Golden chip free Trojan detection leveraging probabilistic neural network with genetic algorithm applied in the training phase

This is a preview of subscription content, access via your institution.

References

  1. 1

    Zhang X J, Zhang F, Guo S Z, et al. Optimal model search for hardware-trojan-based bit-level fault attacks on block ciphers. Sci China Inf Sci, 2018, 61: 039106

    MathSciNet  Article  Google Scholar 

  2. 2

    He J J, Zhao Y Q, Guo X L, et al. Hardware Trojan detection through chip-free electromagnetic side-channel statistical analysis. IEEE Trans VLSI Syst, 2017, 25: 2939–2948

    Article  Google Scholar 

  3. 3

    Elnaggar R, Chakrabarty K. Machine learning for hardware security: opportunities and risks. J Electron Test, 2018, 34: 183–201

    Article  Google Scholar 

  4. 4

    Xue MF, Wang J, Hu A Q. An enhanced classification-based golden chips-free hardware Trojan detection technique. In: Proceedings of IEEE Asian Hardware-Oriented Security and Trust, Yilan, 2016

    Google Scholar 

  5. 5

    Ahmadipour M, Hizam H, Othman M L, et al. Islanding detection method using ridgelet probabilistic neural network in distributed generation. Neurocomputing, 2019, 329: 188–209

    Article  Google Scholar 

  6. 6

    Nourian M A, Fazeli M, Hely D. Hardware Trojan detection using an advised genetic algorithm based logic testing. J Electron Test, 2018, 34: 461–470

    Article  Google Scholar 

Download references

Acknowledgements

This work was financially supported by National Natural Science Foundation of China (Grant No. 61832018).

Author information

Affiliations

Authors

Corresponding author

Correspondence to Yiqiang Zhao.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Liu, Y., He, J., Ma, H. et al. Golden chip free Trojan detection leveraging probabilistic neural network with genetic algorithm applied in the training phase. Sci. China Inf. Sci. 63, 129401 (2020). https://doi.org/10.1007/s11432-019-9803-8

Download citation