{"id":"https://openalex.org/W7165195599","doi":"https://doi.org/10.1145/3787109.3815243","title":"SRAM DNA: Spatial Signatures in Power-Up States for Memory Family Identification","display_name":"SRAM DNA: Spatial Signatures in Power-Up States for Memory Family Identification","publication_year":2026,"publication_date":"2026-06-18","ids":{"openalex":"https://openalex.org/W7165195599","doi":"https://doi.org/10.1145/3787109.3815243"},"language":null,"primary_location":{"id":"doi:10.1145/3787109.3815243","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3787109.3815243","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Great Lakes Symposium on VLSI 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3787109.3815243","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5122130422","display_name":"Sayan Samanta","orcid":null},"institutions":[{"id":"https://openalex.org/I82495205","display_name":"University of Alabama in Huntsville","ror":"https://ror.org/02zsxwr40","country_code":"US","type":"education","lineage":["https://openalex.org/I82495205"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sayan Samanta","raw_affiliation_strings":["The University of Alabama in Huntsville, Huntsville, AL, USA"],"raw_orcid":"https://orcid.org/0009-0004-4561-0803","affiliations":[{"raw_affiliation_string":"The University of Alabama in Huntsville, Huntsville, AL, USA","institution_ids":["https://openalex.org/I82495205"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083246460","display_name":"Biswajit Ray","orcid":"https://orcid.org/0000-0002-5890-1368"},"institutions":[{"id":"https://openalex.org/I92446798","display_name":"Colorado State University","ror":"https://ror.org/03k1gpj17","country_code":"US","type":"education","lineage":["https://openalex.org/I92446798"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Biswajit Ray","raw_affiliation_strings":["Colorado State University, Fort Collins, CO, USA"],"raw_orcid":"https://orcid.org/0000-0002-5890-1368","affiliations":[{"raw_affiliation_string":"Colorado State University, Fort Collins, CO, USA","institution_ids":["https://openalex.org/I92446798"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083066313","display_name":"Aleksandar Milenkovi\u0107","orcid":"https://orcid.org/0000-0002-9359-4594"},"institutions":[{"id":"https://openalex.org/I82495205","display_name":"University of Alabama in Huntsville","ror":"https://ror.org/02zsxwr40","country_code":"US","type":"education","lineage":["https://openalex.org/I82495205"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aleksandar Milenkovic","raw_affiliation_strings":["The University of Alabama in Huntsville, Huntsville, AL, USA"],"raw_orcid":"https://orcid.org/0000-0002-9359-4594","affiliations":[{"raw_affiliation_string":"The University of Alabama in Huntsville, Huntsville, AL, USA","institution_ids":["https://openalex.org/I82495205"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.72595937,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"701","last_page":"708"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/static-random-access-memory","display_name":"Static random-access memory","score":0.8812000155448914},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5350000262260437},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4765999913215637},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4375999867916107},{"id":"https://openalex.org/keywords/random-access-memory","display_name":"Random access memory","score":0.42500001192092896},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4205999970436096},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4198000133037567}],"concepts":[{"id":"https://openalex.org/C68043766","wikidata":"https://www.wikidata.org/wiki/Q267416","display_name":"Static random-access memory","level":2,"score":0.8812000155448914},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5934000015258789},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5350000262260437},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4765999913215637},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44940000772476196},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4375999867916107},{"id":"https://openalex.org/C2994168587","wikidata":"https://www.wikidata.org/wiki/Q5295","display_name":"Random access memory","level":2,"score":0.42500001192092896},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4205999970436096},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4198000133037567},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.37400001287460327},{"id":"https://openalex.org/C530198007","wikidata":"https://www.wikidata.org/wiki/Q80831","display_name":"Integrated circuit","level":2,"score":0.36570000648498535},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3467999994754791},{"id":"https://openalex.org/C134146338","wikidata":"https://www.wikidata.org/wiki/Q1815901","display_name":"Electronic circuit","level":2,"score":0.3034999966621399},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.28299999237060547},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2768999934196472},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.272599995136261},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3787109.3815243","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3787109.3815243","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Great Lakes Symposium on VLSI 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3787109.3815243","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3787109.3815243","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Great Lakes Symposium on VLSI 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2099101940","https://openalex.org/W2110065044","https://openalex.org/W2113322447","https://openalex.org/W2144854846","https://openalex.org/W2539143073","https://openalex.org/W2587887865","https://openalex.org/W2775903597","https://openalex.org/W2904233109","https://openalex.org/W2911964244","https://openalex.org/W3185810800","https://openalex.org/W4255747608","https://openalex.org/W4387414969","https://openalex.org/W4399120099","https://openalex.org/W4402835364","https://openalex.org/W4405440300","https://openalex.org/W4412082658","https://openalex.org/W7092204173"],"related_works":[],"abstract_inverted_index":{"Ensuring":[0],"the":[1,80],"authenticity":[2],"of":[3,79],"integrated":[4],"circuits":[5],"in":[6,30],"complex":[7],"semiconductor":[8],"supply":[9],"chains":[10],"requires":[11],"noninvasive":[12],"methods":[13],"for":[14],"identifying":[15],"device":[16],"provenance.":[17],"This":[18],"work":[19,32],"investigates":[20],"whether":[21],"SRAM":[22,34,52,138],"power-up":[23,61,67,130,139],"states":[24,140],"contain":[25],"structural":[26],"signatures,":[27],"referred":[28],"to":[29,123],"this":[31],"as":[33],"DNA,":[35],"that":[36,137],"distinguish":[37],"memory":[38,82],"families":[39,53],"beyond":[40],"traditional":[41],"device-unique":[42],"Physical":[43],"Unclonable":[44],"Functions":[45],"(PUFs).":[46],"We":[47],"analyze":[48],"eight":[49],"commercial":[50],"4-Mbit":[51],"(15":[54],"chips":[55],"per":[56,132],"family)":[57],"and":[58,99,117,149],"collect":[59],"multiple":[60],"measurements":[62,131],"from":[63],"each":[64],"device.":[65],"Each":[66],"state":[68],"is":[69],"reshaped":[70],"into":[71],"a":[72,128],"2048\u00d72048":[73],"binary":[74],"grid,":[75],"enabling":[76],"spatial":[77,95,144],"analysis":[78],"full":[81],"array.":[83],"From":[84],"these":[85],"grids":[86],"we":[87],"extract":[88],"interpretable":[89],"multi-scale":[90],"descriptors":[91],"capturing":[92],"global":[93],"bias,":[94],"periodicity,":[96],"texture":[97],"statistics,":[98],"directional":[100],"anisotropy.":[101],"A":[102],"Random":[103],"Forest":[104],"classifier":[105],"evaluated":[106],"under":[107],"chip-level":[108],"holdout":[109],"validation":[110],"(Leave-M-Chips-Per-Family)":[111],"achieves":[112],"more":[113],"than":[114],"99.5%":[115],"accuracy":[116],"macro-F1":[118],"score,":[119],"demonstrating":[120],"strong":[121],"generalization":[122],"unseen":[124],"devices":[125],"with":[126],"only":[127],"few":[129],"chip.":[133],"These":[134],"results":[135],"show":[136],"encode":[141],"reproducible":[142],"family-level":[143],"organization":[145],"reflecting":[146],"memory-array":[147],"structure":[148],"manufacturing":[150],"characteristics.":[151]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-06-19T00:00:00"}
