Photosensing PUF from an Intrinsically Random SnTe Memristor for Image Encryption and Recognition.
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| Title: | Photosensing PUF from an Intrinsically Random SnTe Memristor for Image Encryption and Recognition. |
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| Authors: | Xu, Wendi1 (AUTHOR), Zhang, Jia1 (AUTHOR), Xie, Junjie1 (AUTHOR), Xu, Tianzhu1 (AUTHOR), Wu, Jia1 (AUTHOR), Wang, Hong1 (AUTHOR) hongwang93@126.com |
| Source: | Nanomaterials (2079-4991). Jun2026, Vol. 16 Issue 12, p715. 12p. |
| Subjects: | Image encryption, Memristors, Computer security, Photosensitivity, Artificial synapses, Neuromorphics |
| Abstract: | Physical unclonable function (PUF) based on intrinsic device randomness has emerged as promising hardware security primitives, yet combining secure encryption with neuromorphic recognition within a single device platform remains challenging. Here, we demonstrate a photosensing PUF based on an intrinsically random SnTe memristor capable of both image encryption and memristive neural network recognition. The SnTe memristor, fabricated with an In2O3:SnO2/SnTe/Nb:SrTiO3 structure, exhibits stable resistive switching and stable retention exceeding 4000 s. Synaptic biomimetic behaviors including learning-experience emulation, short-term plasticity and long-term plasticity are also realized. Notably, the device displays pronounced optical sensitivity that produces stochastic photocurrent fluctuations originating from unavoidable device-to-device variations under illumination. By quantizing these random photocurrents, an encryption key stream is generated and utilized for image scrambling and diffusion. A memristive neural network is constructed to classify the encrypted images, achieving a recognition accuracy of 95.1% with a loss of 0.15 after 300 training epochs. This work establishes a viable pathway from intrinsic optical randomness to secure neuromorphic computing, highlighting the multifunctional potential of SnTe memristors in integrated hardware security and brain-inspired computation. [ABSTRACT FROM AUTHOR] |
| Copyright of Nanomaterials (2079-4991) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 194907434 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Photosensing PUF from an Intrinsically Random SnTe Memristor for Image Encryption and Recognition. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Xu%2C+Wendi%22">Xu, Wendi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Jia%22">Zhang, Jia</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xie%2C+Junjie%22">Xie, Junjie</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xu%2C+Tianzhu%22">Xu, Tianzhu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wu%2C+Jia%22">Wu, Jia</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Hong%22">Wang, Hong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> hongwang93@126.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Nanomaterials+%282079-4991%29%22">Nanomaterials (2079-4991)</searchLink>. Jun2026, Vol. 16 Issue 12, p715. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Image+encryption%22">Image encryption</searchLink><br /><searchLink fieldCode="DE" term="%22Memristors%22">Memristors</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+security%22">Computer security</searchLink><br /><searchLink fieldCode="DE" term="%22Photosensitivity%22">Photosensitivity</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+synapses%22">Artificial synapses</searchLink><br /><searchLink fieldCode="DE" term="%22Neuromorphics%22">Neuromorphics</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Physical unclonable function (PUF) based on intrinsic device randomness has emerged as promising hardware security primitives, yet combining secure encryption with neuromorphic recognition within a single device platform remains challenging. Here, we demonstrate a photosensing PUF based on an intrinsically random SnTe memristor capable of both image encryption and memristive neural network recognition. The SnTe memristor, fabricated with an In2O3:SnO2/SnTe/Nb:SrTiO3 structure, exhibits stable resistive switching and stable retention exceeding 4000 s. Synaptic biomimetic behaviors including learning-experience emulation, short-term plasticity and long-term plasticity are also realized. Notably, the device displays pronounced optical sensitivity that produces stochastic photocurrent fluctuations originating from unavoidable device-to-device variations under illumination. By quantizing these random photocurrents, an encryption key stream is generated and utilized for image scrambling and diffusion. A memristive neural network is constructed to classify the encrypted images, achieving a recognition accuracy of 95.1% with a loss of 0.15 after 300 training epochs. This work establishes a viable pathway from intrinsic optical randomness to secure neuromorphic computing, highlighting the multifunctional potential of SnTe memristors in integrated hardware security and brain-inspired computation. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Nanomaterials (2079-4991) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/nano16120715 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 715 Subjects: – SubjectFull: Image encryption Type: general – SubjectFull: Memristors Type: general – SubjectFull: Computer security Type: general – SubjectFull: Photosensitivity Type: general – SubjectFull: Artificial synapses Type: general – SubjectFull: Neuromorphics Type: general Titles: – TitleFull: Photosensing PUF from an Intrinsically Random SnTe Memristor for Image Encryption and Recognition. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Xu, Wendi – PersonEntity: Name: NameFull: Zhang, Jia – PersonEntity: Name: NameFull: Xie, Junjie – PersonEntity: Name: NameFull: Xu, Tianzhu – PersonEntity: Name: NameFull: Wu, Jia – PersonEntity: Name: NameFull: Wang, Hong IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20794991 Numbering: – Type: volume Value: 16 – Type: issue Value: 12 Titles: – TitleFull: Nanomaterials (2079-4991) Type: main |
| ResultId | 1 |
