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Addressing Integrated Circuit Integrity Using Statistical Analysis and Machine Learning Techniques
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| 자료유형 | E-Book |
|---|---|
| 개인저자 | Cakir, Burcin. |
| 단체저자명 | Princeton University. Electrical Engineering. |
| 서명/저자사항 | Addressing Integrated Circuit Integrity Using Statistical Analysis and Machine Learning Techniques. |
| 발행사항 | [S.l.] : Princeton University., 2018 |
| 발행사항 | Ann Arbor : ProQuest Dissertations & Theses, 2018 |
| 형태사항 | 114 p. |
| 소장본 주기 | School code: 0181. |
| ISBN | 9780438050280 |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
Adviser: Sharad Malik. |
| 요약 | Outsourcing of design and manufacturing processes makes integrated circuits (ICs) vulnerable to adversarial changes and raises concerns about their security and integrity. The difference in the levels of abstraction between the initial specifica |
| 요약 | In this thesis, we present a novel approach for the analysis of circuits using graph algorithms and different concepts from linear algebra, signal processing and machine learning techniques to detect malicious insertions and reverse engineer a g |
| 요약 | All algorithms have been implemented and demonstrated to be scalable to significant sized ICs. They present valuable insights for reverse engineering digital ICs as well as for Trojan detection. |
| 일반주제명 | Electrical engineering. |
| 언어 | 영어 |
| 기본자료 저록 | Dissertation Abstracts International79-10B(E). Dissertation Abstract International |
| 대출바로가기 | http://www.riss.kr/pdu/ddodLink.do?id=T14998623 |
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| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00024191 | 621.3 | 가야대학교// | 대출가능 |
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