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LMDGW: a novel matrix based dynamic graph watermark

  • Lingling Zeng
  • Wei RenEmail author
  • Yuling Chen
  • Min Lei
Original Research

Abstract

Android platform induces an open application development framework to attract more developers and promote larger market occupations. However, the open architecture also makes it easier to reverse engineering, which results in the property loss for both developers and companies, and increases the risks of mobile malicious code. Therefore, copyright protection for android application is of significant importance. A class of copyright protection methods are based on Android watermark. Different from static watermark, the process of embedding and extracting of dynamic graph watermark (DGW) is based on the function path and operation process of the app, which has better concealment. In this paper, we proposed a late-model dynamic watermark based on matrix, called “LMDGW”. This method is proposed to overcome the shortcoming of unintuitive and vulnerable property of traditional numberal DGW. We encode a matrix with low rank into a watermark graph, and embed the graph construction statements into smali code. With the containing of sensitive block characteristics, LMDGW is able to perceive and locate the changes in the specific block. Besides, LWDGW has great performance in tamper-proof attacks. Experiment results and analysis justified that LMDGW has great data rate and robust, and is available in sensitive code locating. LMDGW is proved to be an intelligent watermarking scheme, and is enlightening for intelligent security.

Keywords

Dynamic graph watermark Matrix watermark Matrix encoding Changes locating Matrix recovery 

Notes

Acknowledgements

This work is financially supported by Open Funding of Guizhou Provincial Key Laboratory of Public Big Data, No. 2017BDKFJJ006

References

  1. Chasaki D, Mansour C (2015) Security challenges in the internet of things. In: Journal International (ed) of. Services and Data Management, Space Based and Situated Computing, Special Issue on Future InternetGoogle Scholar
  2. Chen M, Lin Z, Ma Y, Wu L (2010). The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices. Eprint Arxiv, 9Google Scholar
  3. Chen Y, Jalali A, Sanghavi S, Caramanis C (2013) Low-rank matrix recovery from errors and erasures. IEEE Trans Inf Theory 59(7):4324–4337CrossRefGoogle Scholar
  4. Cheng C, Zeng R (2016). An improved watermarking scheme based on ppct coding. Comput Knowl TechnolGoogle Scholar
  5. Cheng J, Song Y (2012). Dynamic map based on ppct structure software watermark protection. In: World automation congress, pp 133–136Google Scholar
  6. Collberg C, Myles G, Huntwork A (2003) Sandmark-a tool for software protection research. Secur Priv IEEE 1(4):40–49CrossRefGoogle Scholar
  7. Collberg C, Thomborson C (1999). Software watermarking: models and dynamic embeddings. In: ACM Sigplan-Sigact Symposium on Principles of Programming Languages, pp 311–324Google Scholar
  8. Collberg CS, Thomborson C (2000) Watermarking, tamper-proofing, and obfuscation—tools for software protection. Softw Eng IEEE Trans 28(8):735–746CrossRefGoogle Scholar
  9. Collberg CS, Thomborson C, Townsend GM (2007) Dynamic graph-based software fingerprinting. ACM Trans Program Lang Syst 29(6):35CrossRefGoogle Scholar
  10. Hamilton J, Danicic S (2011). A survey of static software watermarking. In: Internet security, pp 100–107Google Scholar
  11. In: Proc of CIHW (2013) A software watermark database scheme based on ppct. 2004:1–12Google Scholar
  12. Khalid SKA, Deris MM, Mohamad KM (2013) Anti-cropping digital image watermarking using sudoku. Int J Grid Util Comput 4(2/3):169–177CrossRefGoogle Scholar
  13. Kuzuno H, Magata K (2016) Detecting and characterising of mobile advertisement network traffic using graph modelling: Comput Int J Space Based Situat 6(2):90CrossRefGoogle Scholar
  14. Kuzuno H, Tonami S (2013). Signature generation for sensitive information leakage in android applications. In: IEEE international conference on data engineering workshops, pp 112–119Google Scholar
  15. Liu Y, Liu C, Zou H (2016) A new structure tensor based image inpainting algorithm. Int J Grid Util Comput 7(4):294–303CrossRefGoogle Scholar
  16. Luo YX, Cheng JH, Fang DY (2008). Dynamic graph watermark algorithm based on the threshold scheme. In: International symposium on information science and engineering, pp 689–693Google Scholar
  17. Palsberg J, Krishnaswamy S, Kwon M, Ma D, Shao Q, Zhang Y (2000). Experience with software watermarking. In: Computer security applications, 2000. ACSAC ’00. Conference, pp 308–316Google Scholar
  18. Ren W, Huang S, Ren Y, Raymond KK (2016a) Lipisc: a lightweight and flexible method for privacy-aware intersection set computation. Plos One 11(6):e0157752CrossRefGoogle Scholar
  19. Ren W, Liu R, Lei M, Choo KKR (2016b) Segoac: a tree-based model for self-defined, proxy-enabled and group-oriented access control in mobile cloud computing. Comput Stand Interfaces 54:29–35CrossRefGoogle Scholar
  20. Steinbauer M, Kotsis GA (2016) Dynamograph: extending the pregel paradigm for large-scale temporal graph processing. Int J Grid Util Comput 7(2):141CrossRefGoogle Scholar
  21. Wang Y (2012). Improved ppct hybrid coding scheme. Computer Engineering & ApplicationsGoogle Scholar
  22. Xiong L, Xu Z, Shi Y. Q (2017). An integer wavelet transform based scheme for reversible data hiding in encrypted images. Multidimens Syst Signal Process, pp 1–12Google Scholar
  23. Zhang H, Chen D (2012). An improved dynamic graph watermark algorithm. In: Multimedia information networking and security, pp 568–571Google Scholar
  24. Zhang Y, Chen K (2014). Appmark: A picture-based watermark for android apps. In: Eighth international conference on software security and reliability, pp 58–67Google Scholar
  25. Zhilyakova LY (2015) Dynamic graph models and their properties. Autom Remote Control 76(8):1417–1435MathSciNetCrossRefzbMATHGoogle Scholar
  26. Zhou W, Zhang X, Jiang X (2013). Appink:watermarking android apps for repackaging deterrence. pages 1–12Google Scholar
  27. Zhou Z, Wang Y, Wu QMJ, Yang CN, Sun X (2016) Effective and efficient global context verification for image copy detection. IEEE Trans Inf Forensics Secur 12(1):48–63CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Lingling Zeng
    • 1
    • 2
  • Wei Ren
    • 1
    • 2
    Email author
  • Yuling Chen
    • 2
  • Min Lei
    • 3
  1. 1.School of Computer ScienceChina University of GeosciencesWuhanPeople’s Republic of China
  2. 2.Guizhou Provincial Key Laboratory of Public Big DataGuiZhou UniversityGuiyangPeople’s Republic of China
  3. 3.Information Security CenterBeijing University of Post and Telecommunications, BeijingBeijingPeople’s Republic of China

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