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

  3. The University of Sydney, Sydney, Australia

    Albert Zomaya

  4. Guangzhou University, Guangzhou, China

    Hongyang Yan

  5. Guangdong Polytechnic Normal University, Guangzhou, China

    Jun Cai

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Ma, Y., Li, Y., Zhang, Z., Zhang, R., Liu, L., Zhang, X. (2021). A Classic Multi-method Collaborative Obfuscation Strategy. In: Tan, Y., Shi, Y., Zomaya, A., Yan, H., Cai, J. (eds) Data Mining and Big Data. DMBD 2021. Communications in Computer and Information Science, vol 1454. Springer, Singapore. https://doi.org/10.1007/978-981-16-7502-7_10

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  • DOI: https://doi.org/10.1007/978-981-16-7502-7_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-7501-0

  • Online ISBN: 978-981-16-7502-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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