An official website of the United States government
Abstract Physical unclonable functions (PUFs) are emerging as an alternative to information security by providing an advanced level of cryptographic keys with non‐replicable characteristics, yet the cryptographic keys of conventional PUFs are not reconfigurable from the ones assigned at the manufacturing stage and the overall authentication process slows down as the number of entities in the dataset or the length of cryptographic key increases. Herein, a supersaturated solution‐based PUF (S‐PUF) is presented that utilizes stochastic crystallization of a supersaturated sodium acetate solution to allow a time‐efficient, hierarchical authentication process together with on‐demand rewritability of cryptographic keys. By controlling the orientation and the average grain size of the sodium acetate crystals via a spatiotemporally programmed temperature profile, the S‐PUF now includes two global parameters, that is, angle of rotation and divergence of the diffracted beam, in addition to the speckle pattern to produce multilevel cryptographic keys, and these parameters function as prefixes for the classification of each entity for a fast authentication process. At the same time, the reversible phase change of sodium acetate enables repeated reconfiguration of the cryptographic key, which is expected to offer new possibilities for a next‐generation, recyclable anti‐counterfeiting platform.
more »
« less
Tattoo‐Like Multi‐Color Physically Unclonable Functions
Abstract Advanced anti‐counterfeiting and authentication approaches are in urgent need of the rapidly digitizing society. Physically unclonable functions (PUFs) attract significant attention as a new‐generation security primitive. The challenge is design and generation of multi‐color PUFs that can be universally applicable to objects of varied composition, geometry, and rigidity. Herein, tattoo‐like multi‐color fluorescent PUFs are proposed and demonstrated. Multi‐channel optical responses are created by electrospraying of polymers that contain semiconductor nanocrystals with precisely defined photoluminescence. The universality of this approach enables the use of dot and dot‐in‐rod geometries with unique optical characteristics. The fabricated multi‐color PUFs are then transferred to a target object by using a temporary tattoo approach. Digitized keys generated from the red, green and blue fluorescence channels facilitate large encoding capacity and rapid authentication. Feature matching algorithms complement the authentication by direct image comparison, effectively alleviating constraints associated with imaging conditions. The strategy that paves the way for the development of practical, cost‐effective, and secure anticounterfeiting systems is presented.
more »
« less
- Award ID(s):
- 2132538
- PAR ID:
- 10478559
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Optical Materials
- Volume:
- 12
- Issue:
- 12
- ISSN:
- 2195-1071
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract A Physical Unclonable Function (PUF) is a security primitive that exploits inherent variations in manufacturing protocols to generate unique, random‐like identifiers. These identifiers are used for authentication and encryption purposes in hardware security applications in the semiconductor industry. Inspired by the success of silicon PUFs, herein it is leverage Terminal deoxynucleotidyl Transferase (TdT), a template‐independent polymerase belonging to the X‐family of DNA polymerases, to augment the intrinsic entropy generated during DNA lesion repair and rapidly produce genetic PUFs that satisfy the following properties: robustness (i.e., they repeatedly produce the same output), uniqueness (i.e., they do not coincide with any other identically produced PUF), and unclonability (i.e., they are virtually impossible to replicate). Furthermore, a post‐sequencing feature selection methodology based on logistic regression to facilitate PUF classification is developed. This experimental and computational pipeline drastically reduces production time and cost compared to conventional genetic barcoding without compromising the stringent PUF criteria of uniqueness and unclonability. This results provide novel insights into the function of TdT and represent a major step toward utilization of PUFs as a biosecurity primitive for cell line authentication and provenance attestation.more » « less
-
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.more » « less
-
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.more » « less
-
The hallmark of the information age is the ease with which information is stored, accessed, and shared throughout the globe. This is enabled, in large part, by the simplicity of duplicating digital information without error. Unfortunately, an ever-growing consequence is the global threat to security and privacy enabled by our digital reliance. Specifically, modern secure communications and authentication suffer from formidable threats arising from the potential for copying of secret keys stored in digital media. With relatively little transfer of information, an attacker can impersonate a legitimate user, publish malicious software that is automatically accepted as safe by millions of computers, or eavesdrop on countless digital exchanges. To address this vulnerability, a new class of cryptographic devices known as physical unclonable functions (PUFs) are being developed. PUFs are modern realizations of an ancient concept, the physical key, and offer an attractive alternative for digital key storage. A user derives a digital key from the PUF’s physical behavior, which is sensitive to physical idiosyncrasies that are beyond fabrication tolerances. Thus, unlike conventional physical keys, a PUF cannot be duplicated and only the holder can extract the digital key. However, emerging machine learning (ML) methods are remarkably adept at learning behavior via training, and if such algorithms can learn to emulate a PUF, then the security is compromised. Unfortunately, such attacks are highly successful against conventional electronic PUFs. Here, we investigate ML attacks against a nonlinear silicon photonic PUF, a novel design that leverages nonlinear optical interactions in chaotic silicon microcavities. First, we investigate these devices’ resistance to cloning during fabrication and demonstrate their use as a source of large volumes of cryptographic key material. Next, we demonstrate that silicon photonic PUFs exhibit resistance to state-of-the-art ML attacks due to their nonlinearity and finally validate this resistance in an encryption scenario.more » « less
