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Physical Unclonable Functions (PUFs) leverage manufacturing process imperfections that cause propagation delay discrepancies for the signals traveling along these paths. While PUFs can be used for device authentication and chip-specific key generation, strong PUFs have been shown to be vulnerable to machine learning modeling attacks. Although there is an impression that combinational circuits must be designed without any loops, cyclic combinational circuits have been shown to increase design security against hardware intellectual property theft. In this paper, we introduce feedback signals into traditional delay-based PUF designs such as arbiter PUF, ring oscillator PUF, and butterfly PUF to give them a wider range of possible output behaviors and thus an edge against modeling attacks. Based on our analysis, cyclic PUFs produce responses that can be binary, steady-state, oscillating, or pseudo-random under fixed challenges. The proposed cyclic PUFs are implemented in field programmable gate arrays, and their power and area overhead, in addition to functional metrics, are reported compared with their traditional counterparts. The security gain of the proposed cyclic PUFs is also shown against state-of-the-art attacks.
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Fortified-Edge 4.0: A ML-Based Error Correction Framework for Secure Authentication in Collaborative Edge Computing
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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- Award ID(s):
- 2101181
- PAR ID:
- 10581948
- Publisher / Repository:
- ACM
- Date Published:
- ISSN:
- 979-8-4007-0605-9/24/06
- ISBN:
- 9798400706059
- Page Range / eLocation ID:
- 639 to 644
- Subject(s) / Keyword(s):
- Collaborative Edge Computing (CEC), Cybersecurity, Security-by-Design (SbD), Hardware Assisted Security (HAS), Physical Unclonable Functions (PUF), Machine Learning (ML), Error Detection, Error Correction
- Format(s):
- Medium: X
- Location:
- Clearwater FL USA
- Sponsoring Org:
- National Science Foundation
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Physically Unclonable Functions (PUFs) have become an important and promising hardware primitive for device fingerprinting, device identification, or key storage. Intrinsic PUFs leverage components already found in existing devices, unlike extrinsic silicon PUFs, which are based on customized circuits that involve modification of hardware. In this work, we present a new type of a memory-based intrinsic PUF, which leverages the Rowhammer effect in DRAM modules - the Rowhammer PUF. Our PUF makes use of bit flips, which occur in DRAM cells due to rapid and repeated access of DRAM rows. Prior research has mainly focused on Rowhammer attacks, where the Rowhammer effect is used to illegitimately alter data stored in memory, e.g., to change page table entries or enable privilege escalation attacks. Meanwhile, this is the first work to use the Rowhammer effect in a positive context - to design a novel PUF. We extensively evaluate the Rowhammer PUF using commercial, off-the-shelf devices, not relying on custom hardware or an FPGA-based setup. The evaluation shows that the Rowhammer PUF holds required properties needed for the envisioned security applications, and could be deployed today.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3649476.3660384
