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Privacy-preserving techniques allow private information to be used without compromising privacy. Most encryption algorithms, such as the Advanced Encryption Standard (AES) algorithm, cannot perform computational operations on encrypted data without first applying the decryption process. Homomorphic encryption algorithms provide innovative solutions to support computations on encrypted data while preserving the content of private information. However, these algorithms have some limitations, such as computational cost as well as the need for modifications for each case study. In this paper, we present a comprehensive overview of various homomorphic encryption tools for Big Data analysis and their applications. We also discuss a security framework for Big Data analysis while preserving privacy using homomorphic encryption algorithms. We highlight the fundamental features and tradeoffs that should be considered when choosing the right approach for Big Data applications in practice. We then present a comparison of popular current homomorphic encryption tools with respect to these identified characteristics. We examine the implementation results of various homomorphic encryption toolkits and compare their performances. Finally, we highlight some important issues and research opportunities. We aim to anticipate how homomorphic encryption technology will be useful for secure Big Data processing, especially to improve the utility and performance of privacy-preserving machine learning.

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.

This paper constructs a secure storage and sharing model of medical data based on the blockchain technology of computer network technology, and the model mainly designs the encryption process, storage process and sharing process of medical data. The model combines asymmetric encryption algorithm and ciphertext access strategy and designs a hybrid encryption method for secure storage and sharing of medical data through three stages: public parameters and key generation, encryption and decryption. The comprehensive performance of the constructed model is tested, and the security performance indexes are 0.998, 0.989, 0.996 and 0.993 and the execution time of the sharing mechanism is 1~16s, the data upload time is 1200ms, and the data download time is only 200ms.

Protecting the contents of medical records is of paramount importance when it comes to preserving patients’ privacy. Most existing cryptographic-based solutions rely on traditional encryption algorithms having a multi-round structure, which introduces processing latency and requires increased resources. Medical images possess special characteristics compared to other types of images. The main goal of this paper is to leverage these characteristics to design and implement an efficient and secure encryption algorithm for such images. The proposed solution defines three variants of encryption algorithms: (a) full, (b) middle-full, and (c) selective. The full approach encrypts all sub-matrices of an image, while the middle-full variant is a middle solution between the selective and full algorithms and its goal is to just hide the type of the medical image. Selective encryption identifies a set of sub-matrices of an image according to a statistical average test, known as region of interest (ROI). In the three approaches, a high security level is ensured since each image is encrypted independently of the previous and next images. Also, all primitives of the proposed cipher, such as permutation and substitution, depend on a dynamic key. Furthermore, the encryption scheme is efficient since the proposed round function is lightweight and applied for only one round. This reduces the latency and the required resources as compared to traditional cryptographic schemes. The proposed approach is flexible as it can be applied in either selective, middle-full, or full mode. Also, the size of a sub-matrix is variable and can be changed according to the available memory size. Several security and performance tests are conducted to evaluate the effectiveness of the proposed solution. The results validate the robustness of the proposed scheme against almost all considered types of attacks and show an improvement in terms of latency and resources compared to current image-encryption schemes. Also, the results confirm the robustness of the proposed algorithm in protecting the contents of medical images.

This paper proposes a new algorithm for text encryption utilizing English words as a unit of encoding. The algorithm vanishes any feature that could be used to reveal the encrypted text through adopting variable code lengths for the English words, utilizing a variable-length encryption key, applying two-dimensional binary shuffling techniques at the bit level, and utilizing four binary logical operations with randomized shuffling inputs. English words that alphabetically sorted are divided into four lookup tables where each word has assigned an index. The strength of the proposed algorithm concluded from having two major components. Firstly, each lookup table utilizes different index sizes, and all index sizes are not multiples of bytes. Secondly, the shuffling operations are conducted on a two-dimensional binary matrix with variable length. Lastly, the parameters of the shuffling operation are randomized based on a randomly selected encryption key with varying size. Thus, the shuffling operations move adjacent bits away in a randomized fashion. Definitively, the proposed algorithm vanishes any signature or any statistical features of the original message. Moreover, the proposed algorithm reduces the size of the encrypted message as an additive advantage which is achieved through utilizing the smallest possible index size for each lookup table.

In order to solve the problems of low transmission efficiency and high transmission bit error rate in traditional transmission methods, a new secure transmission method of network communication data is designed based on symmetric key encryption algorithm. Based on the analysis of the security key theory, the agentless key publishing protocol is adopted to control the access of network communication data, so as to construct the ciphertext protocol. Then the key construction in the encryption process is completed by bilinear mapping method. On this basis, the encryption and decryption algorithm, dynamic key generation module and Shared key update module are combined to realize the secure transmission of network communication data. The experimental results show that the bit error rate of this method was kept below 1%, the time of transmission was below 80 s, and the VIM value exceeded 0.1, indicating that this method has the advantages of high data transmission efficiency, low bit error rate and safer transmission process.

Recent advancements in wireless technology have created an exponential rise in the number of connected devices leading to the internet of things (IoT) revolution. Large amounts of data are captured, processed and transmitted through the network by these embedded devices. Security of the transmitted data is a major area of concern in IoT networks. Numerous encryption algorithms have been proposed in these years to ensure security of transmitted data through the IoT network. Tiny encryption algorithm (TEA) is the most attractive among all, with its lower memory utilization and ease of implementation on both hardware and software scales. But one of the major issues of TEA and its numerous developed versions is the usage of the same key through all rounds of encryption, which yields a reduced security evident from the avalanche effect of the algorithm. Also, the encryption and decryption time for text is high, leading to lower efficiency in IoT networks with embedded devices. This paper proposes a novel tiny symmetric encryption algorithm (NTSA) which provides enhanced security for the transfer of text files through the IoT network by introducing additional key confusions dynamically for each round of encryption. Experiments are carried out to analyze the avalanche effect, encryption and decryption time of NTSA in an IoT network including embedded devices. The results show that the proposed NTSA algorithm is much more secure and efficient compared to state-of-the-art existing encryption algorithms.

Cloud computing has spread widely among different organizations due to its advantages, such as cost reduction, resource pooling, broad network access, and ease of administration. It increases the abilities of physical resources by optimizing shared use. Clients’ valuable items (data and applications) are moved outside of regulatory supervision in a shared environment where many clients are grouped together. However, this process poses security concerns, such as sensitive information theft and personally identifiable data leakage. Many researchers have contributed to reducing the problem of data security in cloud computing by developing a variety of technologies to secure cloud data, including encryption. In this study, a set of encryption algorithms (advance encryption standard (AES), data encryption standard (DES), Blowfish, Rivest-Shamir-Adleman (RSA) encryption, and international data encryption algorithm (IDEA) was compared in terms of security, data encipherment capacity, memory usage, and encipherment time to determine the optimal algorithm for securing cloud information from hackers. Results show that RSA and IDEA are less secure than AES, Blowfish, and DES). The AES algorithm encrypts a huge amount of data, takes the least encipherment time, and is faster than other algorithms, and the Blowfish algorithm requires the least amount of memory space.

The most used asymmetric encryption algorithm nowadays is RSA. It may become insecure regarding advances in the field of quantum computers. It is the reason why the National Institute of Standards and Technologies introduces the challenges of choosing a new post-quantum encryption standard. Initially, NIST received 82 submissions comprising key encapsulation mechanisms and digital signature schemes. However, only 69 of them were formally accepted after an initial review. In July 2022, NIST selected some algorithms for standardization. For the key encapsulation mechanism, Kyber was selected, and for digital signatures, Dilithium Falcon and SPHINCS+. After the third round concluded, NIST indicated it would continue to evaluate some of the alternative algorithms that were not selected as finalists in the third round. This ongoing evaluation is informally referred to as a \"fourth round.\" Initially, there were four participants - BIKE, Classic McEliece, SIKE, and HQC. However, the SIKE downfall with the Castryck-Decru attack was introduced in July 2022, and the HQC algorithm was chosen for standardization in March 2025. In our research, we examine all functions of BIKE, Classic McEliece, and the HQC from the point of view of time and memory consumption. The results obtained will help us during the implementation of the BIKE algorithm on ESP32.