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In the context of the widespread application of robotics technology across numerous industrial sectors, the security of data communication in industrial robot arms emerges as a paramount concern. These robotic arms are instrumental in enhancing productivity and safety in a variety of fields, including but not limited to transportation, agriculture, construction, and mining, by automating tasks and reducing human exposure to hazardous conditions. This paper proposes a novel hybrid encryption strategy to fortify the data security of these industrial robot arms, particularly focusing on preventing data breaches during both wired and wireless communications. The suggested encryption framework combines the strengths of Elliptic Curve Cryptography (ECC) for its efficient asymmetric encryption capabilities, ChaCha20 for its rapid and low-energy symmetric encryption, and Poly1305 for ensuring data integrity through its message authentication code (MAC) algorithm. By leveraging these technologies, the paper outlines the development and application of a secure communication protocol, implemented using Python, that guarantees the confidentiality and integrity of data shared among robot arms and between these arms and their control systems. Additionally, the research conducts a comparative analysis between the ECC-based method and the RSA encryption standard, highlighting the efficiency and effectiveness of the proposed hybrid approach through various tests on different data types and sizes. The findings illustrate a marked improvement in safeguarding against potential data leaks, thereby significantly contributing to the enhancement of industrial robot arms' data security. This study not only addresses the pressing need for robust data protection mechanisms in the face of evolving cyber threats but also sets a benchmark for future research in the field of industrial robotics security. [ABSTRACT FROM AUTHOR]

In today's world, encryption is crucial for protecting sensitive data. Neural networks can provide security against adversarial attacks, but meticulous training and vulnerability analysis are required to ensure their effectiveness. Hence, this research explores hybrid encryption based on a generative adversarial network (GAN) for improved message encryption. A neural network was trained using the GAN method to defend against adversarial attacks. Various GAN training parameters were tested to identify the best model system, and various models were evaluated concerning their accuracy against different configurations. Neural network models were developed for Alice, Bob, and Eve using random datasets and encryption. The models were trained adversarially using the GAN to find optimal parameters, and their performance was analyzed by studying Bob's and Eve's accuracy and bits error. The parameters of 8,000 epochs, a batch size of 4,096, and a learning rate of 0.0008 resulted in 100% accuracy for Bob and 52.14% accuracy for Eve. This implies that Alice and Bob's neural network effectively secured the messages from Eve's neural network. The findings highlight the advantages of employing neural network-based encryption methods, providing valuable insights for advancing the field of secure communication and data protection. [ABSTRACT FROM AUTHOR]

Abstract Personalized medical data privacy and secure storage protection face serious challenges, especially in terms of data security and storage efficiency. Traditional encryption and storage solutions cannot meet the needs of modern medical data protection, which has led to an urgent need for new data protection strategies. Research personalized medical data privacy and secure storage protection based on hybrid encryption, in order to improve the security and efficiency of data storage. A hybrid encryption mechanism was proposed, which uses user attributes as keys for data encryption. The results show that the storage consumption of user attribute keys increases with the number of user attributes, but the consumption of hybrid encryption privacy storage technology is much smaller than that of traditional schemes. In the test, when the number of users increased to 30, the processing time first reached 1200 ms. During the increase in data volume, both test data and real data showed a brief decrease in attack frequency, but after the data volume reached 730–780, the attack frequency increased. It is worth noting that the performance of test data is better than that of real data. Personalized medical data privacy and secure storage protection based on hybrid encryption can not only effectively improve data security and reduce the risk of attack, but also greatly outperform traditional solutions in storage consumption and processing time. It has important practical significance for modern medical data storage protection.

By side-channel attacks, a fraction part of secret keys used in cryptographic schemes could be leaked to adversaries. Recently, adversaries have realized practical side-channel attacks so that these existing cryptographic schemes could be broken. Indeed, researchers have invested and proposed a good approach to withstand such attacks, called as leakage-resilient cryptography. Very recently, several leakage-resilient anonymous multi-receiver encryption (LR-AMRE) schemes based on various public-key systems were also proposed. However, these LR-AMRE schemes are not suitable for a heterogeneous public-key environment under which an authorized receiver group includes heterogeneous receivers under various PKS settings and these receivers have various types of secret/public key pairs. In this article, we propose the $first$ leakage-resilient anonymous heterogeneous multi-receiver hybrid encryption (LR-AHMR-HE) scheme for the heterogeneous public-key system settings. A new framework and associated adversary games of the LR-AHMR-HE scheme are defined. In the adversary games, adversaries are admitted to continuously intercept a fraction part of secret keys. Under the adversary games, formal security proofs are provided to show that the proposed scheme is secure against two types of adversaries (illegitimate user and malicious authority). Comparisons with several related previous schemes are demonstrated to present the merits of our scheme.

With the development of the big data era, the amount of data has entered an explosive growth phase. Limited by the constraints of cost, efficiency, and security of self-built storage systems, enterprises are forced to outsource files to cloud storage systems. However, the lack of file security and auditability in cloud storage systems continues to threaten the security of outsourced files. This paper designs and implements a large file security outsourcing and sharing method based on blockchain (BFSOut). It uses Hyperledger Fabric and Interplanetary File System (IPFS) as the underlying storage engine, which solves the problem of cloud storage security issues. In order to ensure the security of outsource files, the client-side offline encryption and decryption is used. Furthermore, a dynamic hybrid encryption scheme is adopted, making the overall encryption effect more efficient. Meanwhile, BFSOut effectively reduces the time consumption of large file encryption and decryption by 20%–30% through the parallel block encryption and decryption model. Experimental performance and security analysis show that the method has good performance and safety. [ABSTRACT FROM AUTHOR]

As technology is improving and changing rapidly, cloud security has become a challenging task. Consequently, there is a need for more powerful and robust techniques to secure the cloud. Meanwhile, due to the huge size of the provided big data on the cloud, other techniques and methods should be utilized to improve big data analytics and processing. The paper aims to provide a framework for secure and efficient processing and analysis of big data using a double layer of security that is based on Elliptical Curve Cryptography (ECC) and Fully Homomorphic Encryption (FHE). Additionally, a distributed model has been defined to partition big data into smaller data sizes processed by different numbers of virtual CPUs. In the defined distributed model, many virtual machines process different partitions of data parallelly and simultaneously to speed up the processing time of data. KMeans clustering algorithm is used in three datasets as an instance of data analytics to test the suggested framework. Furthermore, the produced results are compared with a centralized-based model to assess the productivity and efficiency of the distributed model. Besides, the principal component analysis (PCA) is applied to the used clustering algorithm to diminish the required clustering time by the distributed model. The results indicate that the clustering time can be reduced by up to 91%, and even with 18% more reduction in the execution time using the distributed model. The recommended solution can improve the effectiveness of big data analytics while guaranteeing the security of such data. [ABSTRACT FROM AUTHOR]

Personalized medical data privacy and secure storage protection face serious challenges, especially in terms of data security and storage efficiency. Traditional encryption and storage solutions cannot meet the needs of modern medical data protection, which has led to an urgent need for new data protection strategies. Research personalized medical data privacy and secure storage protection based on hybrid encryption, in order to improve the security and efficiency of data storage. A hybrid encryption mechanism was proposed, which uses user attributes as keys for data encryption. The results show that the storage consumption of user attribute keys increases with the number of user attributes, but the consumption of hybrid encryption privacy storage technology is much smaller than that of traditional schemes. In the test, when the number of users increased to 30, the processing time first reached 1200 ms. During the increase in data volume, both test data and real data showed a brief decrease in attack frequency, but after the data volume reached 730–780, the attack frequency increased. It is worth noting that the performance of test data is better than that of real data. Personalized medical data privacy and secure storage protection based on hybrid encryption can not only effectively improve data security and reduce the risk of attack, but also greatly outperform traditional solutions in storage consumption and processing time. It has important practical significance for modern medical data storage protection. [ABSTRACT FROM AUTHOR]

Data and information secrecy during storage or transmission has been preserved through the use of cryptography. Consequently, cryptography studies have also progressed from traditional Caesar cipher to the existing cryptographic protocols depending on quantum computing, starting with the latest modular arithmetic-based cryptosystems. The strength of modular arithmetic ciphers lies in the fact that they are computationally difficult to break, but with the advent of quantum computing, even these issues can be cracked with in polynomial time. Research on post-quantum cryptography began in response to this danger, with the goal of creating post-quantum algorithms that are immune to quantum computing. However, cryptographic methods confront a number of other problems, including, but not limited to, availability, integrity, and vulnerability. Despite the researchers' successes, security is still a major issue for Quantum Computing. Because of its many advantages, cyberspace has quickly become the most common medium for disseminating information. Because of the exponential growth of science and technology, notably quantum computers, cyber security is now the top priority for the Internet and other wireless systems. The fundamental goal of this work is to create a Hybrid Quantum Cryptosystem that can be implemented in Wireless Body Sensor Networks. Using a series of comparisons with existing algorithms, we will determine how well our suggested hybrid algorithm operates in terms of key length, key generation time, decryption and encryption timings, and overall speed. The proposed approach attains 10.3 minimal rate of error, which outperforms the existing state-of-art techniques. [ABSTRACT FROM AUTHOR]

Using multiple, individual encryption schemes is a well-established method to increase the overall security of encrypted data. These so-called multiple encryption or hybrid schemes have regained traction in the context of public-key cryptography due to the rise of quantum computers, since it allows the combination of well-known classical encryption schemes with novel post-quantum schemes. In this paper, we conduct a survey of the state-of-the-art public-key multiple encryption (M-PKE) schemes. For the first time, we describe the most relevant M-PKE schemes in detail and discuss their security in a unified model, which allows better comparison between the schemes. Hence, we compare the security, efficiency, and complexity of the schemes and offer recommendations for usage based on common use cases. Our survey emphasizes the importance of being deliberate when combining encryption schemes, as small nuances can easily break security. [ABSTRACT FROM AUTHOR]

In view of the problems of inefficient data encryption, non-support of malicious user revocation and data integrity checking in current smart grid data sharing schemes, this paper proposes a blockchain-based multi-authority revocable data sharing scheme in the smart grid. Using online/offline encryption technology with hybrid encryption technology enhances the encryption performance for the data owner. The use of user binary tree technology enables the traceability and revocability of malicious users. The introduction of multiple attribute authorization authorities eliminates the threat of collusive attacks that exist in traditional data-sharing schemes. In addition, the semi-honest problem of third-party servers is solved by uploading data verification credentials to the blockchain. The security analysis results show that the scheme can resist selective plaintext attacks and collusion attacks. The performance analysis results show that the proposed scheme has lower computational overhead and better functionality than similar schemes, which is suitable for secure data sharing in smart grids.

The development of technology at the present time leads to an increase in the use of electronic commerce due to the increase in demand processes, whether selling or buying goods, products, services, or payment requests, and that the transfer of information the merchants is sensitive and important information, and this information or operations may be subject to penetration or attacks. In this research, we designed a protocol that integrates the Fernet algorithm and the ElGamal algorithm, and we use the Data Leakage Detection Technology (DLD) to safeguard e-commerce transaction data. This protocol provid high security for information, and the integration of algorithms provides high security and strong performance for information transactions that are difficult to hack. We incorporate encryption algorithms to achieve a high level of security and performance. The proposed protocol is higher in security and performance than the algorithms of previous studies. [ABSTRACT FROM AUTHOR]

Today, with the continuous advancement of technological developments, autonomous and semi-autonomous vehicles facilitate our operations in many areas such as personal and commercial transportation, agriculture, construction and mining, research and exploration. Among these vehicles are autonomous mobile robots (AMRs), which are frequently preferred in factories. One of the reasons why AMRs are preferred is that there is insufficient manpower in the areas where they are used. Secondly, these robots can eliminate risky situations that can threaten the health of workers. In addition, AMRs have the potential to save manpower. In this study, we aim to provide data security for AMRs using wireless communication technologies by using a hybrid encryption method. The security performance of asymmetric encryption and the fast communication advantages of symmetric encryption make it necessary to use both encryption methods together for AMRs. In the hybrid encryption approach, the asymmetric encryption method ECC (Elliptic Curve Cryptography) and the symmetric encryption method AES (Advanced Encryption Standard) are used together. ECDSA (Elliptic Curve Digital Signature Algorithm), the digital signature method based on the ECC encryption method, was used as a reference. In the AES encryption method, GCM (Galois/Counter Mode) is preferred since verification is performed in addition to encryption. In this study, AMRs, which communicate with each other or with the controller system and act as data senders, were encrypted using ECDSA-AES/GCM hybrid encryption method using Python programming language and their performance was evaluated. In this way, the protection of the confidentiality and integrity of the transmitted data in case of a possible data leakage during wireless communication will be examined. As a result, this proposed method aims to provide an important step in terms of data security for autonomous mobile robots using wireless communication. [ABSTRACT FROM AUTHOR]

A hybrid encryption scheme for multi-image is proposed in this paper, which can encrypt different types and different sizes of images simultaneously. First, the order of the discrete map is extended from integer order to unequal fractional order. By choosing suitable parameters, the map exhibits chaotic behavior, and using the map for the designed image encryption system can enlarge the key space of the cryptosystem. Then, the plain images are pixel substituted. The chaotic sequences produced from the unequal fractional-order discrete map are shaped and sorted; the index sequences generated by the sorting are used to replace plain image pixels. After plain image pixels are replaced, DNA encoding, selective diffusion, and gene exchange are performed. The statistical properties of the images are masked by the diffusion algorithm. Finally, simulation experiments and security test results show that the designed multi-image hybrid encryption algorithm is effective and secure. [ABSTRACT FROM AUTHOR]

With the continuous destruction of the data transmitted in the protection network system, data encryption is an important research object in the network security technology, and it is the core to ensure the correctness of the data transmitted in the network. Through further research and Analysis on the basic technologies of cryptography and data transmission, combined with several common data encryption algorithms and data communication methods, the Windows sock communication method and mixed encryption module of mixed encryption data transmission system are designed and studied. In this module, a pair of RSA keys are generated by the software system first, which are imported into the hybrid encryption process to encrypt the des keys randomly generated in the system, which optimizes the system design objectives and the main functions of the system. In this paper, through further careful and in-depth research on the two classical encryption algorithms DES (Data Encryption Standard) and RSA (Rivest-Shamir-Adleman), we propose and de-sign a method of heterogeneous network data security transmission based on hybrid encryption. The experiment is programmed by visual c++, and the mixed encryption data transmission system is simulated and tested. The experimental results show that the design and implementation of the hybrid encryption data transmission system overcomes the shortcomings of the previous systems, such as slow speed and difficult key transmission. [ABSTRACT FROM AUTHOR]

In order to ensure the location privacy of mobile nodes when using location-based services,a mobile privacy protection scheme for location based service(LBS)based on random onion routing is proposed.This scheme integrates random onion routing and hybrid encryption to ensure the privacy of mobile node location and the security of query requests.The mobile node randomly selects several nodes in the network before sending the query request to the LBS server to build an onion path,and forwards the query request along this path in turn until the LBS server receives the message.Then,the LBS sends the query result to the sen-ding node along the reverse direction of the onion path.In order to realize the anonymity of the sending node,the addresses of each layer on the randomly constructed onion path are encrypted with a combination of symmetric encryption and asymmetric encryption.In this way,layers of encryption are used to generate the final onion path.Each hop node in the path can get only its next-hop node.Neither the LBS server nor any relay node in the onion routing path can know which node is the sending node,so that the location privacy of the sending node can be kept.On the other hand,in order to ensure that no third party can get the query request or query result,the sending node first uses a symmetric key to encrypt the query request.Then it uses the public key of the LBS server to encrypt the symmetric key.Finally it attaches the symmetric key ciphertext to the query request ciphertext and send it to the LBS server.The LBS server will also return the encrypted query result.Experimental results show that the average response time of this scheme increases slowly with the increase of the number of nodes in the system.The average response time will not increases sharply with the increase of the number of nodes,which will lead to system paralysis.So the system has good stability and scalability.The onion path is randomly selected which does not depend on a specific node,so the scheme has better robustness.

Using multiple, individual encryption schemes is a well-established method to increase the overall security of encrypted data. These so-called multiple encryption or hybrid schemes have regained traction in the context of public-key cryptography due to the rise of quantum computers, since it allows the combination of well-known classical encryption schemes with novel post-quantum schemes. In this paper, we conduct a survey of the state-of-the-art public-key multiple encryption (M-PKE) schemes. For the first time, we describe the most relevant M-PKE schemes in detail and discuss their security in a unified model, which allows better comparison between the schemes. Hence, we compare the security, efficiency, and complexity of the schemes and offer recommendations for usage based on common use cases. Our survey emphasizes the importance of being deliberate when combining encryption schemes, as small nuances can easily break security.

Nowadays, cryptographic systems' designers are facing significant challenges in their designs. They have to constantly search for new ideas of fast unbreakable algorithms with a very powerful key generator. In this paper, we propose a novel hybrid neural-cryptography methodology. It depends on new rule of very fast Backpropagation (BP) instant machine learning (ML). This proposed Hybrid Cryptography system is constructed from Encryptor and Decryptor based on the asymmetric Autoencoder type. The Encryptor encrypts and compresses a set of data to be instant code (i-code) using public key. While the Decryptor recovers this i-code (ciphered-data) based on two keys together. The first is the private key and the other is called instant-key (i-key). This i-key is generated from 3 factors as well (the original data itself, the generated i-code and the private key). The i-key is changing periodically with every transformation of plain data set, so it is powerful unpredictable key against the brute force. [ABSTRACT FROM AUTHOR]

With the rapid development of the genomic sequencing technology, the cost of obtaining personal genomic data and effectively analyzing it has been gradually reduced. The analysis and utilization of genomic data gradually entered the public view, and the leakage of genomic data privacy has attracted the attention of researchers. The security of genomic data is not only related to the protection of personal privacy, but also related to the biological information security of the country. However, there is still no effective genomic data privacy protection scheme using Shangyong Mima(SM) algorithms. In this paper, we analyze the widely used genomic data file formats and design a large genomic data files encryption scheme based on the SM algorithms. Firstly, we design a key agreement protocol based on the SM2 asymmetric cryptography and use the SM3 hash function to guarantee the correctness of the key. Secondly, we used the SM4 symmetric cryptography to encrypt the genomic data by optimizing the packet processing of files, and improve the usability by assisting the computing platform with key management. Software implementation demonstrates that the scheme can be applied to securely transmit the genomic data in the network environment and provide an encryption method based on SM algorithms for protecting the privacy of genomic data.

With the improved hardware storage capabilities and the rapid development of artificial intelligence image recognition technology, information is becoming image-oriented. Increasingly sensitive image data needs to be processed. When facing a large amount of real-time sensitive image data encryption and decryption, ensuring both the speed and the security is an urgent demand. This paper proposes an original triple-hybrid encryption system for a real-time sensitive image acquisition chip. This encryption system optimizes the symmetric encryption algorithm AES, asymmetric encryption algorithm ECC, and chip authentication algorithm PUF in pursuit of security, calculation speed, and to ensure that it is lightweight. The three optimized algorithms are further mixed and reused on the circuit level, to ensure mutual protection while making full use of their advantages. Apart from sensitive image protection at the algorithm level, the image chip itself is also protected by an innovative PUF chip authentication method that prevents it from being tampered with and copied. Triple-hybrid encryption system hardware implementation achieves a frequency of 132.5 MHz under the Virtex-5 FPGA with an area of 2834 Slices; with Virtex-7 FPGA, it reaches a frequency of 137.6 MHz with an area of 2716 Slices. The system is also implemented on SMIC 40 nm ASIC, and the clock frequency reaches 480 MHz and the area is 94,812.4 μ m 2 . In terms of computing speed, the peak image encryption speed is 6.15 Gb/s, which meets the real-time image encryption requirement. In terms of hardware resource usage, AES reduced the hardware area by 60.1% compared with the results in other literature, ECC reduced the hardware area by 43.4%, and the PUF hardware area decreased exponentially with the increase in information entropy. The implementation of the three algorithms is reasonable and cost-effective, and the mixture of algorithms does not increase the required capacity of the hardware resource. The triple-hybrid encryption system cooperates with the image acquisition subsystem, storage subsystem, and asynchronous clock subsystem through software control to realize a complete triple-hybrid encryption SoC chip solution, and was successfully taped-out under the SMIC 40 nm process with all constraints passed and a total area of 10.59 mm 2 . [ABSTRACT FROM AUTHOR]

With the rapid development of electronic information technology, the security of data has become increasingly serious. The traditional single cipher algorithm can not meet the requirements any more. In order to solve these problems, this paper proposed a hardware design scheme of high-speed hybrid encryption system based on SM2, SM3, SM4, in which the hardware structure of SM2 and SM4 algorithms is optimized. Besides, this paper optimized the SM2 algorithm with Karatsuba-Ofman modular multiplier and parallel with point operation. For SM4 algorithm, this paper designed a subpipelining hardware architecture based on composite field S-box so as to improve its throughout. The experimental results showed that all the algorithm circuits implemented by the system have high performance: the point multiplication time of SM2 was 68.37 μs; the hash generation of SM3 only took 0.71 μs; the throughput of SM4 was up to 53.76 Gbps. Compared with the SM2 algorithm with the same security, this hybrid system had 26.67% less encryption time. By comparing and analyzing with related work, it can be proved that this scheme has certain advantages in security and encryption and decryption performance. [ABSTRACT FROM AUTHOR]

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The development of increasingly sophisticated quantum computers poses a long-term threat to current cryptographic infrastructure. This has spurred research into both quantum-resistant algorithms and how to safely transition real-world implementations and protocols to quantumresistant replacements. This transition is likely to be a gradual process due to both the complexity and cost associated with transitioning. One method to ease the transition is the use of classical-quantum hybrid schemes, which provide security against both classical and quantum adversaries. We present a new combiner for creating hybrid encryption schemes directly from traditional encryption schemes. Our construction is the only existing proposal in the literature with IND-CCA-security in the classical and quantum random oracle models, respectively. [ABSTRACT FROM AUTHOR]

In general, confidentiality is an important issue when transferring data in the medical field. Medical data hacking is a trending business followed by many hackers in the black market. To deal with such issues, cloud-based security solutions are being developed day by day. Design complexity is a big issue in all conventional methods, even in various technological facilities for security-related issues in the medical field. This paper combines elliptic curve cryptography (ECC) and blockchain encryption to develop an efficient steganography technique for data hiding in the multiple input multiple output-orthogonal frequency-division multiplexing (MIMO-OFDM) channel. This hybrid encryption method is named reconfigurable area-power efficient steganography (RAPS) for MIMO-OFDM channel coding. Generally, the performance of ECC encryption is affected by the design complexity due to the use of several units. Mainly, the use of complex multiplier units creates a major problem in ECC design. Therefore, the Montgomery multiplier is used in the proposed work for ECC design because it provides faster multiplication with simpler operations. Also, the combination of blockchain technology with ECC provides additional security features like immutability, decentralization and elimination of third-party. This hybrid encryption technique uses Low-Density Parity Check for efficient data transmission between sender-receiver. The proposed RAPS technique with MIMO-OFDM design is implemented using MATLAB and Xilinx platform. The performance of the RAPS technique is compared with conventional encryption methods like Advanced Encryption Standard and ECC in terms of area utilization, operating frequency and power consumption. [ABSTRACT FROM AUTHOR]