A Modelling Attack Resistant Low Overhead Memristive Physical Unclonable Function

Memristors are finding applications in memory, logic, neuromorphic systems, and data security. To this end, we leverage the non-linear behaviour of memristors to devise a low overhead physical unclonable function using a memristive chaos circuit in conjunction with a non-linear memristive encoder. W...

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Published in2020 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT) pp. 1 - 4
Main Authors Yang, Xiaohan, Khandelwal, Saurabh, Jiang, Aiqi, Jabir, Abusaleh
Format Conference Proceeding
LanguageEnglish
Published IEEE 19.10.2020
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ISSN2377-7966
DOI10.1109/DFT50435.2020.9250762

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Abstract Memristors are finding applications in memory, logic, neuromorphic systems, and data security. To this end, we leverage the non-linear behaviour of memristors to devise a low overhead physical unclonable function using a memristive chaos circuit in conjunction with a non-linear memristive encoder. We demonstrate the effectiveness of this architecture in Challenge-Response-Pair based authentication, and for its physical uncloneability. This architecture is highly versatile and can be implemented with a single encoder or a number of encoders running in parallel, each one with its own merit, for extending the sizes of CRPs. To demonstrate its effectiveness, we subject the architecture to machine learning based modelling attacks e.g. Logistic Regression, Support Vector Machines, Random Forest, as well as Artificial Neural Network classifiers. We found out that the proposed PUF architecture provides better resistance to such attacks, even for smaller bit sizes and at reduced overheads.
AbstractList Memristors are finding applications in memory, logic, neuromorphic systems, and data security. To this end, we leverage the non-linear behaviour of memristors to devise a low overhead physical unclonable function using a memristive chaos circuit in conjunction with a non-linear memristive encoder. We demonstrate the effectiveness of this architecture in Challenge-Response-Pair based authentication, and for its physical uncloneability. This architecture is highly versatile and can be implemented with a single encoder or a number of encoders running in parallel, each one with its own merit, for extending the sizes of CRPs. To demonstrate its effectiveness, we subject the architecture to machine learning based modelling attacks e.g. Logistic Regression, Support Vector Machines, Random Forest, as well as Artificial Neural Network classifiers. We found out that the proposed PUF architecture provides better resistance to such attacks, even for smaller bit sizes and at reduced overheads.
Author Khandelwal, Saurabh
Yang, Xiaohan
Jiang, Aiqi
Jabir, Abusaleh
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Snippet Memristors are finding applications in memory, logic, neuromorphic systems, and data security. To this end, we leverage the non-linear behaviour of memristors...
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SubjectTerms Authentication
Chaos
Hardware
Manganese
Memristors
Physical unclonable function
Resistance
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Title A Modelling Attack Resistant Low Overhead Memristive Physical Unclonable Function
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