Εμφάνιση απλής εγγραφής

dc.creatorLiakos K.G., Plessas F.C.en
dc.date.accessioned2023-01-31T08:50:22Z
dc.date.available2023-01-31T08:50:22Z
dc.date.issued2022
dc.identifier10.1109/PACET56979.2022.9976350
dc.identifier.isbn9798350399585
dc.identifier.urihttp://hdl.handle.net/11615/75817
dc.description.abstractHardware Trojan (HT) consists a chip-level viruses which aim to leak encrypted information or degrade the performance of the infected device. They are a modification to the original design of a circuit and consist of two components, trigger, and payload. The trigger is the mechanism that calls the payload under rare conditions. The payload mechanism is responsible for the type of attack the infected circuit will receive. HTs can be inserted into any phase of the Application-Specific Integrated Circuits (ASICs) production chain. They can stay stealthy and be undetected. HTs viruses are a crucial issue in the field of electronics, with the potential to become an outbreak in the next years. A major problem is that, at the academic and research level, there is a general lack of data, a lack of uninfected benchmark circuits, a lack of the small type of uninfected and infected circuits, and a large imbalance in the amount of data between uninfected and infected circuits. We used and designed these limited benchmark circuits for the Gate Level Netlist (GLN) phase with a professional tool and extracted area, power, and time analysis features. Through these features, we created a synthetic data creation tool known as GAINESIS through which we created our CAS-HtBase. CAS-HtBase aims to provide the researchers with a new HT database based on GLN analysis exclusively for ASICs. The format of CAS-HtBase allows the development of Machine Learning (ML) models without conversions to the database. © 2022 IEEE.en
dc.language.isoenen
dc.source2022 Panhellenic Conference on Electronics and Telecommunications, PACET 2022en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85145656457&doi=10.1109%2fPACET56979.2022.9976350&partnerID=40&md5=d789508b8617ae791840c6b5799f4a73
dc.subjectApplication specific integrated circuitsen
dc.subjectElectric network analysisen
dc.subjectHardware securityen
dc.subjectMachine learningen
dc.subjectMalwareen
dc.subjectSiliconen
dc.subjectTiming circuitsen
dc.subjectVirusesen
dc.subjectApplication-specific integrated circuitsen
dc.subjectBenchmark circuiten
dc.subjectChip-levelen
dc.subjectEncrypted informationsen
dc.subjectGate levelsen
dc.subjectGate-level netlisten
dc.subjectMachine learning modelsen
dc.subjectNetlisten
dc.subjectOriginal designen
dc.subjectPerformanceen
dc.subjectDatabase systemsen
dc.subjectInstitute of Electrical and Electronics Engineers Inc.en
dc.titleCAS-HtBase: a new database for the study of HTs at the pre-silicon stage of ASICsen
dc.typeconferenceItemen


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