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The number of smart homes is increasing steadily. One of the first technologies that comes to mind when talking about smart homes is Zigbee, which stands out for its low cost, low latency, low power consumption, and mesh networking capabilities. One of the key features of Zigbee is the encryption of payloads within its frames for security purposes. However, being able to decrypt this payload is crucial for fully understanding its operation and for purposes such as testing the network’s security. Therefore, in this paper, we present the decrypted Zigbee IoT Network Traffic dataset, ZigBeeNet. We captured packets using Wireshark in real time from a smart home with 15 Zigbee devices over 20 days and saved them in pcap files. Additionally, we used a key extraction method to obtain the network key, decrypt the payload data, and analyze the characteristic features of network traffic, which we present in this paper. ZigBeeNet will be useful in wider areas than existing datasets with its ability to support network security research, pattern analysis, network performance analysis, and Zigbee traffic generator. We believe that this open-source dataset will contribute significantly to a wide range of industrial and academic research applications. Full article

Outlined is a proposal designed to culminate in the foundry fabrication of arrays of singly addressable quantum dot sources deterministically emitting single pairs of energy-time entangled photons at C-band wavelengths, each pair having negligible spin-orbit fine structure splitting, each pair being channeled into single mode pig-tail optical fibers. Entangled photons carry quantum state information among distributed quantum servers via I/O ports having two functions: the unconditionally secure distribution of decryption keys to decrypt publicly distributed, encrypted classical bit streams as input to generate corresponding qubit excitations and to convert a stream of quantum nondemolition measurements of qubit states into a classical bit stream. Outlined are key steps necessary to fabricate arrays of on-demand quantum dot sources of entangled photon pairs; the principles are (1) foundry fabrication of arrays of isolated quantum dots, (2) generation of localized sub-surface shear strain in a semiconductor stack, (3) a cryogenic anvil cell, (4) channeling entangled photons into single-mode optical fibers, (5) unconditionally secure decryption key distribution over the fiber network, (6) resonant excitation of a Josephson tunnel junction qubits from classical bits, and (7) conversion of quantum nondemolition measurements of qubit states into a classical bit. Full article

In this paper, we propose a definition of block tensors and the real representation of tensors. Equipped with the simplification method, i.e., the real representation along with the M-P inverse, we demonstrate the conditions that are necessary and sufficient for the system of dual split quaternion tensor equations $(\mathcal{A}{\ast }_N\mathcal{X},\mathcal{X}{\ast }_S\mathcal{C})=(\mathcal{B},\mathcal{D})$, when its solution exists. Furthermore, the general expression of the solution is also provided when the solution of the system exists, and we use a numerical example to validate it in the last section. To the best of our knowledge, this is the first time that the aforementioned tensor system has been examined on dual split quaternion algebra. Additionally, we provide its equivalent conditions when its Hermitian solution $\mathcal{X}={\mathcal{X}}^{\ast }$ and $\eta$-Hermitian solutions $\mathcal{X}={\mathcal{X}}^{\eta \ast }$ exist. Subsequently, we discuss two special dual split quaternion tensor equations. Last but not least, we propose an application for encrypting and decrypting two color videos, and we validate this algorithm through a specific example. Full article

Federated learning avoids centralizing data in a central server by distributing the model training process across devices, thus protecting privacy to some extent. However, existing research shows that model updates (e.g., gradients or weights) exchanged during federated learning may still indirectly leak sensitive information about the original data. Currently, single-key homomorphic encryption methods applied in federated learning cannot solve the problem of privacy leakage that may be caused by the collusion between the participant and the federated learning server, whereas existing privacy-preserving federated learning schemes based on multi-key homomorphic encryption in semi-honest environments have deficiencies and limitations in terms of security and application conditions. To this end, this paper proposes a privacy-preserving federated learning scheme based on multi-key fully homomorphic encryption to cope with the potential risk of privacy leakage in traditional federated learning. We designed a multi-key fully homomorphic encryption scheme, mMFHE, that encrypts by aggregating public keys and requires all participants to jointly participate in decryption sharing, thus ensuring data security and privacy. The proposed privacy-preserving federated learning scheme encrypts the model updates through multi-key fully homomorphic encryption, ensuring confidentiality under the CRS model and in a semi-honest environment. As a fully homomorphic encryption scheme, mMFHE supports homomorphic addition and homomorphic multiplication for more flexible applications. Our security analysis proves that the scheme can withstand collusive attacks by up to $N-1$ users and servers, where N is the total number of users. Performance analysis and experimental results show that our scheme reduces the complexity of the NAND gate, which reduces the computational load and improves the efficiency while ensuring the accuracy of the model. Full article

Ensuring the security of picture data on a network presents considerable difficulties because of the requirement for conventional embedding systems, which ultimately leads to subpar performance. It poses a risk of unauthorized data acquisition and misuse. Moreover, the previous image security-based techniques faced several challenges, including high execution times. As a result, a novel framework called Graph Convolutional-Based Twofish Security (GCbTS) was introduced to secure the images used in healthcare. The medical data are gathered from the Kaggle site and included in the proposed architecture. Preprocessing is performed on the data inserted to remove noise, and the hash 1 value is computed. Using the generated key, these separated images are put through the encryption process to encrypt what they contain. Additionally, to verify the user’s identity, the encrypted data calculates the hash 2 values contrasted alongside the hash 1 value. Following completion of the verification procedure, the data are restored to their original condition and made accessible to authorized individuals by decrypting them with the collective key. Additionally, to determine the effectiveness, the calculated results of the suggested model are connected to the operational copy, which depends on picture privacy. Full article

The computer network has fundamentally transformed modern interactions, enabling the effortless transmission of multimedia data. However, the openness of these networks necessitates heightened attention to the security and confidentiality of multimedia content. Digital images, being a crucial component of multimedia communications, require robust protection measures, as their security has become a global concern. Traditional color image encryption/decryption algorithms, such as DES, IDEA, and AES, are unsuitable for image encryption due to the diverse storage formats of images, highlighting the urgent need for innovative encryption techniques. Chaos-based cryptosystems have emerged as a prominent research focus due to their properties of randomness, high sensitivity to initial conditions, and unpredictability. These algorithms typically operate in two phases: shuffling and replacement. During the shuffling phase, the positions of the pixels are altered using chaotic sequences or matrix transformations, which are simple to implement and enhance encryption. However, since only the pixel positions are modified and not the pixel values, the encrypted image’s histogram remains identical to the original, making it vulnerable to statistical attacks. In the replacement phase, chaotic sequences alter the pixel values. This research introduces a novel encryption technique for color images (RGB type) based on DNA subsequence operations to secure these images, which often contain critical information, from potential cyber-attacks. The suggested method includes two main components: a high-speed permutation process and adaptive diffusion. When implemented in the MATLAB software environment, the approach yielded promising results, such as NPCR values exceeding 98.9% and UACI values at around 32.9%, demonstrating its effectiveness in key cryptographic parameters. Security analyses, including histograms and Chi-square tests, were initially conducted, with passing Chi-square test outcomes for all channels; the correlation coefficient between adjacent pixels was also calculated. Additionally, entropy values were computed, achieving a minimum entropy of 7.0, indicating a high level of randomness. The method was tested on specific images, such as all-black and all-white images, and evaluated for resistance to noise and occlusion attacks. Finally, a comparison of the proposed algorithm’s NPCR and UAC values with those of existing methods demonstrated its superior performance and suitability. Full article

The Internet of Things (IoT) is a heterogeneous network composed of numerous dynamically connected devices. While it brings convenience, the IoT also faces serious challenges in data security. Ciphertext-policy attribute-based encryption (CP-ABE) is a promising cryptography method that supports fine-grained access control, offering a solution to the IoT’s security issues. However, existing CP-ABE schemes are inefficient and unsuitable for IoT devices with limited computing resources. To address this problem, this paper proposes an efficient pairing-free CP-ABE scheme for the IoT. The scheme is based on lightweight elliptic curve scalar multiplication and supports multi-authority and verifiable outsourced decryption. The proposed scheme satisfies indistinguishability against chosen-plaintext attacks (CPA) under the elliptic curve decisional Diffie–Hellman (ECDDH) problem. Performance analysis shows that our proposed scheme is more efficient and better suited to the IoT environment compared to existing schemes. Full article

Traditional cryptographic methods often need complex designs that require substantial memory and battery power, rendering them unsuitable for small handheld devices. As the prevalence of these devices continues to rise, there is a pressing need to develop smart, memory-efficient cryptographic protocols that provide both high speed and robust security. Current solutions, primarily dependent on dynamic permutations, fall short in terms of encryption and decryption speeds, the cryptographic strength, and the memory efficiency. Consequently, the evolution of lightweight cryptographic algorithms incorporating randomised substitution properties is imperative to meet the stringent security demands of handheld devices effectively. In this paper, we present an advanced design of lightweight block ciphers that enhances traditional dynamic permutations with innovative randomised substitutions. This design utilises straightforward randomized encryption methods such as XOR, nibble swap, count ones, and left shift. The cryptographic robustness of our proposed block cipher has been rigorously tested through several standardised statistical tests, as recommended by the National Institute of Standards and Technology (NIST). These evaluations confirm that our algorithm maintains strong cryptographic properties with randomised substitutions and outperforms existing models in several key aspects. Moreover, comparative assessments reveal that our algorithm achieves a throughput of 853.31 Kbps while consuming only 1510 bytes of memory and demonstrating over 60% avalanche properties, significantly outperforming other solutions in terms of CPU utilisation and memory consumption. These results underscore the efficacy of our approach in fulfilling the advanced security requirements of modern handheld devices. Full article

Quantum-secure cryptography is a dynamic field due to its crucial role in various domains. This field aligns with the ongoing efforts in data security. Post-quantum encryption (PQE) aims to counter the threats posed by future quantum computers, highlighting the need for further improvement. Based on the learning with error (LWE) system, this paper introduces a novel asymmetric encryption technique that encrypts entire messages of n bits rather than just 1 bit. This technique offers several advantages including an additive homomorphic cryptosystem. The robustness of the proposed lightweight public key encryption method, which is based on a new version of LWE, ensures that private keys remain secure and that original data cannot be recovered by an attacker from the ciphertext. By improving encryption and decryption execution time—which achieve speeds of 0.0427 ms and 0.0320 ms, respectively—and decreasing ciphertext size to 708 bits for 128-bit security, the obtained results are very promising. Full article

In the past two decades, research in the field of chaotic synchronization has attracted extensive attention from scholars, and at the same time, more synchronization methods, such as chaotic master–slave synchronization, projection synchronization, sliding film synchronization, fractional-order synchronization and so on, have been proposed and applied to chaotic secure communication. In this paper, based on radial basis function neural network theory and the particle swarm optimisation algorithm, the RBFNN-PSO synchronisation method is proposed for the Sprott B chaotic system with external noise. The RBFNN controller is constructed, and its parameters are used as the particle swarm particle optimisation parameters, and the optimal values of the controller parameters are obtained by the PSO training method, which overcomes the influence of external noise and achieves the synchronisation of the master–slave system. Then, it is shown by numerical simulation and analysis that the scheme has a good performance against external noise. Because the Sprott B system has multiple chaotic attractors with richer dynamics, the synchronization system based on Sprott B chaos is applied to the image encryption system. In particular, the Zigzag disambiguation method for top corner rotation and RGB channel selection is proposed, and the master–slave chaotic system synchronisation sequences are diffused to the disambiguated data streams, respectively. Therefore, the encryption and decryption of image transmission are implemented and the numerical simulation results are given, the random distribution characteristics of encrypted images are analysed using histogram and Shannon entropy methods, and the final results achieve the expected results. Full article

Coherent diffractive imaging is an optical methodology that encodes information about an object within the diffraction intensity. Here, we introduce a diffractive optical encryption system that utilizes multiple wavelengths and multiple distances, significantly expanding the size of the secret key space and enhancing the overall security of the system by incorporating these parameters as keys. The system adopts single optical path design, compact structure and is easy to implement, overcoming the disadvantage of single key space of traditional encryption system. This system can encrypt images into a series of diffraction intensity maps (i.e., ciphertexts), and exhibits a high sensitivity to minor variations in wavelength or distance during the process of decryption, showing excellent anti-cracking ability. Furthermore, the system also has considerable robustness, ensuring that the information still can be effectively recovered even in instances of partial loss. Numerical simulation results are presented to demonstrate feasibility and effectiveness of the proposed method. Our study provides novel concepts and methodologies to the advancement of optical encryption technology, while also offering significant technical assistance to the domain of information security. Full article

As technology advances rapidly, a diverse array of Internet of Things (IoT) devices finds widespread application across numerous fields. The intelligent nature of these devices not only gives people more convenience, but also introduces new challenges especially in security when transmitting data in fog-based cloud environments. In fog computing environments, data need to be transmitted across multiple devices, increasing the risk of data being intercepted or tampered with during transmission. To securely share cloud ciphertexts, an alleged proxy re-encryption approach is a commonly adopted solution. Without decrypting the original ciphertext, such a mechanism permits a ciphertext intended for user A to be easily converted into the one intended for user B. However, to revoke the decryption privilege of data users usually relies on the system authority to maintain a user revocation list which inevitably increases the storage space. In this research, the authors come up with a fog-based proxy re-encryption system with revocable identity. Without maintaining the traditional user revocation list, the proposed scheme introduces a time-updated key mechanism. The time-update key could be viewed as a partial private key and should be renewed with different time periods. A revoked user is unable to obtain the renewed time-update key and hence cannot share or decrypt cloud ciphertexts. We formally demonstrate that the introduced scheme satisfies the security of indistinguishability against adaptively chosen identity and chosen plaintext attacks (IND-PrID-CPA) assuming the hardness of the Decisional Bilinear Diffie–Hellman (DBDH) problem in the random oracle model. Furthermore, compared with similar systems, the proposed one also has lower computational complexity as a whole. Full article

This paper presents three novel encryption and decryption schemes based on graph theory that aim to improve security and error resistance in communication networks. The novelty of this work lies in the application of complete bipartite graphs in two of the schemes and the Cartesian product of graphs in the third, representing a unique approach to cryptographic algorithm development. Unlike traditional cryptographic methods, these graph-based schemes use structural properties of graphs to achieve robust encryption, providing greater resistance to attacks and corruption. Each scheme is illustrated with detailed examples that show how the algorithms can be successfully implemented. The algorithms are written in standard mathematical notation, making them adaptable for machine implementation and scalable for real-world use. The schemes are also rigorously analyzed and compared in terms of their temporal and spatial complexities, using Big $\mathcal{O}$ notation. This comprehensive evaluation focuses on their effectiveness, providing valuable insights into their potential for secure communication in modern networks. Full article

This paper proposes an asymmetric scanning holography cryptosystem based on the Elgamal algorithm. The method encodes images with sine and cosine holograms. Subsequently, each hologram is divided into a signed bit matrix and an unsigned hologram matrix, both encrypted using the sender’s private key and the receiver’s public key. The resulting ciphertext matrices are then transmitted to the receiver. Upon receipt, the receiver decrypts the ciphertext matrices using their private key and the sender’s public key. We employ an asymmetric single-image encryption method for key management and dispatch for securing imaging and transmission. Furthermore, we conducted a sensitivity analysis of the encryption system. The image encryption metrics, including histograms of holograms, adjacent pixel correlation, image correlation, the peak signal-to-noise ratio, and the structural similarity index, were also examined. The results demonstrate the security and stability of the proposed method. Full article

Protecting sensitive patient data, such as electrocardiogram (ECG) signals, during RF wireless transmission is essential due to the increasing demand for secure telemedicine communications. This paper presents an innovative chaotic-based encryption system designed to enhance the security and integrity of telemedicine data transmission. The proposed system utilizes a multi-scroll chaotic system for ECG signal encryption based on master–slave synchronization. The ECG signal is encrypted by a master system and securely transmitted to a remote location, where it is decrypted by a slave system using an extended state observer. Synchronization between the master and slave is achieved through the Lyapunov criteria, which ensures system stability. The system also supports Orthogonal Frequency Division Multiplexing (OFDM) and adaptive n-quadrature amplitude modulation (n-QAM) schemes to optimize signal discretization. Experimental validations with a custom transceiver scheme confirmed the system’s effectiveness in preventing channel overlap during 2.5 GHz transmissions. Additionally, a commercial RF Power Amplifier (RF-PA) for LTE applications and a development board were integrated to monitor transmission quality. The proposed encryption system ensures robust and efficient RF transmission of ECG data, addressing critical challenges in the wireless communication of sensitive medical information. This approach demonstrates the potential for broader applications in modern telemedicine environments, providing a reliable and efficient solution for the secure transmission of healthcare data. Full article