Summary
Intrinsic-ID is a Dutch SME, spin-off from Philips Research, and a world leader in security solutions for chips, with 25+ patents. Intrinsic-ID has created a technology to uniquely identify and authenticate chips based on the inherent characteristics of their memory component (SRAM). This technology, a digital equivalent of a fingerprint, is called Physical Unclonable Function (PUF).
Intrinsic-ID is working on INSTET – a fully-fledged security solution on top of PUF that will protect low-end chips that are omnipresent in IoT devices everywhere by making them physically and cryptographically secure and extremely resilient to advanced attacks. INSTET will work as a Root of Trust, i.e. a set of core software components that are always trusted by the chip, and provide a trust foundation for the IoT device and distributed IoT systems.
INSTET addresses the core problem of semiconductor vendors and OEMs: lack of security. INSTET can be deployed on almost any chip, including the ones that are already in the field, without costly redesigns or additional hardware, generating savings of up to 35% per chip.
In this 6-month feasibility study, Intrinsic-ID will investigate the product/market fit and business model fit in three most promising vertical segments of the semiconductor industry (wearables, medical electronics and automotive), develop a go-to-market strategy and calculate costs of scaling up.
Intrinsic-ID is working on INSTET – a fully-fledged security solution on top of PUF that will protect low-end chips that are omnipresent in IoT devices everywhere by making them physically and cryptographically secure and extremely resilient to advanced attacks. INSTET will work as a Root of Trust, i.e. a set of core software components that are always trusted by the chip, and provide a trust foundation for the IoT device and distributed IoT systems.
INSTET addresses the core problem of semiconductor vendors and OEMs: lack of security. INSTET can be deployed on almost any chip, including the ones that are already in the field, without costly redesigns or additional hardware, generating savings of up to 35% per chip.
In this 6-month feasibility study, Intrinsic-ID will investigate the product/market fit and business model fit in three most promising vertical segments of the semiconductor industry (wearables, medical electronics and automotive), develop a go-to-market strategy and calculate costs of scaling up.
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More information & hyperlinks
Web resources: | https://cordis.europa.eu/project/id/744484 |
Start date: | 01-10-2016 |
End date: | 31-03-2017 |
Total budget - Public funding: | 71 429,00 Euro - 50 000,00 Euro |
Cordis data
Original description
Intrinsic-ID is a Dutch SME, spin-off from Philips Research, and a world leader in security solutions for chips, with 25+ patents. Intrinsic-ID has created a technology to uniquely identify and authenticate chips based on the inherent characteristics of their memory component (SRAM). This technology, a digital equivalent of a fingerprint, is called Physical Unclonable Function (PUF).Intrinsic-ID is working on INSTET – a fully-fledged security solution on top of PUF that will protect low-end chips that are omnipresent in IoT devices everywhere by making them physically and cryptographically secure and extremely resilient to advanced attacks. INSTET will work as a Root of Trust, i.e. a set of core software components that are always trusted by the chip, and provide a trust foundation for the IoT device and distributed IoT systems.
INSTET addresses the core problem of semiconductor vendors and OEMs: lack of security. INSTET can be deployed on almost any chip, including the ones that are already in the field, without costly redesigns or additional hardware, generating savings of up to 35% per chip.
In this 6-month feasibility study, Intrinsic-ID will investigate the product/market fit and business model fit in three most promising vertical segments of the semiconductor industry (wearables, medical electronics and automotive), develop a go-to-market strategy and calculate costs of scaling up.
Status
CLOSEDCall topic
SMEInst-13-2016-2017Update Date
27-10-2022
Geographical location(s)
Structured mapping
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