Matthias Ludwig, A. Bette, Bernhard Lippmann, G. Sigl
{"title":"半导体制程技术检测的防伪方法","authors":"Matthias Ludwig, A. Bette, Bernhard Lippmann, G. Sigl","doi":"10.1109/ETS56758.2023.10174131","DOIUrl":null,"url":null,"abstract":"With world-wide distributed semiconductor supply chains and a scarcity of microelectronic products, counterfeit devices are gaining momentum. Sourcing products from trusted providers are the theoretical remedy, yet practice shows the reality. Forged electronics are entering the supply chain at a high rate and pose a threat to safety, reliability, and security. Academia and industry have established various pre- or post-production measures to effectively address this issue partially. Yet, several inadequately covered aspects of the field require improvements. First, this work introduces a rating scheme to enable the effective comparison between anti-counterfeiting methods. Recently published methods are compared using this scheme. Second, a novel, generic, generally applicable prover-verifier attestation framework for post-production anti-counterfeiting methods is established. Third, the work implements a new anti-counterfeit method. By introducing technological individual features, the method incorporates technology intrinsic features of the front-end semiconductor manufacturing process as technology distinctive characteristic. Profile parameters are extracted through pattern recognition and statistical methods which are compared to the expected technologies through distance metrics, allowing an assertion of device authenticity. Finally, the versatility of the method is experimentally validated through real samples. Overall, an accuracy of 100% is reported for seven samples which are checked for authenticity.","PeriodicalId":211522,"journal":{"name":"2023 IEEE European Test Symposium (ETS)","volume":"260 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Counterfeit Detection by Semiconductor Process Technology Inspection\",\"authors\":\"Matthias Ludwig, A. Bette, Bernhard Lippmann, G. Sigl\",\"doi\":\"10.1109/ETS56758.2023.10174131\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With world-wide distributed semiconductor supply chains and a scarcity of microelectronic products, counterfeit devices are gaining momentum. Sourcing products from trusted providers are the theoretical remedy, yet practice shows the reality. Forged electronics are entering the supply chain at a high rate and pose a threat to safety, reliability, and security. Academia and industry have established various pre- or post-production measures to effectively address this issue partially. Yet, several inadequately covered aspects of the field require improvements. First, this work introduces a rating scheme to enable the effective comparison between anti-counterfeiting methods. Recently published methods are compared using this scheme. Second, a novel, generic, generally applicable prover-verifier attestation framework for post-production anti-counterfeiting methods is established. Third, the work implements a new anti-counterfeit method. By introducing technological individual features, the method incorporates technology intrinsic features of the front-end semiconductor manufacturing process as technology distinctive characteristic. Profile parameters are extracted through pattern recognition and statistical methods which are compared to the expected technologies through distance metrics, allowing an assertion of device authenticity. Finally, the versatility of the method is experimentally validated through real samples. Overall, an accuracy of 100% is reported for seven samples which are checked for authenticity.\",\"PeriodicalId\":211522,\"journal\":{\"name\":\"2023 IEEE European Test Symposium (ETS)\",\"volume\":\"260 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE European Test Symposium (ETS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ETS56758.2023.10174131\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE European Test Symposium (ETS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETS56758.2023.10174131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Counterfeit Detection by Semiconductor Process Technology Inspection
With world-wide distributed semiconductor supply chains and a scarcity of microelectronic products, counterfeit devices are gaining momentum. Sourcing products from trusted providers are the theoretical remedy, yet practice shows the reality. Forged electronics are entering the supply chain at a high rate and pose a threat to safety, reliability, and security. Academia and industry have established various pre- or post-production measures to effectively address this issue partially. Yet, several inadequately covered aspects of the field require improvements. First, this work introduces a rating scheme to enable the effective comparison between anti-counterfeiting methods. Recently published methods are compared using this scheme. Second, a novel, generic, generally applicable prover-verifier attestation framework for post-production anti-counterfeiting methods is established. Third, the work implements a new anti-counterfeit method. By introducing technological individual features, the method incorporates technology intrinsic features of the front-end semiconductor manufacturing process as technology distinctive characteristic. Profile parameters are extracted through pattern recognition and statistical methods which are compared to the expected technologies through distance metrics, allowing an assertion of device authenticity. Finally, the versatility of the method is experimentally validated through real samples. Overall, an accuracy of 100% is reported for seven samples which are checked for authenticity.