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Ravichandran H, Sen D, Wali A, Schranghamer TF, Trainor N, Redwing JM, Ray B, Das S. A Peripheral-Free True Random Number Generator Based on Integrated Circuits Enabled by Atomically Thin Two-Dimensional Materials. ACS NANO 2023; 17:16817-16826. [PMID: 37616285 DOI: 10.1021/acsnano.3c03581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
A true random number generator (TRNG) is essential to ensure information security for Internet of Things (IoT) edge devices. While pseudorandom number generators (PRNGs) have been instrumental, their deterministic nature limits their application in security-sensitive scenarios. In contrast, hardware-based TRNGs derived from physically unpredictable processes offer greater reliability. This study demonstrates a peripheral-free TRNG utilizing two cascaded three-stage inverters (TSIs) in conjunction with an XOR gate composed of monolayer molybdenum disulfide (MoS2) field-effect transistors (FETs) by exploiting the stochastic charge trapping and detrapping phenomena at and/or near the MoS2/dielectric interface. The entropy source passes the NIST SP800-90B tests with a minimum normalized entropy of 0.8780, while the generated bits pass the NIST SP800-22 randomness tests without any postprocessing. Moreover, the keys generated using these random bits are uncorrelated with near-ideal entropy, bit uniformity, and Hamming distances, exhibiting resilience against machine learning (ML) attacks, temperature variations, and supply bias fluctuations with a frugal energy expenditure of 30 pJ/bit. This approach offers an advantageous alternative to conventional silicon, memristive, and nanomaterial-based TRNGs as it obviates the need for extensive peripherals while harnessing the potential of atomically thin 2D materials in developing low-power TRNGs.
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Affiliation(s)
- Harikrishnan Ravichandran
- Engineering Science and Mechanics, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Dipanjan Sen
- Engineering Science and Mechanics, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Akshay Wali
- Electrical Engineering and Computer Science, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Thomas F Schranghamer
- Engineering Science and Mechanics, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Nicholas Trainor
- Materials Science and Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, United States
- 2D Crystal Consortium, Materials Research Institute, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Joan M Redwing
- Materials Science and Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, United States
- 2D Crystal Consortium, Materials Research Institute, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Biswajit Ray
- Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, Colorado 80523, United States
| | - Saptarshi Das
- Engineering Science and Mechanics, Pennsylvania State University, University Park, Pennsylvania 16802, United States
- Materials Science and Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, United States
- 2D Crystal Consortium, Materials Research Institute, Pennsylvania State University, University Park, Pennsylvania 16802, United States
- Electrical Engineering and Computer Science, Pennsylvania State University, University Park, Pennsylvania 16802, United States
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Shao B, Wan T, Liao F, Kim BJ, Chen J, Guo J, Ma S, Ahn JH, Chai Y. Highly Trustworthy In-Sensor Cryptography for Image Encryption and Authentication. ACS NANO 2023. [PMID: 37186522 DOI: 10.1021/acsnano.3c00487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
The prevailing transmission of image information over the Internet of Things demands trustworthy cryptography for high security and privacy. State-of-the-art security modules are usually physically separated from the sensory terminals that capture images, which unavoidably exposes image information to various attacks during the transmission process. Here we develop in-sensor cryptography that enables capturing images and producing security keys in the same hardware devices. The generated key inherently binds to the captured images, which gives rise to highly trustworthy cryptography. Using the intrinsic electronic and optoelectronic characteristics of the 256 molybdenum disulfide phototransistor array, we can harvest electronic and optoelectronic binary keys with a physically unclonable function and further upgrade them into multiple-state ternary and double-binary keys, exhibiting high uniformity, uniqueness, randomness, and coding capacity. This in-sensor cryptography enables highly trustworthy image encryption to avoid passive attacks and image authentication to prevent unauthorized editions.
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Affiliation(s)
- Bangjie Shao
- Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong 999077, People's Republic of China
| | - Tianqing Wan
- Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong 999077, People's Republic of China
| | - Fuyou Liao
- Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong 999077, People's Republic of China
- The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen 518055, People's Republic of China
| | - Beom Jin Kim
- School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Jiewei Chen
- Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong 999077, People's Republic of China
| | - Jianmiao Guo
- Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong 999077, People's Republic of China
| | - Sijie Ma
- Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong 999077, People's Republic of China
| | - Jong-Hyun Ahn
- School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Yang Chai
- Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong 999077, People's Republic of China
- The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen 518055, People's Republic of China
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Kim MS, Lee GJ. Visually Hidden, Self-Assembled Porous Polymers for Optical Physically Unclonable Functions. ACS APPLIED MATERIALS & INTERFACES 2023; 15:4477-4486. [PMID: 36633500 DOI: 10.1021/acsami.2c18737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Owing to the advancement of security technologies, several encryption methods have been proposed. Despite such efforts, forging artifices is financially and somatically becoming a constraint for individuals and society (e.g., imprinting replicas of luxury goods or directly life-connected medicines). Physically unclonable functions (PUFs) are one of the promising solutions to address these personal and social issues. The unreplicability of PUFs is a crucial factor for high security levels. Here, this study proposes a visually hidden and self-assembled porous polymer (VSPP) as a tag for optical PUF systems. The VSPP has virtues in terms of wavelength dependency, lens-free compact PUF system, and simple/affordable fabrication processes (i.e., spin coating and annealing). The VSPP consists of an external saturated surface, which covers the inner structures, and an internally abundant porous layer, which triggers stochastic multiple Mie scattering with wavelength dependency. We theoretically and experimentally validate the unobservability of the VSPP and the uniqueness of optical responses by image sensors. Finally, we establish a wavelength-dependent PUF system by using the following three components: solid-state light sources, a VSPP tag, and an image sensor. The captured raw images by the sensor serve as "seed" for unique bit sequences. The robustness of our system is successfully confirmed in terms of bit uniformity (∼0.5), intra/interdevice Hamming distances (∼0.04/∼0.5), and randomness (using NIST test).
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Affiliation(s)
- Min Seong Kim
- Department of Electronics Engineering, Pusan National University, 2, Busandaehak-ro 63 beon-gil, Geumjeong-gu, Busan46241, Republic of Korea
| | - Gil Ju Lee
- Department of Electronics Engineering, Pusan National University, 2, Busandaehak-ro 63 beon-gil, Geumjeong-gu, Busan46241, Republic of Korea
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Revisiting silk: a lens-free optical physical unclonable function. Nat Commun 2022; 13:247. [PMID: 35017474 PMCID: PMC8752800 DOI: 10.1038/s41467-021-27278-5] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 11/05/2021] [Indexed: 01/08/2023] Open
Abstract
For modern security, devices, individuals, and communications require unprecedentedly unique identifiers and cryptographic keys. One emerging method for guaranteeing digital security is to take advantage of a physical unclonable function. Surprisingly, native silk, which has been commonly utilized in everyday life as textiles, can be applied as a unique tag material, thereby removing the necessary apparatus for optical physical unclonable functions, such as an objective lens or a coherent light source. Randomly distributed fibers in silk generate spatially chaotic diffractions, forming self-focused spots on the millimeter scale. The silk-based physical unclonable function has a self-focusing, low-cost, and eco-friendly feature without relying on pre-/post-process for security tag creation. Using these properties, we implement a lens-free, optical, and portable physical unclonable function with silk identification cards and study its characteristics and reliability in a systemic manner. We further demonstrate the feasibility of the physical unclonable functions in two modes: authentication and data encryption. Although conventional optical physical unclonable functions (PUFs) are attractive for security applications, existing optical PUFs have inherent complexity. Here, the authors report a low-cost, lens-free and compact optical PUF that uses silk microfiber-based stochastic diffraction.
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Wali A, Ravichandran H, Das S. A Machine Learning Attack Resilient True Random Number Generator Based on Stochastic Programming of Atomically Thin Transistors. ACS NANO 2021; 15:17804-17812. [PMID: 34665596 DOI: 10.1021/acsnano.1c05984] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
A true random number generator (TRNG) is a critical hardware component that has become increasingly important in the era of Internet of Things (IoT) and mobile computing for ensuring secure communication and authentication schemes. While recent years have seen an upsurge in TRNGs based on nanoscale materials and devices, their resilience against machine learning (ML) attacks remains unexamined. In this article, we demonstrate a ML attack resilient, low-power, and low-cost TRNG by exploiting stochastic programmability of floating gate (FG) field effect transistors (FETs) with atomically thin channel materials. The origin of stochasticity is attributed to the probabilistic nature of charge trapping and detrapping phenomena in the FG. Our TRNG also satisfies other requirements, which include high entropy, uniformity, uniqueness, and unclonability. Furthermore, the generated bit-streams pass NIST randomness tests without any postprocessing. Our findings are important in the context of hardware security for resource constrained IoT edge devices, which are becoming increasingly vulnerable to ML attacks.
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Affiliation(s)
- Akshay Wali
- Electrical Engineering and Computer Science, Penn State University, University Park, Pennsylvania 16802, United States
| | - Harikrishnan Ravichandran
- Engineering Science and Mechanics, Penn State University, University Park, Pennsylvania 16802, United States
| | - Saptarshi Das
- Electrical Engineering and Computer Science, Penn State University, University Park, Pennsylvania 16802, United States
- Engineering Science and Mechanics, Penn State University, University Park, Pennsylvania 16802, United States
- Materials Science and Engineering, Penn State University, University Park, Pennsylvania 16802, United States
- Materials Research Institute, Pennsylvania State University, University Park, Pennsylvania 16802, United States
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Chen X, Wang K, Shi B, Liu T, Chen R, Zhang M, Wen W, Xing G, Wu J. All-Inorganic Perovskite Nanorod Arrays with Spatially Randomly Distributed Lasing Modes for All-Photonic Cryptographic Primitives. ACS APPLIED MATERIALS & INTERFACES 2021; 13:30891-30901. [PMID: 34156815 DOI: 10.1021/acsami.1c08864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The level of hardware or information security can be increased by applying physical unclonable functions (PUFs), which have a high complexity and unique nonreplicability and are based on random physical patterns generated by nature, to anticounterfeiting and encryption technologies. The preparation of PUFs should be as simple and convenient as possible, while maintaining the high complexity and stability of PUFs to ensure high reliability in use. In this study, an all-inorganic perovskite single-crystal array with a controllable morphology and a random size was prepared by a one-step recrystallization method in a solvent atmosphere to generate all-photonic cryptographic primitives. The nondeterministic size of the perovskite nanorods mainly arises from crystal growth in an indeterminate direction, producing a high entropy for the system. The cavity-size-dependent lasing emission behavior of perovskite single crystals was investigated as a preliminary exploration of the generation of all-photonic cryptographic primitives. The lasing-mode number was positively correlated with the length of the perovskite nanorods. Therefore, the prepared perovskite nanorod array with random sizes can be transformed into a quaternary cryptographic key array following encoding rules based on the lasing-mode number. Superior lasing stability was observed for the all-inorganic perovskite under continuous excitation, demonstrating the high reliability of this system.
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Affiliation(s)
- Xinlian Chen
- Materials Genome Institute, Shanghai University, Shanghai 200444, China
| | - Kaiyang Wang
- Joint Key Laboratory of the Ministry of Education, Institute of Applied Physics and Materials Engineering, University of Macau, Avenida da Universidade, Taipa, Macau 999078, China
| | - Bori Shi
- Materials Genome Institute, Shanghai University, Shanghai 200444, China
| | - Tanghao Liu
- Joint Key Laboratory of the Ministry of Education, Institute of Applied Physics and Materials Engineering, University of Macau, Avenida da Universidade, Taipa, Macau 999078, China
| | - Riming Chen
- Joint Key Laboratory of the Ministry of Education, Institute of Applied Physics and Materials Engineering, University of Macau, Avenida da Universidade, Taipa, Macau 999078, China
| | - Mengying Zhang
- Department of Physics, Shanghai University, Shanghai 200444, China
| | - Weijia Wen
- Materials Genome Institute, Shanghai University, Shanghai 200444, China
- Department of Physics, The Hong Kong University of Science and Technology, Hong Kong 999077, China
| | - Guichuan Xing
- Joint Key Laboratory of the Ministry of Education, Institute of Applied Physics and Materials Engineering, University of Macau, Avenida da Universidade, Taipa, Macau 999078, China
| | - Jinbo Wu
- Materials Genome Institute, Shanghai University, Shanghai 200444, China
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