Pub Date : 2019-07-01DOI: 10.1109/IVSW.2019.8854394
N. Du, M. Kiani, Xianyue Zhao, D. Bürger, O. Schmidt, R. Ecke, S. Schulz, H. Schmidt, I. Polian
Emerging memristive devices have been recently suggested for use in secret key generation and other hardware security applications. This position paper brings together the views of researchers from material science and hardware-oriented security. It discusses the question which types of memristors are better suitable for the construction of major hardware security primitives. Specifically, this paper points out the problems caused by electroforming, a necessary step for most of today's memristive devices, and advocates the usage of electroforming-free memristors. It discusses which security properties can be met by such devices and where more research is required.
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Pub Date : 2019-07-01DOI: 10.1109/IVSW.2019.8854455
Batya Karp, O. Amrani, O. Keren
Multi-dimensional codes using a coset based code as one of the base codes have been suggested to increase the code distance and at the same time simplify the encoding and decoding of long codes. We show that while these codes provide sufficient reliability, they can not provide security. We then present two-dimensional product codes using robust codes as the base codes which provide both reliability and security.
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Pub Date : 2019-07-01DOI: 10.1109/IVSW.2019.8854417
D. Fellner
Over the last fifteen years, hardware security and trust has evolved into a major new area of research at the intersection of semiconductor manufacturing, VLSI design and test, computer-aided design, architecture and system security. During the same period, machine learning has experience a major revival in interest and has flourished from a nearly forgotten area to the talk of the town. In this presentation, we will first briefly review various machine learning-based solutions which have been developed to address a number of concerns in hardware security and trust, including hardware Trojan detection, counterfeit IC identification, provenance attestation, hardware-based malware detection, side-channel attacks, PUF modeling, etc. Then, we will examine the key attributes of these problems which make them amenable to machine learning-based solutions and we will discuss the potential and the fundamental limitations of such approaches. Lastly, we will ponder the role of and necessity for advanced contemporary machine learning methods in the context of hardware security and we will conclude with suggestions for avoiding common pitfalls when employing such methods.
{"title":"Keynotes","authors":"D. Fellner","doi":"10.1109/IVSW.2019.8854417","DOIUrl":"https://doi.org/10.1109/IVSW.2019.8854417","url":null,"abstract":"Over the last fifteen years, hardware security and trust has evolved into a major new area of research at the intersection of semiconductor manufacturing, VLSI design and test, computer-aided design, architecture and system security. During the same period, machine learning has experience a major revival in interest and has flourished from a nearly forgotten area to the talk of the town. In this presentation, we will first briefly review various machine learning-based solutions which have been developed to address a number of concerns in hardware security and trust, including hardware Trojan detection, counterfeit IC identification, provenance attestation, hardware-based malware detection, side-channel attacks, PUF modeling, etc. Then, we will examine the key attributes of these problems which make them amenable to machine learning-based solutions and we will discuss the potential and the fundamental limitations of such approaches. Lastly, we will ponder the role of and necessity for advanced contemporary machine learning methods in the context of hardware security and we will conclude with suggestions for avoiding common pitfalls when employing such methods.","PeriodicalId":213848,"journal":{"name":"2019 IEEE 4th International Verification and Security Workshop (IVSW)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128403626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ivsw.2019.8854382
2019 IEEE 4th International Verification and Security Workshop (IVSW 2019)
2019 IEEE第四届国际验证与安全研讨会(IVSW 2019)
{"title":"2019 IEEE 4th International Verification and Security Workshop (IVSW 2019)","authors":"","doi":"10.1109/ivsw.2019.8854382","DOIUrl":"https://doi.org/10.1109/ivsw.2019.8854382","url":null,"abstract":"2019 IEEE 4<sup>th</sup> International Verification and Security Workshop (IVSW 2019)","PeriodicalId":213848,"journal":{"name":"2019 IEEE 4th International Verification and Security Workshop (IVSW)","volume":"34 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123144862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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