APA (7th ed.) Citation

Zhou, Z., Wang, P., Li, G., Zhang, Y., Zhou, Z., & Fang, Z. (2026). Additivity Testing Method for the Capability of Strong PUF to Resist Machine Learning Attacks Under Hybrid Obfuscation Algorithms Protection. 2026 IEEE International Test Conference in Asia (ITC-Asia), Test Conference in Asia (ITC-Asia), 2026 IEEE International, 1. https://doi.org/10.1109/ITC-Asia71864.2026.11710833

Chicago Style (17th ed.) Citation

Zhou, Ziyu, Pengjun Wang, Gang Li, Yuejun Zhang, Zhenkai Zhou, and Zhen Fang. "Additivity Testing Method for the Capability of Strong PUF to Resist Machine Learning Attacks Under Hybrid Obfuscation Algorithms Protection." 2026 IEEE International Test Conference in Asia (ITC-Asia), Test Conference in Asia (ITC-Asia), 2026 IEEE International 2026: 1. https://doi.org/10.1109/ITC-Asia71864.2026.11710833.

MLA (9th ed.) Citation

Zhou, Ziyu, et al. "Additivity Testing Method for the Capability of Strong PUF to Resist Machine Learning Attacks Under Hybrid Obfuscation Algorithms Protection." 2026 IEEE International Test Conference in Asia (ITC-Asia), Test Conference in Asia (ITC-Asia), 2026 IEEE International, 2026, p. 1, https://doi.org/10.1109/ITC-Asia71864.2026.11710833.