Encryption Mode Research Articles

Design of specific mobile health-care communication encryption system based on natural language processing

Aiming at the problem of poor real-time and security caused by symmetric encryption in common communication encryption systems, a specific mobile communication encryption system based on natural language processing is designed. In the hardware part of the system, the hardware encryption module of communication terminal is designed. In the software part of the system, after the communication content is processed by natural language processing, the elliptic curve encryption algorithm is used to encrypt the specific communication content. Through comparative experiments, it is proved that the success rate of key agreement in encryption system processed by natural language is more than 93%, which has better security.

Blockchain-Enabled decentralized Attribute-Based access control with policy hiding for smart healthcare

With the rapid development of edge computing technologies, smart healthcare significantly improves people’s lives by collecting and analyzing health data in real time. However, security and privacy issues impede the wide deployment of smart healthcare systems (SHS). Most of existing solutions still have drawbacks with respect to computation efficiency and users’ privacy. In this paper, a blockchain-enabled attribute-based access control scheme with hidden policies is proposed for SHS. The scheme introduces multiple authorities to avoid single point failure. Especially, the mode of online-offline encryption relieves users’ online computation burden by transferring computation tasks to the idle time of users, and policy hiding protects users’ sensitive information. Furthermore, fair payments are realized based on blockchain and smart contracts to support the outsourcing of decryption between users and mobile edge computing servers. Finally, the proposed scheme is proven secure in the random oracle model, and experimental results show that it is computationally efficient and hence can be used in the edge computing environment.

Research on Real-Time Information Storage and Remote Piano Teaching Based on Bayesian Algorithm

In recent years, big data has developed rapidly, but there are still some problems. In order to solve these problems, this article has carried out research on big data and integrated it into industrial equipment inspection, and designed a function for data processing. This function is based on the XML system and studies the relationship between the XML system and the database in order to switch between different types of data. At the same time, because of the error of the data processed by the sensor, we decided to improve the Bayesian prediction calculation method in order to improve the accuracy of the data and reduce the error of the data. In the process of extracting key data, the key data collected by the sensor will be transmitted to the cloud platform. This is to realize the free transmission of data on different devices without other forms of interference and hindrance. The processed data will be stored in the monitor or computer for further processing. In order to ensure that the data will not be disturbed or destroyed during the process of saving data, we have designed a data security system, which consists of encryption modules and key cracking modules, and has tested the performance of these modules through a large number of experiments. In order to improve the operating efficiency of the system and to extend the service life, online piano teaching is a part of online education. This article uses music education apps and piano online education to study new ways of piano education in the information age and expounds the combination of intelligent systems and piano education. This has a major impact on future education.

AN INNOVATIVE IMPLEMENTATION OF ENCRYPTION ALGORITHM ON FPGA IN MANY CORE ARCHITECTURES.

In this paper, we grant the remodeling with the aid of “categorizes” of amenities—a category being explained as a group of amenities that share innovative operations and are mapped to the same key value based on Encryption schemes of sub-bytes transformation method. The sub-bytes transformation method is the high-speed standard Encryption module. AES Algorithm is synthesized by utilizing Verilog code and encountered into FPGA. We implement a new design of AES Algorithm in FPGA in many core Architectures which is an in-built one.

RASCv2: Enabling Remote Access to Side-Channels for Mission Critical and IoT Systems

The Internet of Things (IoT) and smart devices are currently being deployed in systems such as autonomous vehicles and medical monitoring devices. The introduction of IoT devices into these systems enables network connectivity for data transfer, cloud support, and more, but can also lead to malware injection. Since many IoT devices operate in remote environments, it is also difficult to protect them from physical tampering. Conventional protection approaches rely on software. However, these can be circumvented by the moving target nature of malware or through hardware attacks. Alternatively, insertion of the internal monitoring circuits into IoT chips requires a design trade-off, balancing the requirements of the monitoring circuit and the main circuit. A very promising approach to detecting anomalous behavior in the IoT and other embedded systems is side-channel analysis. To date, however, this can be performed only before deployment due to the cost and size of side-channel setups (e.g., and oscilloscopes, probes) or by internal performance counters. Here, we introduce an external monitoring printed circuit board (PCB) named RASC to provide r emote a ccess to s ide- c hannels. RASC reduces the complete side-channel analysis system into two small PCBs (2 \( \times \) 2 cm), providing the ability to monitor power and electromagnetic (EM) traces of the target device. Additionally, RASC can transmit data and/or alerts of anomalous activities detected to a remote host through Bluetooth. To demonstrate RASCs capabilities, we extract keys from encryption modules such as AES implemented on Arduino and FPGA boards. To illustrate RASC’s defensive capabilities, we also use it to perform malware detection. RASC’s success in power analysis is comparable to an oscilloscope/probe setup but is lightweight and two orders of magnitude cheaper.

5G-BSS: 5G-Based Universal Blockchain Smart Sensors.

A smart sensor is a sensor with information processing functions. It is the product of the combination of sensor integration and a microprocessor. It has the characteristics of intelligence, networking and high precision. It has been widely used in aerospace, aviation, intelligent transportation, industrial control and medical and health care. However, in some specific application scenarios with high data security requirements and low transmission delay, such as environmental detection, transportation, etc., smart sensors have three obvious shortcomings. First, the data transmission delay is high. Second, the confidentiality and integrity of the data transmission process cannot be effectively guaranteed. Third, centralized data storage is easily leaked and tampered with by malicious users and semi-trusted administrators. Therefore, a 5G-based blockchain smart sensor 5G-BSS was designed. 5G-BSS has three innovation points. First, the 5G communication module enables the smart sensor 5G-BSS. The 5G communication module is integrated into the smart sensor 5G-BSS to reduce the delay of data transmission and improve the speed and reliability of data transmission. Second, cryptographic algorithms enable the smart sensor 5G-BSS. The data encryption module of the smart sensor 5G-BSS improves the confidentiality and integrity of the data transmission process. Third, blockchain empowers the smart sensor 5G-BSS. The blockchain client is integrated into the smart sensor 5G-BSS to ensure the centralized storage of data and prevent data leakage and tampering by semi-trusted administrators. The operation process of the hardware and software architecture is described in detail and tested on the Fisco-Bcos. The experimental results show that 5G-BSS not only has fast data transmission speed but also can effectively guarantee the integrity, confidentiality and availability of data. 5G-BSS is suitable for application scenarios with high requirements for data security and data transmission, such as environmental monitoring, intelligent transportation, autonomous driving, etc.

A novel pipelining encryption hardware system with high throughput and high integration for 5G

This paper presents a ZUC-256 stream cipher algorithm hardware system in order to prevent the advanced security threats for 5G wireless network. The main innovation of the hardware system is that a six-stage pipeline scheme comprised of initialization and work stage is employed to enhance the solving speed of the critical logical paths. Moreover, the pipeline scheme adopts a novel optimized hardware structure to fast complete the Mod(2³¹−1) calculation. The function of the hardware system has been validated experimentally in detail. The hardware system shows great superiorities. Compared with the same type system in recent literatures, the logic delay reduces by 47% with an additional hardware resources of only 4 multiplexers, the throughput rate reaches 5.26 Gbps and yields at least 45% better performance, the throughput rate per unit area increases 14.8%. The hardware system provides a faster and safer encryption module for the 5G wireless network.

Privacy-preserving statistical analysis over multi-dimensional aggregated data in edge computing-based smart grid systems

Smart grid systems enable bidirectional data communication between users and a smart grid control center (CC), by utilizing various communication infrastructures and embedded devices. To extract valuable information from users’ power consumption data efficiently, multi-dimensional data of users are required to be analyzed deeply. To protect users’ privacy, power consumption data are usually encrypted before transmission, which simultaneously makes it difficult to conduct statistical analysis. In this paper, we propose a scheme which enables privacy-preserving statistical analysis over multi-dimensional aggregated data (SA-MAD) in smart grid systems equipped with edge computing. We modify Boneh–Goh–Nissim (BGN) public key cryptosystem to a dual-message encryption mode, combining with two special superincreasing sequences to deal with multi-dimensional encrypted data aggregation. Besides, we design an identity-based aggregate signature to ensure encrypted data integrity in smart grid systems, and employ shamir secret sharing technique to support transmission fault-tolerance mechanism from smart meters to corresponding edge servers. SA-MAD enables CC to flexibly conduct privacy-preserving statistical analysis (e.g., sum, average, and variance) over aggregated data, and it could be easily extended to support covariance and linear regression computation. The performance evaluation demonstrates the feasibility of SA-MAD in edge computing-based smart grid systems.

A High-Throughput Hardware Implementation of NAT Traversal For IPSEC VPN

In this paper, we present a high-throughput FPGA implementation of IPSec core. The core supports both NAT and non-NAT mode and can be used in high speed security gateway devices. Although IPSec ESP is very computing intensive for its cryptography process, our implementation shows that it can achieve high throughput and low lantency. The system is realized on the Zynq XC7Z045 from Xilinx and was verified and tested in practice. Results show that the design can gives a peak throughput of 5.721 Gbps for the IPSec ESP tunnel mode in NAT mode and 7.753 Gbps in non-NAT mode using one single AES encrypt core. We also compare the performance of the core when running in other mode of encryption.

Hybridized Model for Data Security Based on Security Hash Analysis (SHA 512) and Salting Techniques

High-profile security breaches and attacks on many organization’s database have been on the increase and the consequences of this, are the adverse effect on the organizations in terms of financial loss and reputation. Many of the security breaches has been ascribed to the vulnerability of the organization’s networks, security policy and operations. Additionally, the emerging technology solutions like Internet-ofThings (IoT), Artificial Intelligence, and Cloud Computing, has extremely exposed many of the organizations to different forms of cyber-threats and attacks. Researchers and system designers have made attempts to proffer solution to some of these challenges. However, the efficacy of the techniques remains a great concern due to insufficient control mechanisms. For instance, many of the techniques are majorly based on a single mode encryption techniques which are not too robust to withstand the threats and attacks on organization’s database. To proffer solution to these challenges, the current research designed and integrated a hybridized data security model based on Secured Hash Analysis (SHA 512) and Salting Techniques to enhance the adeptness of the existing techniques. The Hash Analysis algorithm was used to map the data considered to a bit string of a fixed length and salt was added to the password strings essentially to hide its real hash value. The idea of adding salt to the end of the password is basically to complicate the password cracking process. The hybridized model was implemented in Windows environment using python 3.7 IDE platform and tested on a dedicated Local Area Network (LAN) that was exposed to threats from both internal and external sources. The results from the test show that the model performed well in terms of efficiency and robustness to attacks. The performance of the new model recorded a high level of improvement over the existing techniques with a recital of 97.6%.

Construction and Analysis of Models of Increasing Reliability for Modular Encryption Algorithm

This paper describes the development of a model of symmetric block encryption algorithm using nonpositional polynomial notation systems. Computer model this algorithm was created and its properties were investigated. In order to increase the cryptostrength of the algorithm simple substitution and gamming cipher modes were used, methods of the application of these modes are shown. As a continuation of this work, a computer model for managing keys in the encryption algorithm is being developed

Data Legal Supervision of Online Car-Hailing Platform Based on Big Data Technology and Edge Computing

There is a lack of fairness in market competition and disorder of order as a result of the lack of supervision. OCH (online car-hailing) driver accidents are also reported frequently, causing a slew of social and traffic safety issues. In this paper, we reconstruct the logical path of OCH platform data legal supervision in China’s big data era. We propose a big data encryption algorithm based on data redundancy technology that combines the characteristics of the ECC (Elliptic Curve Cryptography) and AES (Advanced Encryption Standard) block cipher modes in terms of computing speed, parallelism, and security. The system can process large amounts of network data and detect distributed denial of service (DDOS) attacks in real time. The observed feature change trend charts before and after the attacks show significant differences, demonstrating that the proposed features can better distinguish normal traffic from abnormal traffic.

Wide-Range Time-Dependent Color-Tunable Light-Response Afterglow Materials via Absorption Compensation for Advanced Information Encryption.

Stimuli-responsive luminescent materials with time-dependent color are highly desirable in optical information encryption. In this study, multiple time-dependent color processes are achieved by light-responsive afterglow materials through the strategy of absorption compensation. Based on the single-emission band of light-responsive afterglow materials, the color of samples could show a time-dependent change from colored to colorless over several seconds. The strategy possesses high flexibility such that the stimulus light and emission color of light-responsive afterglow materials can be adjusted conveniently to adapt to various scenes. It is also beneficial to expand the capacity and complexity of information encryption. A three-color, time-resolved anticounterfeiting, and data encryption mode is demonstrated. This facile absorption compensation method based on light-response afterglow materials may promote the development of advanced dynamic information encryption.

A design of high-Speed SMS4 cipher circuit

SMS4 cipher algorithm is a commercial cipher independently developed by china. This paper proposes a circuit design of high-speed SMS4 cipher algorithm, which adopts two-dimensional expansion and key path optimization technology. The round key generation module runs synchronously with the encryption module, and the running round is constant, which can effectively resist the side channel attack. Using Xilinx artix-7 for synthesis, the results show that the design function is correct, and achieves the balance of computing speed and resource occupation.

VLSI Design of Advanced-Features AES Cryptoprocessor in the Framework of the European Processor Initiative

This article presents a cryptographic hardware (HW) accelerator supporting multiple advanced encryption standard (AES)-based block cipher modes, including the more advanced cipher-based MAC (CMAC), counter with CBC-MAC (CCM), Galois counter mode (GCM), and XOR-encrypt-XOR-based tweaked-codebook mode with ciphertext stealing (XTS) modes. The proposed design implements advanced and innovative features in HW, such as AES key secure management, on-chip clock randomization, and access privilege mechanisms. The system has been tested in a RISC-V-based system-on-chip (SoC), specifically designed for this purpose, on an Ultrascale + Xilinx FPGA, analyzing resource and power consumption, together with system performances. The cryptoprocessor has been then synthesized on a 7-nm CMOS standard-cells technology; performances, complexity, and power consumption information are analyzed and compared with the state of the art. The proposed cryptoprocessor is ready to be embedded within the innovative European Processor Initiative (EPI) chip.

Bioinspired Perovskite Nanocrystals-Integrated Photonic Crystal Microsphere Arrays for Information Security.

Information security occupies an important position in the era of big data. Attempts to improve the security performance tend to impart them with more additional encryption strategies. Herein, inspired by the wettability feature of Stenocara beetle elytra and signal model of traffic light, a novel array of perovskite nanocrystals (PNs)‐integrated PhC microsphere for information security is presented. The photoluminescent PNs are encapsulated in angle‐independent PhC microspheres to impart them with binary optical signals as coding information. Through the multimask superposition approach, PNs‐integrated PhC microspheres with different codes are placed into fluorosilane‐treated PDMS substrate to form different arrays. These arrays could converge moisture on PhC microspheres in wet environment, which avoids the ions loss of the PNs and effectively prevented mutual contamination. In addition, the fluorescence of the PNs inside PhC microspheres could reversibly quench or recover in response to the environmental moisture. Based on these features, it is demonstrated that the PNs‐integrated PhC microsphere arrays could realize various information encryption modes, which indicate their excellent values in information security fields.

Detecting Encryption Vulnerabilities with Lossless Compression

Ciphertext entropy is a key property for detecting the use of insecure encryption modes such as Electronic Code Book (ECB) and for testing symmetric=key cryptographic algorithms. This paper discusses the use of lossless compression utilities as a proxy measurement for entropy and its use in detecting a limited set of encryption vulnerabilities. We also note the use of off-theshelf algorithms yields a teaching tool for Information Technology and Cybersecurity students. Finally, small and consistent differences between encryption modes provide the potential to identify the encryption algorithm from compression factors.

A Secure Encrypted Classified Electronic Healthcare Data for Public Cloud Environment

The major operation of the blood bank supply chain is to estimate the demand, perform inventory management and distribute adequate blood for the needs. The proliferation of big data in the blood bank supply chain and data management needs an intelligent, automated system to classify the essential data so that the requests can be handled easily with less human intervention. Big data in the blood bank domain refers to the collection, organization, and analysis of large volumes of data to obtain useful information. For this purpose, in this research work we have employed machine learning techniques to find a better classification model for blood bank data. At the same time, it is vital to manage data storage requirements. The Cloud offers wide benefits for data storage and the simple, efficient technology is adapted in various domains. However, the data to be stored in the cloud should be secured in order to avoid data breaches. For this, a data encryption module has been incorporated into this research work. The combined model provides secure encrypted classified data to be stored in the cloud, which reduces human intervention and analysis time. Machine learning models such as Support Vector Machine (SVM), Multinomial Naive Bayes (MNB), Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), K-Nearest Neighbor (KNN) are used for classification. For data security, the Advanced Encryption Standard with Galois/Counter Mode (AES–GCM) encryption model is employed, which provides maximum security with minimum encryption time. Experimental results demonstrate the performance of machine learning and encryption techniques by processing blood bank data.

Designing a New XTS-AES Parallel Optimization Implementation Technique for Fast File Encryption

XTS-AES is a disk encryption mode of operation that uses the block cipher AES. Several studies have been conducted to improve the encryption speed using XTS-AES according to the increasing disk size. Among them, there are researches on parallel encryption of XTS-AES using GPU. Although these studies focus on parallel encryption of AES, optimization for the entire XTS mode has not been performed. The reason is that the <inline-formula> <tex-math notation="LaTeX">$\alpha ^{j}$ </tex-math></inline-formula> computation process included in XTS mode is not suitable for parallel operation. Therefore, in this paper, we proposed several techniques for high-speed encryption in GPU by modifying XTS-AES into a form that is advantageous for parallel operation. The core idea is to pre-calculate the <inline-formula> <tex-math notation="LaTeX">$\alpha ^{j}$ </tex-math></inline-formula> calculation on the CPU into a form that is easy to operate on the GPU. To achieve this goal, we analyzed the <inline-formula> <tex-math notation="LaTeX">$\alpha ^{j}$ </tex-math></inline-formula> calculation process and present the parts that can be optimized. First, we presented a method that can replace multiple operations with a single table reference through the analyzed <inline-formula> <tex-math notation="LaTeX">$\alpha ^{j}$ </tex-math></inline-formula> computation progress. Thereafter, we proposed a method that can be calculated by partially skipping the entire <inline-formula> <tex-math notation="LaTeX">$\alpha ^{j}$ </tex-math></inline-formula> computation process that must be sequentially calculated through the table reference technique. For the proposed optimization implementation, we presented various results for evaluating the optimal implementation. In addition, we compared the performance of XTS-AES OpenSSL implementation on CPU and our proposed optimization implementation on GPU.

HARDWARE FOR ELECTRONIC DOCUMENT MANAGEMENT FOR GRAIN HARVESTING AND IT LEGAL REGULATION

The features of the legal regulation of electronic document management in field work on grain harvesting are considered. Possible risks in this type of work are presented, a mechanism for minimizing them using RFID technology is proposed. The assessment of the possibility of using electronic document management systems within the framework of grain traceability legislation is given. (Research purpose) The research purpose is studying the legislative framework for the use of electronic documents in the transmission of harvesting information from the field, as well as to find the optimal technical solution for the safe transmission of such data. (Materials and methods) Described the algorithm of interaction of participants in the process. The format and structure of various types of data, including the time and coordinates of the operation, for the exchange of messages between nodes were justified. We analyzed the existing cryptographic algorithms that can be applied to solve the tasks in the limited capabilities of the hardware and software complex. (Results and discussion) We formulated the requirements for the hardware of the electronic signature carrier and for the encryption module. The current requirements for the ciphers used were given. The main criteria of the system were determined: asymmetric encryption based on the logarithm of elliptic curves with a key size of 256 bits, hardware for cryptographic protection of information with a memory capacity of at least 1 kilobyte, its execution in the form factor of a card with an RFID interface. We have proposed hardware complexes for cryptographic protection of information that meet the specified requirements and are currently available on the Russian market. (Conclusions) They have shown that the implementation of the developed system will not only speed up the document flow during field work, but also prevent illegal actions and will become the basis for electronic document management, including primary documents.