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Smart medical devices and the internet of things (IoT) have enhanced healthcare systems by allowing remote monitoring of patient's health. Because of the unexpected increase in the number of diabetes patients, it is critical to regularly evaluate patients' health conditions before any significant illness occurs. As a result of transmitting a large volume of sensitive medical data, dealing with IoT data security issues remains a difficult challenge. This paper presents a secure remote diabetes monitoring (SR-DM) model that uses hybrid encryption, combining the advanced encryption standard and elliptic curve cryptography (AES-ECC), to ensure the patients' sensitive data is protected in IoT platforms based on the cloud. The health statuses of patients are determined in this model by predicting critical situations using machine learning (ML) algorithms for analyzing medical data sensed by smart health IoT devices. The results reveal that the AES-ECC approach has a significant influence on cloud-based IoT systems and the random forest (RF) classification method outperforms with a high accuracy of 91.4%. As a consequence of the outcomes obtained, the proposed model effectively establishes a secure and efficient system for remote health monitoring. [ABSTRACT FROM AUTHOR]

Cryptography aims to design algorithms for the protection of important data transmitted over unsecured networks. These algorithms encrypt the data and render it incomprehensible even if it is captured by enemies. Today's data encryption standard is the AES algorithm. The most important and nonlinear unit in the AES algorithm is the s-box structure. The S-box provides the mixing process in the algorithm, that is, the confusion. An s-box structure with a high nonlinearity value greatly increases the security against various attacks. Therefore, s-box is of vital importance in an encryption algorithm. When we look at the literature, chaos-based s-box structures are frequently used. However, the nonlinearity value of s-boxes produced with chaos is low. In this article, a new, fast, and very simple method is proposed to increase the nonlinearity value of chaos-based s-box structures. In the proposed method, the nonlinearity value is calculated by changing the places of the elements respectively. When the nonlinearity value increases, the s-box is updated, and the next element is passed. In this way, many iterations are not looked at in vain. This saves a lot of time. As a result of the analysis, it has been proven that the s-box structure obtained by the proposed method is cryptographically strong and has a high nonlinearity value. It is thought that the proposed method will provide many advantages for future cryptography applications. [ABSTRACT FROM AUTHOR]

In a cloud environment, outsourced graph data is widely used in companies, enterprises, medical institutions, and so on. Data owners and users can save costs and improve efficiency by storing large amounts of graph data on cloud servers. Servers on cloud platforms usually have some subjective or objective attacks, which make the outsourced graph data in an insecure state. The issue of privacy data protection has become an important obstacle to data sharing and usage. How to query outsourcing graph data safely and effectively has become the focus of research. Adjacency query is a basic and frequently used operation in graph, and it will effectively promote the query range and query ability if multi-keyword fuzzy search can be supported at the same time. This work proposes to protect the privacy information of outsourcing graph data by encryption, mainly studies the problem of multi-keyword fuzzy adjacency query, and puts forward a solution. In our scheme, we use the Bloom filter and encryption mechanism to build a secure index and query token, and adjacency queries are implemented through indexes and query tokens on the cloud server. Our proposed scheme is proved by formal analysis, and the performance and effectiveness of the scheme are illustrated by experimental analysis. The research results of this work will provide solid theoretical and technical support for the further popularization and application of encrypted graph data processing technology. [ABSTRACT FROM AUTHOR]

Ensuring the protection of digital data is of utmost importance in our current reliance on network operations. However, security measures such as data encryption often result in decreased performance speed. This paper enhanced the 128-bit version of the advanced encryption standard (AES) by substituting the MixColumns function with a permutation-based approach and decreasing the overall number of rounds. The evaluation results indicate a substantial enhancement in the speed of encryption and decryption, with a 76.76% improvement in encryption time and a 55.46% improvement in decryption time. Furthermore, it is important to mention that the modifications implemented in the standard AES did not compromise its security in relation to the strict avalanche criterion. The avalanche effect of the modified AES is 52.92%, surpassing the minimum requirement of 50%. Finally, the modified AES demonstrated a 31.12% increase in throughput for encryption and a 25.50% increase for decryption when compared to the original AES, using the sample dataset. [ABSTRACT FROM AUTHOR]

Cloud computing is a rapidly advancing paradigm that enables users to access various services and resources anytime, anywhere. With this advancement, security has become a major concern for business organisations and individuals, and hence, it is essential to ensure that the services are provided with high data security. Numerous researches have focused on devising effective techniques to enhance data security. However, with the increasing connectivity, security still remains to be a major challenge. This paper devises a novel data protection scheme in the cloud by using the Twofish encryption algorithm and a key generation scheme with the Bald Eagle Pelican Optimization (BEPO) Algorithm. The proposed Twofish+BEPO_KeyGen is implemented in various phases, like initialization, registration, key generation, data encryption, authentication, validation and data sharing, and data decryption. Here, the Twofish algorithm is used to encrypt the data that has to be outsourced to the cloud, and for encryption, the security key required is generated by the BEPO algorithm. The efficacy of the Twofish+BEPO_KeyGen approach is examined by considering metrics, like memory usage, validation time, normalized variance, and conditional privacy, and is detected to have achieved values of 76.3 MB, 37.278 s, 1.665, and 0.926, correspondingly. [ABSTRACT FROM AUTHOR]

Addressing privacy concerns is critical in smart manufacturing where sensitive data is used for machine learning. Data protection is essential to ensure model accuracy while upholding data privacy. Homeomorphic encryption, an algorithm for privacy-preserving machine learning, achieves this by transforming data using a neural network with secret key weights. This process conceals private data while retaining the potential to learn classification models from the anonymized data. This paper introduces a comprehensive quality metric to assess homeomorphic encryption across conflicting criteria: security (regarding private data), machine learning adaptability (tolerance), and efficiency (regarding needed extra resources). Through experiments on various datasets, the metric proves its effectiveness in guiding optimal encryption parameter selection. Our findings highlight homeomorphic encryption's strong overall quality, positioning it as a valuable Industry 4.0 solution. By offering a simpler alternative to fully homomorphic encryption, it effectively addresses privacy concerns and enhances data usability in the context of smart manufacturing. [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]

Currently, the size of multimedia data is rising gradually from gigabytes to petabytes, due to the progression of a larger quantity of realistic data. The majority of big data is conveyed via the internet and they were accumulated on cloud servers. Since cloud computing offers internet-oriented services, there were a lot of attackers and malevolent users. They always attempt to deploy the private data of users without any right access. At certain times, they substitute the real data by any counterfeit data. As a result, data protection has turned out to be a noteworthy concern in recent times. This paper aims to establish an optimization-based privacy preservation model for preserving multimedia data by selecting the optimal secret key. Here, the encryption and decryption process is carried out by Improved Blowfish cryptographic technique, where the sensitive data in cloud server is preserved using the optimal key. Optimal key generation is the significant procedure to ensure the objectives of integrity and confidentiality. Likewise, data restoration is the inverse process of sanitization (decryption). In both the cases, key generation remains a major aspect, which is optimally chosen by a novel hybrid algorithm termed as "Clan based Crow Search with Adaptive Awareness probability (CCS-AAP). Finally, an analysis is carried out to validate the improvement of the proposed method. [ABSTRACT FROM AUTHOR]

In order to improve data security and network data security in the digital economy-driven environment, this paper combines data security technology and network security technology to build a digital economy security management and control system. Moreover, this paper describes the data encryption of the data owners before the framework index and the composition and construction method of the corresponding EncIR tree, and analyzes the spatial keyword group query algorithm on the EncIR tree. In addition, this paper analyzes the experimental performance of index building and spatial query, and builds an intelligent digital economy security system on the basis of these algorithms. The experimental research results verify that the data security technology and network data system driven by the digital economy have good security performance, and on this basis, follow-up security regulations can be formulated. [ABSTRACT FROM AUTHOR]

Patient privacy and data protection have been crucial concerns in Ehealthcare systems for many years. In modern-day applications, patient data usually holds clinical imagery, records, and other medical details. Lately, the Internet of Medical Things (IoMT), equipped with cloud computing, has come out to be a beneficial paradigm in the healthcare field. However, the openness of networks and systems leads to security threats and illegal access. Therefore, reliable, fast, and robust security methods need to be developed to ensure the safe exchange of healthcare data generated from various image sensing and other IoMT-driven devices in the IoMT network. This paper presents an image protection scheme for healthcare applications to protect patients' medical image data exchanged in IoMT networks. The proposed security scheme depends on an enhanced 2D discrete chaotic map and allows dynamic substitution based on an optimized highly-nonlinear S-box and diffusion to gain an excellent security performance. The optimized S-box has an excellent nonlinearity score of 112. The new image protection scheme is efficient enough to exhibit correlation values less than 0.0022, entropy values higher than 7.999, and NPCR values around 99.6%. To reveal the efficacy of the scheme, several comparison studies are presented. These comparison studies reveal that the novel protection scheme is robust, efficient, and capable of securing healthcare imagery in IoMT systems. [ABSTRACT FROM AUTHOR]

The subject matter of this article is the processes of increasing information security in communication systems to solve applied problems that are critical in the transmission of confidential data. The goal is to develop a multistage method for protecting information from unauthorized access, based on probabilistic encryption integration, error-correcting code, and error decorrelation. The tasks to be solved are as follows: to develop a probabilistic encryption algorithm that considers the entropy of the characters' appearance in a message; to implement iterative coding with variable parameters of the information bits matrix; and to implement error decorrelation based on the generated matrix by interleaving information and check bits according to a given algorithm. Methodology: theory of signal communication and signal processing, theory of cryptography, theory of noiseresistant codes, probability theory, statistical analysis. The following results were obtained: a multi-stage method for protecting information from unauthorized access was proposed, in which at each step of data conversion, information secrecy is increased; probabilistic encryption was implemented, which considers the entropy of a discrete source of information when forming a space of random combinations; based on an iterative code with specified matrix parameters, an additional increase in the space of random combinations was implemented; error decorrelation reduces the multiplicity of errors in codewords and ensures mixing of bits according to a predetermined law. Conclusions. The scientific novelty of the results obtained is as follows: 1) an improved method of information protection from unauthorized access is proposed, based on probabilistic encryption integration, interference-resistant coding, and error decorrelation; 2) increasing information concealment is realized by eliminating the main shortcomings of probabilistic encryption, which did not take into account the entropy of the symbols of the open message; 3) it is proposed to form the space of random combinations taking into account the average probability of the appearance of a symbol in open texts, which will allow the output of a probabilistic cipher to form a stream of random combinations, which, according to its statistical properties, is close to the uniform distribution law; 4) further development of information protection methods based on interference-resistant coding and error decorrelation with encryption functions is received; 5) a further development of the statistical encryption method is the use of all redundant elements for both probabilistic encryption and interference-resistant coding. [ABSTRACT FROM AUTHOR]

Nonvolatile organic photonic transistor (OPT) memories have attracted widespread attention due to their nondestructive readout, remote controllability, and robust tunability. Developing electrets with similar molecular structures but different memory behaviors and light‐responsive features is crucial for light‐wavelength‐modulated data encryption. However, reported OPT memories have yet to meet this challenge. Here a new electret molecule ("H‐PDI") is developed via reconfiguring the linear perylene diimide molecule ("L‐PDI") to a helical shape. Respectively incorporating H‐PDI and L‐PDI into the floating gate layer results to H‐PDI OPT and L‐PDI OPT. Attributing to their remarkably different electronic structures and energy bandgaps, H‐PDI OPT and L‐PDI OPT preferably respond to 405 and 532 nm light irradiation, respectively. Upon electrical programming, data can be written and stored in both memories with good retention features and a high "1"/"0" state current ratio over 105, though the data can only be erased by light with correct wavelengths, rather than the electrical field. Moreover, data stored in a memory array consisting of both H‐PDI OPT and L‐PDI OPT can only be read out by correct inputs, and wrong inputs will lead to highly deceptive outputs. This study provides a general design strategy of OPT for advanced data encryption and protection. [ABSTRACT FROM AUTHOR]

The objective of this review was to examine the different biometric data encryption techniques or algorithms used in authentication for information security. Consequently, the PRISMA methodology was used to select articles in different databases during the period between 2019 and 2023. The databases used were SCOPUS, SCIELO and GOOGLE ACADEMICO, where when applying the proposed inclusion and exclusion criteria, they were considered 13 articles for this research. In this way, it was possible to notice the need to apply encryption algorithms as a form of attack prevention and aimed at meeting the objectives of information security, the most used being AES (Advanced Encryption Standard) and encryption chaotic. [ABSTRACT FROM AUTHOR]

Multi-Source data plays an important role in the evolution of media convergence. Its fusion processing enables the further mining of data and utilization of data value and broadens the path for the sharing and dissemination of media data. However, it also faces serious problems in terms of protecting user and data privacy. Many privacy protectionmethods have been proposed to solve the problemof privacy leakage during the process of data sharing, but they suffer fromtwo flaws: 1) the lack of algorithmic frameworks for specific scenarios such as dynamic datasets in the media domain; 2) the inability to solve the problem of the high computational complexity of ciphertext in multi-source data privacy protection, resulting in long encryption and decryption times. In this paper, we propose a multi-source data privacy protection method based on homomorphic encryption and blockchain technology, which solves the privacy protection problem ofmulti-source heterogeneous data in the dissemination ofmedia and reduces ciphertext processing time.We deployed the proposedmethod on theHyperledger platformfor testing and compared it with the privacy protection schemes based on k-anonymity and differential privacy. The experimental results showthat the key generation, encryption, and decryption times of the proposedmethod are lower than those in data privacy protection methods based on k-anonymity technology and differential privacy technology. This significantly reduces the processing time ofmulti-source data, which gives it potential for use in many applications. [ABSTRACT FROM AUTHOR]

There are many cloud data security techniques and algorithms available that can be used to detect attacks on cloud data, but these techniques and algorithms cannot be used to protect data from an attacker. Cloud cryptography is the best way to transmit data in a secure and reliable format. Various researchers have developed various mechanisms to transfer data securely, which can convert data from readable to unreadable, but these algorithms are not sufficient to provide complete data security. Each algorithm has some data security issues. If some effective data protection techniques are used, the attacker will not be able to decipher the encrypted data, and even if the attacker tries to tamper with the data, the attacker will not have access to the original data. In this paper, various data security techniques are developed, which can be used to protect the data from attackers completely. First, a customized American Standard Code for Information Interchange (ASCII) table is developed. The value of each Index is defined in a customized ASCII table. When an attacker tries to decrypt the data, the attacker always tries to apply the predefined ASCII table on the Ciphertext, which in a way, can be helpful for the attacker to decrypt the data. After that, a radix 64-bit encryption mechanism is used, with the help of which the number of cipher data is doubled from the original data. When the number of cipher values is double the original data, the attacker tries to decrypt each value. Instead of getting the original data, the attacker gets such data that has no relation to the original data. After that, a Hill Matrix algorithm is created, with the help of which a key is generated that is used in the exact plain text for which it is created, and this Key cannot be used in any other plain text. The boundaries of each Hill text work up to that text. The techniques used in this paper are compared with those used in various papers and discussed that how far the current algorithm is better than all other algorithms. Then, the Kasiski test is used to verify the validity of the proposed algorithm and found that, if the proposed algorithm is used for data encryption, so an attacker cannot break the proposed algorithm security using any technique or algorithm. [ABSTRACT FROM AUTHOR]

Protecting and concealing sensitive data in the modern world is challenging. Due to insufficient protection and privacy, it is feasible for critical information to be fabricated. This led to a significant financial loss for someone. The intended recipient must be trusted with sensitive information and be able to independently authenticate the accuracy of the information by independently checking the specifics. There are several driving the rise in QR codes used for information transmission. Due to their enormous capacity for storing information, QR codes are vital for dissemination. However, most currently deployed QR code solutions employ insecure data formats and never employ encryption. Secure QR Code is data protection and data concealing available technology. The Quick Response (QR) code is widely used and accessible without extensive technical training. Now, the user data stored in a QR code is effectively public knowledge and occasionally even illegally used. To address the abovementioned issues, this study's authors propose a novel QR code encryption system. Using the image's mathematical processing method, we may apply the equivalence class principle to the ordered equations of the two-dimensional code, producing the desired cryptographic result. This method exploits the unique visual properties of the QR code. Only a QR code reader can decode the code's useful information, which is too complex for standard reading methods. It will be utilised to address issues in speedy business client data protection Security, commodity anti-counterfeiting, and bicycle sharing QR codes. [ABSTRACT FROM AUTHOR]

Hyperledger Fabric is a distributed ledger solution platform based on a modular architecture. The cryptographic algorithm is the core of the platform to ensure the security and tamper-resistant of the data on the chain. However, the original Fabric platform lacks the protection of user's keys and cryptographic operations. To this end, this paper proposes a data privacy protection method for Hyperledger Fabric based on Trustzone technology, which places the user's key and the cryptographic operation process of private data in the trusted execution environment for protection. The experimental results based on the existing blockchain network show that the scheme can effectively ensure the security of data encryption process and key static storage, greatly reduce the trusted computing base and the attack surface. The performance loss is within an acceptable range. [ABSTRACT FROM AUTHOR]

Personal health records (PHR) represent health data managed by a specific individual. Traditional solutions rely on centralized architectures to store and distribute PHR, which are more vulnerable to security breaches. To address such problems, distributed network technologies, including blockchain and distributed hash tables (DHT) are used for processing, storing, and sharing health records. Furthermore, fully homomorphic encryption (FHE) is a set of techniques that allows the calculation of encrypted data, which can help to protect personal privacy in data sharing. In this context, we propose an architectural model that applies a DHT technique called the interplanetary protocol file system and blockchain networks to store and distribute data and metadata separately; two new elements, called data steward and shared data vault, are introduced in this regard. These new modules are responsible for segregating responsibilities from health institutions and promoting end-to-end encryption; therefore, a person can manage data encryption and requests for data sharing in addition to restricting access to data for a predefined period. In addition to supporting calculations on encrypted data, our contribution can be summarized as follows: (i) mitigation of risk to personal privacy by reducing the use of unencrypted data, and (ii) improvement of semantic interoperability among health institutions by using distributed networks for standardized PHR. We evaluated performance and storage occupation using a database with 1.3 million COVID-19 registries, which showed that combining FHE with distributed networks could redefine e-health paradigms. [ABSTRACT FROM AUTHOR]

In the first part of the paper is presented the state of the art regarding the Flywheel Energy Storage Systems (FESS) and the inertial energy storage system based on the flywheel principle FESS, with axial magnetic bearing developed at ICPE-CA. The second part of the paper is focused on the applicative extension of the inertial energy storage systems namely inertial device for energy storage and protection of local micro electric grids by the galvanic separation of the supply circuit of this microgrid from the industrial electrical network. The power supply is made for a certain period of time of special consumers aimed at data protection and fast storage in case of failure. The flywheel (FW) is permanently in rotation provided by an electric motor and transmits the movement to an electric generator. Both electric machines are sized to the cumulative power for a group of special consumers, in which the electric motor is powered by a controller from the industrial network, and the electric machine generator feeds the microgrid of special consumers through an electronic block for the conversion and adaptation of electrical parameters. Also, in the paper it is presented the preliminary syzing for the prototype inertial energy storage system which will be developed manufactured and tested. [ABSTRACT FROM AUTHOR]

Traditional centralized cloud storage has difficulties in realizing the secure storage and sharing of speech and other multimedia data, as well as realizing fine-grained access control and privacy protection for speech data. To address this problem, we propose a distributed storage scheme for encryption speech data based on blockchain and inter planetary file system (IPFS). Our scheme is based on the characteristics of blockchain anti-tampering, decentralization and traceability. It is designed to ensure the security and controllability of private sensitive speech data of data users without the use of centralized cloud storage architecture. First, the ciphertext policy hierarchical attribute-based encryption (CP-HABE) scheme is used to encrypt the speech data. The encrypted speech data is then stored in the IPFS to achieve distributed storage. Second, a distributed and trusted access control policy is implemented by deploying an access control protocol Ethereum smart contract related to speech attributes. Finally, the proposed scheme is deployed and tested in the Linux environment, and the smart contract is deployed on the Ethereum test chain. Through experimental comparison with different storage schemes, analysis of the operational properties of our scheme and the evaluation of the quality index of the encryption scheme, the proposed scheme is shown to reliable, secure and scalable. [ABSTRACT FROM AUTHOR]

Security of data is one of the most important aspects of one's digital presence. Many Encryption Algorithms are used in various apps and services to secure data, like AES, DES, Blowfish, RSA, and Triple-DES among others. With the advent of new and sophisticated technologies, these existing data security systems are becoming less efficient in protecting data. Advanced data security protocols used in various applications like WhatsApp and Telegram are becoming inadequate to protect the privacy of an individual. With advancements in Hardware, the time required to break a cryptographic system is becoming even lesser than earlier. Thus, the requirement of a multi-layered encryption protocol that utilizes multiple advanced cryptographic algorithms implemented in a cascading manner is ever more necessary. In this project, data will be encrypted using multiple algorithms like AES, RSA, and Blowfish. The keys that will be used for encryption will also be secured similarly and transmitted only after authentication. Multi-layered encryption protocols are not widely used in current systems. Here will address the problems faced by standalone systems used for data security. [ABSTRACT FROM AUTHOR]

Cryptography is a technique for encoding data by encrypting plaintext into an unreadable (meaningless) form. Cryptographic methods have good and bad performance depending on the type of algorithm we use. Therefore, the purpose of this study is to measure speed by combining the two algorithms used. The Rabbit Stream algorithm is a stream cipher algorithm whose system security depends on the generation of a key bit stream (keystream), which only guarantees 128-bit key security but has the advantage of being fast in the encryption and decryption process, while the Enhanced Dual RSA algorithm is an asymmetric algorithm to increase data protection from the Dual RSA algorithm by utilizing the Pells equation as a substitute for public key exponents. On the other hand, the algorithm in question requires a significant amount of time to encrypt messages with a large capacity when compared to the Rabbit Stream algorithm. Nonetheless, the study's findings suggest that using a hybrid method is comparatively faster for processing substantial amounts of data. [ABSTRACT FROM AUTHOR]

Today, no one can deny the tremendous effects of cloud computing as it provides access to lot of computing resources including infrastructure, hardware, network, server and applications services to its users. These services are controlled by third party known as Cloud Service Providers. Despite the flexibility and scalability of the cloud computing which has given the business a colossal revolution, privacy is still a major issue which cannot be abolished or ignored. With the development of cloud computing, privacy security issues have become increasingly prominent, which is of concern to industry and academia. Our research progress review the privacy, security and data storage issues of cloud computing. Firstly, we discuss some privacy, security and data storage issues; and then advise an inclusive privacy protection framework by implementing numerous data protection technologies. Secondly, we elaborated the research evolution of some technologies, alike data encryption technique, key and token generation policies at authorization layer, acknowledgement of data at privacy layer and access control and generation of transaction codes at verification layer. Thirdly, we proposed a token generation algorithm. Lastly, we discuss the parameters include in the proposed technique, comparison of token generation base on different attributes, features and strengths and concluded with the possible future research directions. Moreover, PHP language is used for API and RDMS (MySQL) is used as database tool for software development and testing process. Android Studio and Ionic framework was used for frontend development. [ABSTRACT FROM AUTHOR]

In order to ensure the protection of important data in the face of natural and man-made disasters in data centers in cloud computing services, sufficient backups of the data are required. This paper briefly introduced the security encryption measures for disaster backup of data under cloud computing. The transmission performance during disaster backup was improved by the intelligent ant colony algorithm. Simulation experiments were performed to compare the encryption performance of two encryption algorithms, the Rivest, Shamir, and Adleman (RSA) algorithm and the Advanced Encryption Standard (AES) algorithm, in disaster backup, and the transmission performance of the intelligent ant colony algorithm and the maximum network flow algorithm. The results showed that the asymmetric encryption algorithm and the RSA algorithm had better encryption performance than the AES algorithm in terms of disaster backup; with the increase of backup data volume, the transmission performance of both route assignment algorithms decreased, but the intelligent ant colony algorithm always outperformed the maximum network flow algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a novel encryption method based on individual block ciphering using Catalan random walks. This paper aims to offer some new possibilities of multimedia data protection to realize the rights of participants in the multimedia distribution chain (image, text, video, sound). Also, the emphasis is on advanced analysis of Catalan numbers and their combinatorial representations in multimedia security. The proposed method consists of five phases: conversion, division, selection, encryption, and generation. We presented the application of our method in ensuring the security of multimedia content. The proposed method was implemented in Java. In the experimental testing, we provide the time and space complexity of Catalan keys generation and Maurer's universal statistical test for the proposed method. Also, we state security analysis using machine learning methods and comparative analysis with existing methods of encrypting data into a blockchain. [ABSTRACT FROM AUTHOR]

This article examines the disconnect between people's social conceptions of privacy and information security in relation to encryption vis-à-vis the legal protections offered by law. It describes the social conceptions and expectations of participants based in New Zealand and contrasts these with the applicable laws and legal protections concerning privacy, information security and encryption. In light of incongruence between the social and the legal, the article recommends law and policy developments to better align and connect people's social conceptions of privacy and information security with the legal protections provided by law. This includes having greater awareness of the relevance of civil and criminal procedure rights to privacy and information security in the context of encryption and providing stronger legal protections to the right against unreasonable search and seizure and the privilege against self-incrimination. [ABSTRACT FROM AUTHOR]

Data encryption technology can protect data from illegal theft. This study analyzed the Rivest, Shamir, and Adleman (RSA) algorithm, the Advanced Encryption Standard (AES) algorithm, and their encryption and decryption processes, compared their merits and demerits, and combined them to from the AES + RSA algorithm to achieve network data protection. It was found from the performance analysis that the AES algorithm only took a short time to encrypt and decrypt, while the RSA algorithm, due to asymmetric encryption, spent a much longer time in decryption than in encryption; the total time consumed by the AES algorithm for encryption and decryption increased hundreds of times, but the operation time of the AES + RSA algorithm was only slightly longer than that of the AES algorithm. Also, from the perspective of security analysis, both AES and RSA algorithms had high confidentiality, which could meet the needs of information security. The results show that the combination of AES and RSA algorithms is effective in information security, which can be further popularized and applied in reality. [ABSTRACT FROM AUTHOR]

In order to solve the network security problem of data encryption technology, this paper proposes a research method of computer network information security maintenance based on data encryption technology. Taking the network reporting system of a mining enterprise as the research object, this paper comprehensively expounds on the design of network reporting system and data encryption in network communication from the aspects of demand investigation, demand analysis, system design, software system development, and so on and implements the development by using BS architecture + independent client. The experimental results show that the AES algorithm can be independently designated as 128 bits, 192 bits, and 256 bits. Conclusion. This scheme can realize the rapid and safe transmission of data information and provide an effective means for the transmission of confidential documents on the network, so it has a good application prospect. [ABSTRACT FROM AUTHOR]

Repeatable dual‐encryption platforms, coupled with a strong protective capacity for stored information, are highly desirable for current data security but still a challenge to be realized. Herein, a new type of thermoset‐based repeatable dual‐encryption platform is designed to fulfill the challenge. Through introducing dynamic boroxine bonds and hydrogen bonds within the thermoset, self‐healing, recyclability, and shape‐memory properties can be achieved. Given the shape memory behavior of this thermoset, encryption data within complex 3D structures can be realized. Thus, shape recovery is inevitable for the decryption, providing strong protection for encrypted data. Furthermore, the encrypted data can be protected by showing misleading information before true information during the decryption process, which is caused by the different analogous "LEGO" assembly sequences of thermosets that induces different hydrophobic association interactions. The decrypted information can be erased by heating, realizing the repeatable encryption/decryption. Additionally, the thermosets can be efficiently recycled. This strategy opens up a smart prospect for high level dual‐encryption platform. [ABSTRACT FROM AUTHOR]

The collection of amounts of useful data from various IoT devices through machine learning (ML) techniques has been extensively applied in lots of areas of the smart city. To improve the efficiency of machine learning, people realize efficient data classification by supporting the ML model, namely, the support vector machine (SVM) model, which is used in the realization of linear classification. However, data security and data protection are not addressed in SVM classifier training from multiple entity-labeled IoT data. In the existing solution, they depend on the implicit hypothesis that learning data can be dependable collected from complex data providers, which is often not the reality. To solve the question between the above problems, in this article, we put forward a secure support vector machine—a secure SECURE SVM training scheme for protecting the privacy on encrypted IoT data based on blockchain. Firstly, a secure and dependable data encryption sharing platform is established among complex data providers by using blockchain technology, which is recorded in a distributed ledger. Secondly, the homomorphic cryptosystem is used to design secure components, and the secure polynomial multiplication is improved to design a secure SVM training algorithm, which only needs two interactions in one iteration and does not need a trusted third party. Finally, the experimental results display that the plan ensures the confidentiality of sensitive data of each data provider and the confidentiality and validity of SVM model parameters of data analysts. [ABSTRACT FROM AUTHOR]

European start-up companies must overcome more 'transfer hurdles' when personal data is transferred from the European Union to the US (United States of America) as part of crowdfunding campaign activities. Transfer of personal data is commonly not associated with (small scale) crowdfunding activities. However, the strict rules of the EU GDPR (European General Data Protection Regulation) on safeguarding personal data apply to all companies when data is transferred from the EU to the US - regardless the size of the business. This article identifies exchange of personal data that takes place between primarily fundraiser and crowdfunding service provider in different steps of fundraising campaigns. The framework for rewardbased crowdfunding for goods production that is provided by the US based Indiegogo platform is used as example and context. The article highlights by way of example the obligations that must be met by European fundraisers as "data controllers" when personal data is transferred to Indiegogo. No easy solutions are provided by either European Union or national data protection authorities on how to establish an adequate level of personal data protection. Paradigms on how to secure transfer of personal data to third countries are available in form of so-called standard contractual clauses, but still conditions for transfer of personal data from Europe to the US are hard to comply with. Apart from entering into an inter partes agreement on use of standard contractual clauses with the crowdfunding platform provider, a European fundraiser must furthermore make a so-called "transfer impact assessment" to ensure that third party access to personal data is avoided. In the case of transfer of personal data from the EU to the US the fundraiser must consider using encryption of data as a "supplementary measure" to block third party access. Encryption of data is however not suitable for exchange of data in a dynamic crowdfunding campaign so other means for protection of data must be found and applied. The reason and explanation for making data transfers from the EU to the US that hard for e.g., fundraisers are thus to be found at interstate level in the relation between the EU and the US. According to EU law, more specifically the GDPR and several of the provision of the Charter of Fundamental Rights of the European Union, US security legislation authorises a disproportionate access for US intelligence services to citizens' personal data. A solution on manageable transfer of personal data from the EU to the US may be found before the end of 2022, since a new TADP (Trans-Atlantic Data Privacy Framework) is currently being negotiated between EU and US at top politician level. However, the implementation of the TADP may take som time since the EU legislative framework needs adjustments to make the new transfer possibilities operational. [ABSTRACT FROM AUTHOR]

The need to a robust and effective methods for secure data transferring makes the more credible. Two disciplines for data encryption presented in this paper: machine learning and deoxyribonucleic acid (DNA) to achieve the above goal and following common goals: prevent unauthorized access and eavesdropper. They used as powerful tool in cryptography. This paper grounded first on a two modified Hebbian neural network (MHNN) as a machine learning tool for message encryption in an unsupervised method. These two modified Hebbian neural nets classified as a: learning neural net (LNN) for generating optimal key ciphering and ciphering neural net CNN) for coding the plaintext using the LNN keys. The second granulation using DNA nucleated to increase data confusion and compression. Exploiting the DNA computing operations to upgrade data transmission security over the open nets. The results approved that the method is effective in protect the transferring data in a secure manner in less time. [ABSTRACT FROM AUTHOR]

One of the challenges in the Internet of Things systems is the security of the critical data, for example, data used for intrusion detection. The paper research construction of an intrusion detection system that ensures the confidentiality of critical data at a given level of intrusion detection accuracy. For this goal, federated learning is used to train an intrusion detection model. Federated learning is a computational model for distributed machine learning that allows different collaborating entities to train one global model without sharing data. This paper considers the case when entities have data that are different in attributes. Authors believe that it is a common situation for the critical systems constructed using Internet of Things (IoT) technology, when industrial objects are monitored by different sets of sensors. To evaluate the applicability of the federated learning for this case, the authors developed an approach and an architecture of the intrusion detection system for vertically partitioned data that consider the principles of federated learning and conducted the series of experiments. To model vertically partitioned data, the authors used the Secure Water Treatment (SWaT) data set that describes the functioning of the water treatment facility. The conducted experiments demonstrate that the accuracy of the intrusion detection model trained using federated learning is compared with the accuracy of the intrusion detection model trained using the centralized machine learning model. However, the computational efficiency of the learning and inference process is currently extremely low. It is explained by the application of homomorphic encryption for input data protection from different data owners or data sources. This defines the necessity to elaborate techniques for generating attributes that could model horizontally partitioned data even for the cases when the collaborating entities share datasets that differ in their attributes. [ABSTRACT FROM AUTHOR]

With technological advancement, cloud computing paradigms are gaining massive popularity in the ever-changing technological advancement. The main objective of the cloud computing system is to provide on-demand storage and computing resources to the users on the pay-per-use policy. It allows small businesses to use top-notch infrastructure at low expense. However, due to the cloud resource sharing property, data privacy and security are significant concerns and barriers for smart systems to constantly transfer generated data to the cloud computing resources, which a third-party provider manages. Many encryption techniques have been proposed to cope with data security issues. In this paper, different existing data protection and encryption techniques based on common parameters have been critically analyzed and their workflows are graphically presented. This survey aims to collect existing data encryption techniques widely presented in the literature for smart system data security offloaded to the cloud computing systems under a single umbrella. [ABSTRACT FROM AUTHOR]

The tremendous development of cloud computing with related technologies is an unexpected one. However, centralized cloud storage faces few challenges such as latency, storage, and packet drop in the network. Cloud storage gets more attention due to its huge data storage and ensures the security of secret information. Most of the developments in cloud storage have been positive except better cost model and effectiveness, but still data leakage in security are billiondollar questions to consumers. Traditional data security techniques are usually based on cryptographic methods, but these approaches may not be able to withstand an attack from the cloud server's interior. So, we suggest a model called multi-layer storage (MLS) based on security using elliptical curve cryptography (ECC). The suggested model focuses on the significance of cloud storage along with data protection and removing duplicates at the initial level. Based on divide and combine methodologies, the data are divided into three parts. Here, the first two portions of data are stored in the local system and fog nodes to secure the data using the encoding and decoding technique. The other part of the encrypted data is saved in the cloud. The viability of our model has been tested by research in terms of safety measures and test evaluation, and it is truly a powerful complement to existing methods in cloud storage. [ABSTRACT FROM AUTHOR]

Pervasive sensing with Body Sensor Networks (BSNs) is a promising technology for continuous health monitoring. Since the sensor nodes are resource-limited, on-node processing and advertisement of digested information via BLE beacon is a promising technique that can enable a node gateway to communicate with more sensor nodes and extend the sensor node's lifetime before requiring recharging. This study proposes a Dynamic Light-weight Symmetric (DLS) encryption algorithm designed and developed to address the challenges in data protection and real-time secure data transmission via message advertisement. The algorithm uses a unique temporal encryption key to encrypt each transmitting packet with a simple function such as XOR. With small additional overhead on computational resources, DLS can significantly enhance security over existing baseline encryption algorithms. To evaluate its performance, the algorithm was utilized on beacon data encryption over advertising channels. The experiments demonstrated the use of the DLS encryption algorithm on top of various light-weight symmetric encryption algorithms (i.e., TEA, XTEA, PRESENT) and a MD5 hash function. The experimental results show that DLS can achieve acceptable results for avalanche effect, key sensitivity, and randomness in ciphertexts with a marginal increase in the resource usage. The proposed DLS encryption algorithm is suitable for implementation at the application layer, is light and energy efficient, reduces/removes the need for secret key exchange between sensor nodes and the server, is applicable to dynamic message size, and also protects against attacks such as known plaintext attack, brute-force attack, replaying attack, and differential attack. [ABSTRACT FROM AUTHOR]

To strengthen the security of edge network data and reduce network latency, in this paper, we combine an advanced reduced instruction set computing machine (ARM) and a field programmable gate array (FPGA) to propose a lightweight ARM-FPGA computing architecture for edge network data security protection and acceleration. Firstly, the access control lists are set through FPGA to authorize and filter illegal data, thereby reducing the transmission and processing of invalid data on the network. Secondly, based on the principles of dynamization, diversification, and randomization, the initial random key is generated using a pseudo-random number generator and a scrambling factor, and the hash of the data packet value updates the key to ensure "one frame, one key." Then, an ARM microprocessor is used to monitor the working status of the system in real-time. If an abnormality is found, different disturbance factors are activated using key management to change the system running status and restore the stability of the system. Finally, pipeline technology and critical path optimization on FPGA are used to parallelize the underlying encryption algorithm and data compression algorithm to achieve high-speed memory communication and meet the performance requirements of different networks. The experimental and analysis results show that the computing architecture designed in this paper has high network encryption performance and can effectively prevent data leakage. In addition, the effectiveness of the architecture in terms of network delay and network load is verified. [ABSTRACT FROM AUTHOR]

The purposes are to develop the patent data profoundly, control the data access process effectively, and protect the patent information and content. The traditional patent review systems are analyzed. For the present patent data security and privacy protection technologies and algorithms, the patent information data are stored on different block nodes after data fragmentation using blockchain technology. Then the data are shared using the data encryption algorism. In this way, data access control can be restricted to particular users. Finally, a patent data protection scheme based on privacy protection is proposed. The security of the scheme and the model performance are verified through simulation experiments. The time required to encrypt 10 MB files with 64-bit and 128-bit data is 35 ms and 105 ms, respectively. The proposed re-encryption algorithm only needs 1 s to decrypt 64 KB data, and only 1% of the data needs asymmetric encryption. This greatly reduces the computational overhead of encryption. Results demonstrate that the system can effectively control the access methods of users, efficiently protect the personal privacy and patent content of patent applicants, and reduce the patent office cloud computing overhead using the local resources of branches. The distributed storage methods can reduce the cloud system interaction of the patent office, thereby greatly improving the speed of encryption and ensuring data security. Compared with the state of the art methods, the proposed patent data access and protection system based on blockchain technology have greater advantages in data security and model performance. The research results can provide a research foundation and practical value for the protection and review systems of patent data. [ABSTRACT FROM AUTHOR]

Unlike public chains, the Alliance Blockchain Hyperledger Fabric has a member management service mechanism that may provide data isolation security at the channel level. However, because this data isolation security technique synchronizes plaintext data inside the channel, data leakage is still a possibility. Furthermore, in some fine-grained privacy protection circumstances, channel-based data access restriction is ineffective. In order to solve the data privacy security problems in the above-mentioned consortium chain superledger, a blockchain data attribute encryption scheme based on ciphertext policy is proposed. Combining the original Fabric Certificate Authority module in the Hyperledger, the proposed scheme can realize the user-level fine-grained security access to control blockchain data while also realizing the secure distribution of user attribute keys in the blockchain data attribute encryption scheme based on the ciphertext policy scheme. The security analysis of the scheme shows that the scheme achieves the security goals of attribute-based encryption user attribute private key secure distribution and data privacy protection. The scope of this research is that this study confirms that the solution's architecture achieves fine-grained access control of private data on the Hyperledger Blockchain network and also the security objectives of secure transmission of user characteristic secret keys and data privacy protection. The performance analysis part also shows that the proposed scheme has good usability. [ABSTRACT FROM AUTHOR]

The paper presents analysis of the possibility of using selected hash functions submitted for the SHA-3 competition in the SDEx encryption method. The group of these functions will include the finalists of the SHA-3 competition, i.e. BLAKE, Grøstl, JH, Keccak, Skein. The aim of the analysis is to develop more secure and faster cryptographic algorithm compared to the current version of the SDEx method with SHA- 512 and the AES algorithm. When considering the speed of algorithms, mainly the software implementation will be taken into account, as it is the most commonly used. [ABSTRACT FROM AUTHOR]

The intention of this position paper is to comment on the joint European Data Protection Supervisor (EDPS)‐Agencia Española de Protección de Datos (aepd) publication '14 Misunderstandings with regard to Biometric Identification and Authentication' that was published in June 2020 and to provide additional input to help with the better understanding of the issues raised in that publication. In particular, it aims to highlight some important missing information in the aforementioned publication. It is hoped that this paper will help with any future revision of the EDPS‐aepd publication, such that it includes a full picture of the current state of the art in biometrics and the availability of standards and privacy enhancing techniques. [ABSTRACT FROM AUTHOR]

An editorial is presented on underlining violations of data protection requirements by an EU agency. Topics include admonishment of Europol for the continued storage of large amounts of personal data without data subject categorization; explaining the importance of the requirement for categorizing personal data into different types of data subjects; and information hacking from encrypted phone services or extracted from asylum seekers.

In cryptography, data encryption turns ordinary information into an obfuscated code, and the information cannot be viewed without being decrypted. Thus, cryptography remains the main element of data protection. There are two kinds of cryptography, such as symmetric and asymmetric. There are many existing symmetric algorithms that are used to encrypt data, such as the Data Encryption Standard (DES), Triple Data Encryption Algorithm (TDEA), Enigmatic Diagonal Encryption Standard (EDES), Advanced Encryption Standard (AES), BLOWFISH, TWOFISH, Rivest Cipher 4 (RC4), Rivest Cipher 6 (RC6), which have been reviewed in this paper. It compares and tracks a summary of productive encryption calculations. The performance is compared with key size, space, time, security, and features of encryption methods. [ABSTRACT FROM AUTHOR]

E-documents are carriers of sensitive data, and their security in the open network environment has always been a common problem with the field of data security. Based on the use of encryption schemes to construct secure access control, this paper proposes a fusion data security protection scheme. This scheme realizes the safe storage of data and keys by designing a hybrid symmetric encryption algorithm, a data security deletion algorithm, and a key separation storage method. The scheme also uses file filter driver technology to design a user operation state monitoring method to realize real-time monitoring of user access behavior. In addition, this paper designs and implements a prototype system. Through the verification and analysis of its usability and security, it is proved that the solution can meet the data security protection requirements of sensitive E-documents in the open network environment. [ABSTRACT FROM AUTHOR]

Attribute based encryption is suitable for data protection in data outsourcing systems such as cloud computing. However, the leveraging of encryption technique may retrain some routine operations over the encrypted data, particularly in the field of data retrieval. This paper presents an attribute based date retrieval with proxy re-encryption (ABDR-PRE) to provide both fine-grained access control and retrieval over the ciphertexts. The proposed scheme achieves fine-grained data access management by adopting KP-ABE mechanism, a delegator can generate the re-encryption key and search indexes for the ciphertexts to be shared over the target delegatee's attributes. Throughout the process of data sharing, the data are transferred as ciphers thus the server and unauthorized users cannot acquire the sensitive information of the encrypted data so the privacy and confidentiality can be protected. By security analysis, the proposed scheme meets the security requirements confidentiality, keyword semantic security as well as collusion attack resistance. [ABSTRACT FROM AUTHOR]

Mechanochromic fluorophores and elastomers gain great potential in dynamic data encryption and anti-counterfeiting due to their instant responses, excellent handleability, high-throughput data-verification, and multi-dimensional security features. However, the reported mechanochromic fluorophores generally require solvent fuming or thermal annealing to revert their responses, sacrificing the handleability and lengthening the authentication time. For the mechanochromic elastomers, the data input requires precisely control the dose of the crosslinkers or phase tuning agents, making the high-throughput data-processing rather challenging. Here we developed a mechanically gated data display by synergizing the mechanochromism of chiral photonic elastomers and optically responsive molecules. Specifically, the reflectance or emission of the dyes/fluorophores could be selectively reflected or transmitted by the elastomers with desired photonic bandgaps, leading to data displays of given color/fluorescence. Mechanically stretching the elastomers can readily tuning their photonic bandgaps over a wide range, thereby notably alternating the corresponding reflection and emission wavelength, and the outcome of displayed data. Relaxing the elastomers rapidly restores the initial data. Moreover, the displayed data varies notably under L- and R-circular polarizer filter, respectively, offering good programmability and multi-dimensional security features. This work represents a unique data protection approach and enables properties unattainable by conventional mechanochromic fluorophores and elastomers. • The displayed data changes dynamically when stretching or relaxing the CLC elastomer. • The fast mechanical responses of the CLC films accelerates the authentication process. • The synergy of CLC film and fluorophores enables multi-dimensional data protection. • The output emission wavelength could be tuned by the strain of CLC films. • Combinational encryption with three inputs is achieved. [ABSTRACT FROM AUTHOR]

Biometrics has proved to be an efficient solution to several of the security problems that are prominent in the modern age in most technological fields. It is the estimation of physical or behavioral features of humans utilized for distinctive recognition. Biometricsuses Digital Image Processing's pattern identification technology for recognizing the unique characteristics of humans. Fingerprint impression, facial landmarks, iris morphology, voice recognition, handwriting detection, hand geometry recognition, finger vein identification and signature recognition are the most widely applied or called biometric modalities. Biometrics is used in different areas, one of which is protection systems. We propose an intelligent biometric authentication system for data management in the cloud. A general issue is keeping biometric data safe in health facilities for patient authentication. Many experiments have shown different means of keeping biometric information, particularly biometric data from finger veins. Therefore, by implementing the above three principles of information protection and developing a robust authentication framework with high standards of reliability, privacy and security, better ways of protecting this data need to be found. Besides, biometric data is quite tough to replicate and any loss of biometric information contributes to high risks. This study uses fingerprint scanner systems to be using changed minutae algorithm to create an effective biometric identification system. Only the enclosed triangles around each minute were contrasted between the input and the stored prototype in the updated method. The suggested method gave a high degree of accuracy with an error rate equal to 0.5%. [ABSTRACT FROM AUTHOR]

This article introduces the new method of sensor data privacy protection method for IoT. Asymmetric encryption is used to verify the identity of the gateway by the sensor. The IoT gateway node verifies the integrity and source of the data, then creates a block, and submits the block chain transaction. In order to avoid tracking the source of the data, a ring signature is used to anonymize the gateway transaction. The proxy re-encryption method realizes the sharing of encrypted data. On the basis of smart contracts, attribute-based data access control allows decentralized applications to finely control data access. Through experiments, the effects of sensor/gateway verification, transaction signatures, and sensor data encryption on performance are discussed. The results show that transaction delays are all controlled within a reasonable range. The system performance achieved by this method is also relatively stable. [ABSTRACT FROM AUTHOR]