{"title":"不受信任的第三方数字IP核:在高级合成过程中硬件木马安全数据路径的功率延迟权衡驱动探索","authors":"A. Sengupta, Saumya Bhadauria","doi":"10.1145/2742060.2742061","DOIUrl":null,"url":null,"abstract":"An evolutionary algorithm (EA) driven novel design space exploration (DSE) of an optimized hardware Trojan secured datapath based on user power-delay constraint during high level synthesis (HLS) is presented. The focus on hardware Trojan secured datapath generation during HLS has been very little with absolutely zero effort so far in design space exploration of a user multi-objective (MO) constraint optimized hardware Trojan secured datapath. This problem mandates attention as producing a Trojan secured datapath is not inconsequential. Merely the detection process of Trojan is not as straightforward as concurrent error detection (CED) of transient faults as it involves the concept of multiple third party intellectual property (3PIP) vendors to facilitate detection, let aside the exploration process of a user optimized Trojan secured datapath based on MO constraints. The proposed DSE for hardware Trojan detection includes novel problem encoding technique that enables exploration of efficient distinct vendor allocation as well as enables exploration of an optimized Trojan secured datapath structure. The exploration backbone for the proposed approach is bacterial foraging optimization algorithm (BFOA) which is known for its adaptive feature (tumbling/swimming) and simplified model. Results of comparison with recent approach indicated an average improvement in quality of results (QoR) of >14.1%","PeriodicalId":255133,"journal":{"name":"Proceedings of the 25th edition on Great Lakes Symposium on VLSI","volume":"90 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Untrusted Third Party Digital IP Cores: Power-Delay Trade-off Driven Exploration of Hardware Trojan Secured Datapath during High Level Synthesis\",\"authors\":\"A. Sengupta, Saumya Bhadauria\",\"doi\":\"10.1145/2742060.2742061\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An evolutionary algorithm (EA) driven novel design space exploration (DSE) of an optimized hardware Trojan secured datapath based on user power-delay constraint during high level synthesis (HLS) is presented. The focus on hardware Trojan secured datapath generation during HLS has been very little with absolutely zero effort so far in design space exploration of a user multi-objective (MO) constraint optimized hardware Trojan secured datapath. This problem mandates attention as producing a Trojan secured datapath is not inconsequential. Merely the detection process of Trojan is not as straightforward as concurrent error detection (CED) of transient faults as it involves the concept of multiple third party intellectual property (3PIP) vendors to facilitate detection, let aside the exploration process of a user optimized Trojan secured datapath based on MO constraints. The proposed DSE for hardware Trojan detection includes novel problem encoding technique that enables exploration of efficient distinct vendor allocation as well as enables exploration of an optimized Trojan secured datapath structure. The exploration backbone for the proposed approach is bacterial foraging optimization algorithm (BFOA) which is known for its adaptive feature (tumbling/swimming) and simplified model. Results of comparison with recent approach indicated an average improvement in quality of results (QoR) of >14.1%\",\"PeriodicalId\":255133,\"journal\":{\"name\":\"Proceedings of the 25th edition on Great Lakes Symposium on VLSI\",\"volume\":\"90 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 25th edition on Great Lakes Symposium on VLSI\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2742060.2742061\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 25th edition on Great Lakes Symposium on VLSI","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2742060.2742061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Untrusted Third Party Digital IP Cores: Power-Delay Trade-off Driven Exploration of Hardware Trojan Secured Datapath during High Level Synthesis
An evolutionary algorithm (EA) driven novel design space exploration (DSE) of an optimized hardware Trojan secured datapath based on user power-delay constraint during high level synthesis (HLS) is presented. The focus on hardware Trojan secured datapath generation during HLS has been very little with absolutely zero effort so far in design space exploration of a user multi-objective (MO) constraint optimized hardware Trojan secured datapath. This problem mandates attention as producing a Trojan secured datapath is not inconsequential. Merely the detection process of Trojan is not as straightforward as concurrent error detection (CED) of transient faults as it involves the concept of multiple third party intellectual property (3PIP) vendors to facilitate detection, let aside the exploration process of a user optimized Trojan secured datapath based on MO constraints. The proposed DSE for hardware Trojan detection includes novel problem encoding technique that enables exploration of efficient distinct vendor allocation as well as enables exploration of an optimized Trojan secured datapath structure. The exploration backbone for the proposed approach is bacterial foraging optimization algorithm (BFOA) which is known for its adaptive feature (tumbling/swimming) and simplified model. Results of comparison with recent approach indicated an average improvement in quality of results (QoR) of >14.1%