Summary
Over the recent years, the explosive growth of digital technologies allowed to implement disruptive business models driven by data collection and processing. In particular, the internet of things (IoT) opens unprecedented opportunities for consumers (smart society), organisations/companies (industry 4.0/ smart factories) and governments (smart nations). However, as every adoption of new technologies involves some risks, security attacks are amongst the most severe challenges for IoT: only in 2021, the inflicted damages have been valued $6 trillion globally and 1,097 organizations were hit by ransomware attacks. Secure IoT is generally enabled by the physical unclonable function (PUF), namely a hardware function which is embedded in the chip and capable of generating a random, unique response to a given challenge. Improvements in attack methods over the years have recently moved the field of PUFs from the conventional, silicon-based CMOS technology, toward emerging non-volatile memories (NVMs). The latter allows for high density, low cost, highly scalable PUF with the capability of reconfiguration. Currently a truly tamper-resistant and reliable weak PUF leveraging stochastic switching of NVMs for secure IoT is still missing and highly requested by the market. Within the ERC-COG project RESCUE (2015-2020), a novel method for true random number generation (TRNG) based on NVMs was developed and patented. The TRNG scheme allows for iPUF (invisible PUF), namely a digital, highly reliable PUF, which is 100% robust to physical attacks. Within the SHANNON project, we will address the technical and commercial feasibility of iPUF, validating the concept with industry grade embedded NVMs and elevating its technology readiness level via experimental tests and simulations. New architecture and algorithms will be developed to strengthen the IP position of iPUF as a scalable security primitive for IoT systems.
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Web resources: | https://cordis.europa.eu/project/id/101069299 |
Start date: | 01-11-2022 |
End date: | 30-04-2024 |
Total budget - Public funding: | - 150 000,00 Euro |
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Original description
Over the recent years, the explosive growth of digital technologies allowed to implement disruptive business models driven by data collection and processing. In particular, the internet of things (IoT) opens unprecedented opportunities for consumers (smart society), organisations/companies (industry 4.0/ smart factories) and governments (smart nations). However, as every adoption of new technologies involves some risks, security attacks are amongst the most severe challenges for IoT: only in 2021, the inflicted damages have been valued $6 trillion globally and 1,097 organizations were hit by ransomware attacks. Secure IoT is generally enabled by the physical unclonable function (PUF), namely a hardware function which is embedded in the chip and capable of generating a random, unique response to a given challenge. Improvements in attack methods over the years have recently moved the field of PUFs from the conventional, silicon-based CMOS technology, toward emerging non-volatile memories (NVMs). The latter allows for high density, low cost, highly scalable PUF with the capability of reconfiguration. Currently a truly tamper-resistant and reliable weak PUF leveraging stochastic switching of NVMs for secure IoT is still missing and highly requested by the market. Within the ERC-COG project RESCUE (2015-2020), a novel method for true random number generation (TRNG) based on NVMs was developed and patented. The TRNG scheme allows for iPUF (invisible PUF), namely a digital, highly reliable PUF, which is 100% robust to physical attacks. Within the SHANNON project, we will address the technical and commercial feasibility of iPUF, validating the concept with industry grade embedded NVMs and elevating its technology readiness level via experimental tests and simulations. New architecture and algorithms will be developed to strengthen the IP position of iPUF as a scalable security primitive for IoT systems.Status
SIGNEDCall topic
ERC-2022-POC1Update Date
09-02-2023
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