Post Quantum Cryptographic Keys Generated with Physical Unclonable Functions

Cambou, Bertrand; Gowanlock, Michael; Yıldız, Bahattin; Ghanaimiandoab, Dina; Lee, Kaitlyn; Nelson, Stefan; Philabaum, Christopher; A, Stenberg; Wright, Jordan

doi:10.3390/app11062801

Cited by 12 publications

(11 citation statements)

References 8 publications

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“…These random numbers are used as symmetric encryption keys that are encapsulated by the more deterministic PUF responses. [17]…”

Section: Use Of Pufs and Enrollmentmentioning

confidence: 99%

“…Only a server that has knowledge of the expected value of the response from the PUF, is capable of guessing the actual response from the PUF once it has been hashed. [17] RBC also allows us to intentionally inject noise into the actual PUF response by including responses from fuzzy cells. With noise injection, the Hamming distance between the actual PUF response and the expected PUF response increases thus the computing power on the server end must also increase in order for the actual PUF response to be verified in a reasonable amount of time.…”

Section: Error Sources and Correction With Pufsmentioning

confidence: 99%

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Security and robustness of AI-driven IOTs with differential sensing schemes

Heynssens,

Cambou,

Montano Claure

2023

Autonomous Systems: Sensors, Processing and Security for Ground, Air, Sea, and Space Vehicles and Infrastructure 2023

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Unexpected faulty sensors can seriously compromise the mission of strategic assets driven by artificial intelligence (AI), autonomous unmanned vehicles, and robots. In life threatening operation, these devices must make real time decisions based on the vital information collected from the sensors. AI is vulnerable to sensor failures caused both by malicious actions and by system breakdown. We propose a new scheme that is providing, in real-time, a unique fingerprint of a pair of differential sensors operating as a Physically Unclonable Function (PUF). The solution can be implemented with little computational complexity or power usage on most IOT devices driven by AI and a set of sensors. The differential circuitry ensures the authenticity of the source of the information generated from the sensors, thereby preventing malicious actors from deliberately falsifying sensor data. Without the fingerprint from the sensors, these actors will have reduced opportunities to access the server thus limiting this attack vector. Faulty sensors are identifiable since their erratic fingerprints differ from those identified at launch. The data originating from bad sensors is thereby ignored in favor of the data generated by redundant sensors when available in the system. This technology also ensures that the accuracy of the information from the sensor is within normal tolerances for a real-time AI environment. The fingerprints are used to create unique encryption keys for standardized post quantum cryptographic based communication. We are hereby demonstrating experimentally the relevance of the proposed differential circuits for these targeted applications.

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“…These random numbers are used as symmetric encryption keys that are encapsulated by the more deterministic PUF responses. [17]…”

Section: Use Of Pufs and Enrollmentmentioning

confidence: 99%

Section: Error Sources and Correction With Pufsmentioning

confidence: 99%

Security and robustness of AI-driven IOTs with differential sensing schemes

Heynssens,

Cambou,

Montano Claure

2023

Autonomous Systems: Sensors, Processing and Security for Ground, Air, Sea, and Space Vehicles and Infrastructure 2023

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“…Attacks based on differential power analysis can extract cryptographic keys during the encryption and decryption process. Quantum adversaries are targeting key extractions as well [1]. Internet of things (IoT) devices are being used more and more in everyday life.…”

Section: Introductionmentioning

confidence: 99%

“…These tools depend on each other to build the keyless protocol. So, this section will give a brief description of the tools before explaining the keyless protocol steps [1].…”

Section: Introductionmentioning

confidence: 99%

Statistical Analysis of ReRAM-PUF based Keyless Encryption Protocol Against Frequency Analysis Attack

Miandoab¹,

Assiri²,

Mihaljevic³

et al. 2021

Preprint

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There has been a growing interest in fully integrating Physical Unclonable Function (PUF) for cryptographic primitives, or keyless encryption. Keyless primitives do not store key information during the entire encryption and decryption phase, providing full security against volatile and non-volatile memory attacks. The concept of keyless encryption using ReRAM PUF is a relatively new concept, and the security aspect of the protocol has not been tested yet. In this paper, we use statistical models to analyze the randomness of the protocol and its resistance against frequency attacks.

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“…It is now anticipated that quantum computers (QC) will be able to break both RSA and ECC when the technology to manufacture enough quantum nodes becomes available. Paper [9] describes practical ways to generate keys from physical unclonable functions, for both lattice and code-based cryptography and proposes to generate the public-private key pairs by replacing the random number generators with data streams generated from addressable physical unclonable functions (PUFs) to obtain the seeds needed in the post quantum cryptographic (PQC) algorithms. Dissimilar to the key pairs computed by PQC algorithms, the seeds are relatively short, typically 256-bits long.…”

mentioning

confidence: 99%