Patterning Metal-Organic Frameworks (MOFs) is essential for their use in sensing, electronics, photonics, and encryption technologies. However, current lithography methods are limited in their ability to pattern more than two MOFs, hindering the potential for creating advanced multifunctional surfaces. Additionally, balancing design flexibility, simplicity, and cost often results in compromises. This study addresses these challenges by combining Digital-Light Processing (DLP) with a capillary-assisted stop-flow system to enable multimaterial MOF patterning. It demonstrates the desktop fabrication of multiplexed arbitrary micropatterns across cm-scale areas while preserving the MOF\'s pore accessibility. The ink, consisting of a MOF crystal suspension in a low volatile solvent, a mixture of high molecular weight oligomers, and a photoinitiator, is confined by capillarity in the DLP projection area and quickly exchanged using syringe pumps. The versatility of this method is demonstrated by the direct printing of a ZIF-8-based luminescent oxygen sensor, a 5-component dynamic information concealment method, and a PCN-224-based colorimetric sensor for amines, covering disparate pore and analyte sizes. The multi-MOF capabilities, simplicity, and accessibility of this strategy pave the way for the facile exploration of MOF materials across a wide range of applications, with the potential to significantly accelerate the design-to-application cycle of MOF-based devices.

The Internet of Medical Things (IoMT) has transformed healthcare by connecting medical devices, sensors, and patients, significantly improving patient care. However, the sensitive data exchanged through IoMT is vulnerable to security attacks, raising serious privacy concerns. Traditional key sharing mechanisms are susceptible to compromise, posing risks to data integrity. This paper proposes a Timestamp-based Secret Key Generation (T-SKG) scheme for resource-constrained devices, generating a secret key at the patient\'s device and regenerating it at the doctor\'s device, thus eliminating direct key sharing and minimizing key compromise risks. Simulation results using MATLAB and Java demonstrate the T-SKG scheme\'s resilience against guessing, birthday, and brute force attacks. Specifically, there is only a 9 % chance of key compromise in a guessing attack if the attacker knows the key sequence pattern, while the scheme remains secure against brute force and birthday attacks within a specified timeframe. The T-SKG scheme is integrated into a healthcare framework to securely transmit health vitals collected using the MySignals sensor kit. For confidentiality, the Data Encryption Standard (DES) with various Cipher Block modes (ECB, CBC, CTR) is employed.

In therapeutic diagnostics, early diagnosis and monitoring of heart disease is dependent on fast time-series MRI data processing. Robust encryption techniques are necessary to guarantee patient confidentiality. While deep learning (DL) algorithm have improved medical imaging, privacy and performance are still hard to balance. In this study, a novel approach for analyzing homomorphivally-encrypted (HE) time-series MRI data is introduced: The Multi-Faceted Long Short-Term Memory (MF-LSTM). This method includes privacy protection. The MF-LSTM architecture protects patient\'s privacy while accurately categorizing and forecasting cardiac disease, with accuracy (97.5%), precision (96.5%), recall (98.3%), and F1-score (97.4%). While segmentation methods help to improve interpretability by identifying important region in encrypted MRI images, Generalized Histogram Equalization (GHE) improves image quality. Extensive testing on selected dataset if encrypted time-series MRI images proves the method\'s stability and efficacy, outperforming previous approaches. The finding shows that the suggested technique can decode medical image to expose visual representation as well as sequential movement while protecting privacy and providing accurate medical image evaluation.

With growing threats from counterfeiting-based security breaches, multi-level and specific stimuli-responsive anti-counterfeiting devices and message encryption methods have attracted immense research interest. Fluorescence-based encryption from aggregation-induced emission (AIE)-based materials solves the problems to a considerable extent. However, the development of smarter patterns with hierarchical security levels alongside dynamic display is still challenging. To screen out this complication, we bring forward a pH-switchable fluorescent assembly of an AIEgen and an aliphatic acid. We later temporally direct the molecular assembly with the aid of a chemical trigger-regulated pH clock, generating a transitory multicolor emission, including transient white light generation. The pH-dependent emissions were further implemented in constructing smart multi-input fluorescent chemical AND gates. Subsequently, we integrate the time-gated emissive system to develop an advanced multi-dimensionally secure data encryption strategy. This novel approach enhances anti-counterfeiting measures by introducing an additional layer of security based on temporal characteristics.

Physical unclonable functions (PUFs) have emerged as an unprecedented solution for modern information security and anticounterfeiting by virtue of their inherent unclonable nature derived from distinctive, randomly generated physical patterns that defy replication. However, the creation of traceable optical PUF tags remains a formidable challenge. Here, we demonstrate a traceable PUF system whose unclonability arises from the random distribution of diamonds and the random intensity of the narrow emission from germanium vacancies (GeV) within the diamonds. Tamper-resistant PUF labels can be manufactured on diverse and intricate structural surfaces by blending diamond particles into polydimethylsiloxane (PDMS) and strategically depositing them onto the surface of objects. The resulting PUF codes exhibit essentially perfect uniformity, uniqueness, reproducibility, and substantial encoding capacity, making them applicable as a private key to fulfill the customization demands of circulating commodities. Through integration of a digitized \"challenge-response\" protocol, a traceable and highly secure PUF system can be established, which is seamlessly compatible with contemporary digital information technology. Thus, the GeV-PUF system holds significant promise for applications in data security and blockchain anticounterfeiting, providing robust and adaptive solutions to address the dynamic demands of these domains.

Fractional-order (FO) chaotic systems exhibit random sequences of significantly greater complexity when compared to integer-order systems. This feature makes FO chaotic systems more secure against various attacks in image cryptosystems. In this study, the dynamical characteristics of the FO Sprott K chaotic system are thoroughly investigated by phase planes, bifurcation diagrams, and Lyapunov exponential spectrums to be utilized in biometric iris image encryption. It is proven with the numerical studies the Sprott K system demonstrates chaotic behaviour when the order of the system is selected as 0.9. Afterward, the introduced FO Sprott K chaotic system-based biometric iris image encryption design is carried out in the study. According to the results of the statistical and attack analyses of the encryption design, the secure transmission of biometric iris images is successful using the proposed encryption design. Thus, the FO Sprott K chaotic system can be employed effectively in chaos-based encryption applications.

BACKGROUND: The medical knowledge graph provides explainable decision support, helping clinicians with prompt diagnosis and treatment suggestions. However, in real-world clinical practice, patients visit different hospitals seeking various medical services, resulting in fragmented patient data across hospitals. With data security issues, data fragmentation limits the application of knowledge graphs because single-hospital data cannot provide complete evidence for generating precise decision support and comprehensive explanations. It is important to study new methods for knowledge graph systems to integrate into multicenter, information-sensitive medical environments, using fragmented patient records for decision support while maintaining data privacy and security.
OBJECTIVE: This study aims to propose an electronic health record (EHR)-oriented knowledge graph system for collaborative reasoning with multicenter fragmented patient medical data, all the while preserving data privacy.
METHODS: The study introduced an EHR knowledge graph framework and a novel collaborative reasoning process for utilizing multicenter fragmented information. The system was deployed in each hospital and used a unified semantic structure and Observational Medical Outcomes Partnership (OMOP) vocabulary to standardize the local EHR data set. The system transforms local EHR data into semantic formats and performs semantic reasoning to generate intermediate reasoning findings. The generated intermediate findings used hypernym concepts to isolate original medical data. The intermediate findings and hash-encrypted patient identities were synchronized through a blockchain network. The multicenter intermediate findings were collaborated for final reasoning and clinical decision support without gathering original EHR data.
RESULTS: The system underwent evaluation through an application study involving the utilization of multicenter fragmented EHR data to alert non-nephrology clinicians about overlooked patients with chronic kidney disease (CKD). The study covered 1185 patients in nonnephrology departments from 3 hospitals. The patients visited at least two of the hospitals. Of these, 124 patients were identified as meeting CKD diagnosis criteria through collaborative reasoning using multicenter EHR data, whereas the data from individual hospitals alone could not facilitate the identification of CKD in these patients. The assessment by clinicians indicated that 78/91 (86%) patients were CKD positive.
CONCLUSIONS: The proposed system was able to effectively utilize multicenter fragmented EHR data for clinical application. The application study showed the clinical benefits of the system with prompt and comprehensive decision support.

Multiplexing technology creates several orthogonal data channels and dimensions for high-density information encoding and is irreplaceable in large-capacity information storage, and communication, etc. The multiplexing dimensions are constructed by light attributes and spatial dimensions. However, limited by the degree of freedom of interaction between light and material structure parameters, the multiplexing dimension exploitation method is still confused. Herein, a 7D Spin-multiplexing technique is proposed. Spin structures with four independent attributes (color center type, spin axis, spatial distribution, and dipole direction) are constructed as coding basic units. Based on the four independent spin physical effects, the corresponding photoluminescence wavelength, magnetic field, microwave, and polarization are created into four orthogonal multiplexing dimensions. Combined with the 3D of space, a 7D multiplexing method is established, which possesses the highest dimension number compared with 6 dimensions in the previous study. The basic spin unit is prepared by a self-developed laser-induced manufacturing process. The free state information of spin is read out by four physical quantities. Based on the multiple dimensions, the information is highly dynamically multiplexed to enhance information storage efficiency. Moreover, the high-dynamic in situ image encryption/marking is demonstrated. It implies a new paradigm for ultra-high-capacity storage and real-time encryption.

We refine and extend Ziv\'s model and results regarding perfectly secure encryption of individual sequences. According to this model, the encrypter and the legitimate decrypter share a common secret key that is not shared with the unauthorized eavesdropper. The eavesdropper is aware of the encryption scheme and has some prior knowledge concerning the individual plaintext source sequence. This prior knowledge, combined with the cryptogram, is harnessed by the eavesdropper, who implements a finite-state machine as a mechanism for accepting or rejecting attempted guesses of the plaintext source. The encryption is considered perfectly secure if the cryptogram does not provide any new information to the eavesdropper that may enhance their knowledge concerning the plaintext beyond their prior knowledge. Ziv has shown that the key rate needed for perfect secrecy is essentially lower bounded by the finite-state compressibility of the plaintext sequence, a bound that is clearly asymptotically attained through Lempel-Ziv compression followed by one-time pad encryption. In this work, we consider some more general classes of finite-state eavesdroppers and derive the respective lower bounds on the key rates needed for perfect secrecy. These bounds are tighter and more refined than Ziv\'s bound, and they are attained using encryption schemes that are based on different universal lossless compression schemes. We also extend our findings to the case where side information is available to the eavesdropper and the legitimate decrypter but may or may not be available to the encrypter.

In recent years in the field of traditional materials, traditional polyaniline has faced a number of scientific problems such as an irregular morphology, high difficulty in crystallization, and difficulty in forming an ordered structure compared to the corresponding inorganic materials. In response to these urgent issues, this study determines how to prepare a highly ordered structure in polyaniline formed at the gas-liquid interface. By dynamically arranging aniline monomers into a highly ordered structure with sodium dodecyl benzene sulfonate (SDBS) surfactant, aniline polymerization is initiated at the gas-liquid interface, resulting in two-dimensional polyaniline crystal sheets with a highly ordered structure. By elucidating the microstructure, crystallization process, and molecular structure of the two-dimensional polyaniline crystal sheets, the practical application of polyaniline as an encryption label in the field of electrochromism has been further expanded, thus making polyaniline widely used in the field of information encryption. Therefore, the synthesis of flaky polyaniline crystal sheets has a role in scientific research and practical application, which will arouse the interest and exploration of researchers.