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Additivity Testing Method for the Capability of Strong PUF to Resist Machine Learning Attacks Under Hybrid Obfuscation Algorithms Protection

Bibliographic Details
Title: Additivity Testing Method for the Capability of Strong PUF to Resist Machine Learning Attacks Under Hybrid Obfuscation Algorithms Protection
Authors: Zhou, Ziyu, Wang, Pengjun, Li, Gang, Zhang, Yuejun, Zhou, Zhenkai, Fang, Zhen
Source: 2026 IEEE International Test Conference in Asia (ITC-Asia) Test Conference in Asia (ITC-Asia), 2026 IEEE International. :1-6 Aug, 2026
Relation: 2026 IEEE International Test Conference in Asia (ITC-Asia)
Database: IEEE Xplore Digital Library
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DbLabel: IEEE Xplore Digital Library
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PubType: Conference
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  Data: Additivity Testing Method for the Capability of Strong PUF to Resist Machine Learning Attacks Under Hybrid Obfuscation Algorithms Protection
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  Data: 2026 IEEE International Test Conference in Asia (ITC-Asia) Test Conference in Asia (ITC-Asia), 2026 IEEE International. :1-6 Aug, 2026
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  Data: 2026 IEEE International Test Conference in Asia (ITC-Asia)
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RecordInfo BibRecord:
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        Value: 10.1109/ITC-Asia71864.2026.11710833
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        PageCount: 6
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      – TitleFull: Additivity Testing Method for the Capability of Strong PUF to Resist Machine Learning Attacks Under Hybrid Obfuscation Algorithms Protection
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          Name:
            NameFull: Zhou, Ziyu
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          Name:
            NameFull: Wang, Pengjun
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            NameFull: Li, Gang
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            NameFull: Zhang, Yuejun
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            NameFull: Zhou, Zhenkai
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            NameFull: Fang, Zhen
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              M: 08
              Type: published
              Y: 2026
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            – TitleFull: 2026 IEEE International Test Conference in Asia (ITC-Asia), Test Conference in Asia (ITC-Asia), 2026 IEEE International
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