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Physical Unclonable Functions (PUFs) are widely researched in the field of security because of their unique, robust, and reliable nature, PUFs are considered device-specific root keys that are hard to duplicate. There are many variants of PUFs that are being studied and implemented including hardware and software PUFs. Though PUFs are believed to be secure and reliable, they are not without challenges of their own. The efficient performance of PUF depends on various environmental factors, which leads to inefficiency. Bit flipping is one such problem that can bring down the reliability of the PUF. Memory-based PUFs are prone to unavoidable bit flips occurring in the hardware, similarly, sensor-based PUFs are prone to bit flips occurring due to temperature variation. The number of errors in the PUF response must be minimized to improve the reliability of the PUF in security applications. In this research we explore the Machine Learning (ML) model based on K-mer sequencing to detect and correct the bit flips in the PUFs, hence fortifying the PUF-based secure authentication system for authentication and authorization of Edge Data Centers (EDC) in a Collaborative Edge Computing (CEC) Environment.
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Reconfigurable Physically Unclonable Functions Based on Nanoscale Voltage‐Controlled Magnetic Tunnel Junctions
Abstract With the fast growth of the number of electronic devices on the internet of things (IoT), hardware‐based security primitives such as physically unclonable functions (PUFs) have emerged to overcome the shortcomings of conventional software‐based cryptographic technology. Existing PUFs exploit manufacturing process variations in a semiconductor foundry technology. This results in a static challenge–response behavior, which can present a long‐term security risk. This study shows a reconfigurable PUF based on nanoscale magnetic tunnel junction (MTJ) arrays that uses stochastic dynamics induced by voltage‐controlled magnetic anisotropy (VCMA) for true random bit generation. A total of 100 PUF instances are implemented using 10 ns voltage pulses on a single chip with a 10 × 10 MTJ array. The unipolar nature of the VCMA mechanism is exploited to stabilize the MTJ state and eliminate bit errors during readout. All PUF instances show entropy close to one, inter‐Hamming distance close to 50%, and no bit errors in 104repeated readout measurements.
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- PAR ID:
- 10440327
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Electronic Materials
- Volume:
- 9
- Issue:
- 8
- ISSN:
- 2199-160X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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