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Exploring high‐safety but convenient encryption and decryption technologies to combat threats of information leakage is urgently needed but remains a great challenge. Here, a synergistically time‐ and temperature‐resolved information coding/decoding solution based on functional photonic inks is demonstrated. Encrypted messages can be stored into multiple channels with dynamic‐color patterns, and information decryption is only enabled at appointed temperature and time points. Notably, the ink can be easily processed into quick‐response codes and multipixel plates. With high transparency and responsive color variations controlled by ink compositions and ambient temperatures, advanced 3D stacking multichannel coding and Morse coding techniques can be applied for multi‐information storage, complex anticounterfeiting, and information interference. This study paves an avenue for the design and development of dynamic photonic inks and complex encryption technologies for high‐end anticounterfeiting applications. Here, a synergistically time‐/temperature‐resolved information coding/decoding solution based on a photonic anticounterfeiting ink is demonstrated. The ink can be easily processed into different patterns, which enable the storage of messages into multiple channels as well as the information decryption at appointed temperature and time points, providing inspirations for advanced information‐encryption and anticounterfeiting technologies.

This paper discusses the encryption-decryption-based state estimation (EDBSE) issue for coupled perturbation complex networks (CPCNs) in the framework of the Kalman-type filtering scheme. A uniform distributed random variable is employed to characterize the coupled perturbation among different network units. A uniform-quantization-dependent encryption-decryption (UQDED) scheme is considered here to orchestrate the transmitted data. A novel EDBSE approach is developed such that the upper bounds of prediction error (PE) covariance (PEC) and estimation error (EE) covariance (EEC) can be derived by resolving Riccati-like difference equations and the estimation parameter (EP) is determined by minimizing the trace of the upper bound of EEC. Furthermore, a uniformly bounded condition is elaborated to evaluate the algorithm performance of EDBSE. Finally, an illustrative example is conducted to verify the validity of the introduced EDBSE method.

In the paper we present a simple threshold decryption system based on the RSA cryptosystem. Our model avoids the application of the Shamir secret sharing protocol and is based only on the Chinese reminder theorem. The flexibility in the threshold level is attained due to the suitable preparation of the input data. The second part of the article describes a modification of the basic model, which admits the sender’s impact on the choice of the real receiver’s group.

The protection of data is essential in this digitized world and hence the need for cryptographic techniques to aid in this process. Cryptography in general helps achieve three primary goals; confidentiality, integrity, and authenticity. The goal of confidentiality is to ensure and allow for authorized access. Encryption is ubiquitous and unavoidable as it plays a pivotal role in confidentiality in both classical and quantum computing and cryptography. This paper proposes a classical and quantum cryptographic scheme known as “Kruptós” that is based on proven mathematical concepts and operations. As part of the scheme, certain principles have been incorporated to further increase its complexity. The traditional system development life cycle (SDLC) methodology was adopted in developing the algorithm. The frameworks and algorithms showed that the proposed technique can be used easily to encrypt textual data.

The Internet of Things (IoT) connects various medical devices that enable remote monitoring, which can improve patient outcomes and help healthcare providers deliver precise diagnoses and better service to patients. However, IoT-based healthcare management systems face significant challenges in data security, such as maintaining a triad of confidentiality, integrity, and availability (CIA) and securing data transmission. This paper proposes a novel AdaBoost support vector machine (ASVM) based on the grey wolf optimization and international data encryption algorithm (ASVM-based GWO-IDEA) to secure medical data in an IoT-enabled healthcare system. The primary objective of this work was to prevent possible cyberattacks, unauthorized access, and tampering with the security of such healthcare systems. The proposed scheme encodes the healthcare data before transmitting them, protecting them from unauthorized access and other network vulnerabilities. The scheme was implemented in Python, and its efficiency was evaluated using a Kaggle-based public healthcare dataset. The performance of the model/scheme was evaluated with existing strategies in the context of effective security parameters, such as the confidentiality rate and throughput. When using the suggested methodology, the data transmission process was improved and achieved a high throughput of 97.86%, an improved resource utilization degree of 98.45%, and a high efficiency of 93.45% during data transmission.

This research aims to enhance photo encryption security by developing a sophisticated technique. This method uses homomorphic encryption to address challenges in encrypting visible spectrum pictures. Each red–green–blue (RGB) channel of the image is divided into smaller sub-values, encrypted separately using an optimized homomorphic encryption algorithm, and then combined for further encryption. Additionally, a novel approach involves combining surrounding pixels to embed extra data during encryption. The process allows for compression and decompression of encrypted components for easier storage or transmission. After decryption, the initial pixel values are recovered, removing any unnecessary data and condensing each channel's pixel intensity into just two sub-values. Multiple security evaluations confirm the method's robustness and resistance, emphasizing its strong security features for encrypted images.

The majority of imaging techniques use symmetric and asymmetric cryptography algorithms to encrypt digital media. Most of the research works contributed in the literature focus primarily on the Advanced Encryption Standard (AES) algorithm for encryption and decryption. This paper propose an analysis for performing image encryption and decryption by hybridization of Elliptic Curve Cryptography (ECC) with Hill Cipher (HC), ECC with Advanced Encryption Standard (AES) and ElGamal with Double Playfair Cipher (DPC). This analysis is based on the following parameters: (i) Encryption and decryption time, (ii) entropy of encrypted image, (iii) loss in intensity of the decrypted image, (iv) Peak Signal to Noise Ratio (PSNR), (v) Number of Pixels Change Rate (NPCR), and (vi) Unified Average Changing Intensity (UACI). The hybrid process involves the speed and ease of implementation from symmetric algorithms, as well as improved security from asymmetric algorithms. ECC and ElGamal cryptosystems provide asymmetric key cryptography, while HC, AES, and DPC are symmetric key algorithms. ECC with AES are perfect for remote or private communications with smaller image sizes based on the amount of time needed for encryption and decryption. The metric measurement with test cases finds that ECC and HC have a good overall solution for image encryption.

Data exchange has been rapidly increased recently by increasing the use of mobile networks. Sharing information (text, image, audio and video) over unsecured mobile network channels is liable for attacking and stealing. Encryption techniques are the most suitable methods to protect information from hackers. Hill cipher algorithm is one of symmetric techniques, it has a simple structure and fast computations, but weak security because sender and receiver need to use and share the same private key within a non-secure channel. Therefore, a novel hybrid encryption approach between elliptic curve cryptosystem and hill cipher (ECCHC) is proposed in this paper to convert Hill Cipher from symmetric technique (private key) to asymmetric one (public key) and increase its security and efficiency and resist the hackers. Thus, no need to share the secret key between sender and receiver and both can generate it from the private and public keys. Therefore, the proposed approach presents a new contribution by its ability to encrypt every character in the 128 ASCII table by using its ASCII value direct without needing to assign a numerical value for each character. The main advantages of the proposed method are represented in the computation simplicity, security efficiency and faster computation.

The development of the Internet of Things (IoT) is predicted to change the healthcare industry and might lead to the rise of the Internet of Medical Things. The IoT revolution is surpassing the present-day human services with promising mechanical, financial, and social prospects. This paper investigated the security of medical images in IoT by utilizing an innovative cryptographic model with optimization strategies. For the most part, the patient data are stored as a cloud server in the hospital due to which the security is vital. So another framework is required for the secure transmission and effective storage of medical images interleaved with patient information. For increasing the security level of encryption and decryption process, the optimal key will be chosen using hybrid swarm optimization, i.e., grasshopper optimization and particle swarm optimization in elliptic curve cryptography. In view of this method, the medical images are secured in IoT framework. From this execution, the results are compared and contrasted, whereas a diverse encryption algorithm with its optimization methods from the literature is identified with the most extreme peak signal-to-noise ratio values, i.e., 59.45 dB and structural similarity index as 1.

In this paper, we have disccussed an algorithm for encryption and decryption using matrix theory and we have worked two examples for this algorithm.