V. Parmar, Sandeep Kaur Kingra, Deepak Verma, Digamber Pandey, G. Piccolboni, A. Bricalli, A. Regev, G. Pares, L. Grenouillet, J. Nodin, M. Suri
{"title":"Demonstration of SMT-reflow Immune and SCA-resilient PUF on 28nm RRAM device array","authors":"V. Parmar, Sandeep Kaur Kingra, Deepak Verma, Digamber Pandey, G. Piccolboni, A. Bricalli, A. Regev, G. Pares, L. Grenouillet, J. Nodin, M. Suri","doi":"10.1109/IMW56887.2023.10145993","DOIUrl":null,"url":null,"abstract":"We demonstrate 16kB RRAM PUF (Physically Un-clonable Function) arrays with excellent immunity to hightemperature SMT (surface mount technology) -reflow process and resilience against modern Machine-Learning (ML) based sidechannel attacks (SCA). Robust PUF operation is experimentally demonstrated on two optimized 2T-2R CMOS-RRAM designs (28 nm and 130 nm). We exploit forming voltage variability coupled with a dedicated novel programming scheme to extract unique PUF signatures. Fabricated arrays exhibit excellent performance in terms of speed, data retention and memory window. Extracted PUF signatures satisfy NIST (800-90B) tests showing extremely narrow distribution for hamming weight across multiple dies. Resilience against modern ML-SCA is achieved by introducing a secondary low energy HRS (high-resistance state) programming step and RRAM device stack-engineering. Proposed work is one of the first demonstrations for SMT-reflow immunity in context of PUF designs highlighting the high tolerance of the PUF signature to temperatures as high as 200 °C.","PeriodicalId":153429,"journal":{"name":"2023 IEEE International Memory Workshop (IMW)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Memory Workshop (IMW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMW56887.2023.10145993","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We demonstrate 16kB RRAM PUF (Physically Un-clonable Function) arrays with excellent immunity to hightemperature SMT (surface mount technology) -reflow process and resilience against modern Machine-Learning (ML) based sidechannel attacks (SCA). Robust PUF operation is experimentally demonstrated on two optimized 2T-2R CMOS-RRAM designs (28 nm and 130 nm). We exploit forming voltage variability coupled with a dedicated novel programming scheme to extract unique PUF signatures. Fabricated arrays exhibit excellent performance in terms of speed, data retention and memory window. Extracted PUF signatures satisfy NIST (800-90B) tests showing extremely narrow distribution for hamming weight across multiple dies. Resilience against modern ML-SCA is achieved by introducing a secondary low energy HRS (high-resistance state) programming step and RRAM device stack-engineering. Proposed work is one of the first demonstrations for SMT-reflow immunity in context of PUF designs highlighting the high tolerance of the PUF signature to temperatures as high as 200 °C.