Encryption Technology Research Articles

An Exploratory Study on the Application of Blockchain Technology to the Chinese Ship Auction Market

The Chinese ship trading market has undergone remarkable development, transitioning into a global exemplar of ship transactions. Nevertheless, this market continues to confront a series of challenges, encompassing low transaction rates, delayed transaction values, and market instability. Blockchain, with its secure, transparent, and tamper-resistant technological features, presents a potential solution for the ship trading market. Through its decentralized architecture, blockchain technology can reduce platform operational costs, enhancing market competitiveness. Concurrently, the utilization of asymmetric encryption technology can enhance the security of platform data, effectively addressing privacy concerns. Furthermore, through a sharing mechanism, blockchain can aid in establishing a unified credit evaluation system, thereby increasing market trust to address the absence of a credit evaluation system. Moreover, blockchain technology can be employed to construct a risk identification mechanism, fortifying the platform's regulatory model to address regulatory deficiencies.

A Survey on Graphical Password Strategy Authentication

In an ever-evolving digital realm, ensuring the security and reliability of software applications has become increasingly crucial. The continuous advancement of technology also brings about more complex cyber threats, emphasizing the urgent need to identify and address vulnerabilities. In response to this growing imperative, we introduce "Graphical Password Authenticator: A Novel Approach to Secure User Authentication." The Graphical Password Authenticator reimagines the conventional user authentication process by utilizing graphical elements and innovative techniques. It provides a secure and user-friendly alternative to traditional text-based passwords, offering enhanced protection against unauthorized access. By incorporating graphical images, patterns, or other visual cues, users can create unique and memorable authentication credentials that are difficult for malicious actors to compromise. This approach offers a more intuitive and engaging way for users to access their accounts while significantly reducing the risk of password-related security breaches. The Graphical Password Authenticator system ensures robust security through a combination of graphical recognition and encryption technologies. It is designed to be resistant to common attack methods such as brute force and keyloggers, providing a higher level of protection for user accounts and sensitive information. This novel approach to user authentication fosters a secure and user-centric environment, making it a promising solution for the ever-evolving digital landscape. The Graphical Password Authenticator is a groundbreaking step at the intersection of user authentication and innovation. By redefining the way users prove their identity through memorable graphical elements, this approach empowers users with a more secure and intuitive means of accessing their digital resources. This paradigm shift in authentication methods showcases the potential of technology to enhance user security and create a safer digital future, ultimately bridging the gap between user convenience and robust cybersecurity. Keywords: Graphical Password Authenticator, User Authentication, Cybersecurity, Digital Security, Encryption Technologies, User-Centric Approach, Brute Force Resistance, Keyloggers Protection.

A Research on Graphical Password Strategy Authentication

In an ever-evolving digital realm, ensuring the security and reliability of software applications has become increasingly crucial. The continuous advancement of technology also brings about more complex cyber threats, emphasizing the urgent need to identify and address vulnerabilities. In response to this growing imperative, we introduce "Graphical Password Authenticator: A Novel Approach to Secure User Authentication." The Graphical Password Authenticator reimagines the conventional user authentication process by utilizing graphical elements and innovative techniques. It provides a secure and user-friendly alternative to traditional text-based passwords, offering enhanced protection against unauthorized access. By incorporating graphical images, patterns, or other visual cues, users can create unique and memorable authentication credentials that are difficult for malicious actors to compromise. This approach offers a more intuitive and engaging way for users to access their accounts while significantly reducing the risk of password-related security breaches. The Graphical Password Authenticator system ensures robust security through a combination of graphical recognition and encryption technologies. It is designed to be resistant to common attack methods such as brute force and keyloggers, providing a higher level of protection for user accounts and sensitive information. This novel approach to user authentication fosters a secure and user-centric environment, making it a promising solution for the ever-evolving digital landscape. The Graphical Password Authenticator is a groundbreaking step at the intersection of user authentication and innovation. By redefining the way users prove their identity through memorable graphical elements, this approach empowers users with a more secure and intuitive means of accessing their digital resources. This paradigm shift in authentication methods showcases the potential of technology to enhance user security and create a safer digital future, ultimately bridging the gap between user convenience and robust cybersecurity.

Synergies and Challenges in the Integration of Cloud Computing and Deep Learning: Current Status, Interconnectedness, and Future Directions

This article reviews the status and recent developments in the integration of cloud computing and deep learning, as well as the interrelationship between these two technologies. The paper explores the intersection of cloud computing and deep learning in addressing cybersecurity challenges. Amidst the rapid expansion of the worldwide public cloud services market, the vulnerability to cyber-attacks and breaches in data management is on the rise. Different intrusion detection systems use different deep learning techniques to improve the effectiveness of intrusion detection in cloud computing environments. Additionally, the use of encryption technology and the corresponding deep learning retrieval technology further improves the security of cloud data. Moreover, the paper deeply studies how the scheduling mechanism of deep reinforcement learning can optimize the performance of cloud services by efficiently allocating resources and solving the problem of slow cloud service speed. It also derives the optimal energy strategy through deep neural networks to address the energy consumption challenges in cloud computing data centers. This article also reviews the five emerging architectures of cloud computing and explores the role of deep learning within these frameworks. Finally, it analyzes some of the challenges facing the future of cloud computing and deep learning, including the security and confidentiality of cloud computing, as well as low latency and high throughput optimization in the field of deep learning. In summary, this article provides insight into current trends, challenges, and future prospects for the evolving integration between cloud computing and deep learning.

Research on the Application of Data Encryption Technology in Computer Network Communication Security

With the rapid development of information technology, computer network communication has been widely used in various fields. However, the security issues of network communication have become increasingly prominent, and data is vulnerable to various attacks during transmission. Data encryption technology is a key technology for protecting information security. By converting plaintext information into non-mandatory ciphertext, the confidentiality and non-threatening nature of data are protected. This paper first introduces the basic principles and classification of data encryption technology, including real-time encryption, real-time encryption and hybrid encryption. It mainly analyzes the specific applications of data encryption technology in virtual private networks (VPNs), secure gateway security layers (SSL)/transport layer security (TLS), wireless network security, email encryption and cloud storage encryption. Finally, the development trends of emerging technologies such as quantum encryption, homomorphic encryption and blockchain encryption are discussed. By reasonably applying these encryption technologies, the security of computer network communication can be effectively improved.

Multi-channel polarization manipulation based on graphene for encryption communication

Wave-based cryptography, at the vanguard of advancing technologies in advanced information science, is essential for establishing a diverse array of secure cryptographic platforms. The realization of these platforms hinges on the intelligent application of multiplexing techniques, seamlessly combined with appropriate metasurface technology. Nevertheless, existing multi-channel encryption technologies based on metasurfaces face challenges related to information leakage during partial channel decoding processes. In this paper, we present a reprogrammable metasurface for polarization modulation. This metasurface not only allows for the arbitrary customization of linearly polarized reflected waves but also enables real-time amplitude modulation. Here, relying on polarization amplitude control, a fully secure communication protocol is developed precisely in the terahertz (THz) spectrum to achieve real-time information encryption based on polarization modulation metasurfaces where access to information is highly restricted. The proposed metasurface employs the double random phase encryption (DRPE) algorithm for information encryption. It transmits the encrypted data through different polarization channels using two graphene nanoribbons, exclusively controlled by external biasing conditions. Various encryption scenarios have been outlined to fortify information protection against potential eavesdroppers. The simulated results show that this unique technology for hiding images by manipulating the polarization of the reflected wave provides new opportunities for various applications, including encryption, THz communications, THz secure data storage, and imaging.

Short message encryption technology of Beidou communication based on SM9

AbstractTo reduce the security authentication time cost, forwarding delay, and enhance message security of Beidou communication short messages, this paper proposes a Beidou communication short message encryption technology based on SM9 (Mobile Code Secure Communication). This technology uses split hierarchical clustering algorithm to cluster the short message data of Beidou Communication, in order to unify the processing of similar short message data and improve the encryption efficiency of subsequent short messages. Based on the data clustering results, this paper constructs a short message forwarding verification model using the SM9 identification password algorithm, and provides the message content of the communication application protocol and the communication receiving information protocol to achieve low‐cost and efficient forwarding verification. In addition, this article improves the initial value selection of Logistic chaotic mapping by coupling the tent map with coupled mapping lattice (CML) in the spatiotemporal chaos model to generate a chaotic initial value sequence, thereby expanding the key space, enhancing the ability to resist exhaustive attacks, enhancing the randomness of the generated key parameters, and optimizing the encryption effect of short messages. The experimental results show that the short message security authentication time of the technology proposed in this article is basically controlled within 25 ms, and the minimum forwarding delay is only 23.9 ms, which can effectively resist attacks and improve the security of Beidou communication.

Cloud Enabled e-Banking Payment Security Implementation using Blockchain Technology

Cloud computing has revolutionized the banking industry by offering flexible and flexible products for the delivery of electronic banking services. However, due to the sensitivity of the central authority, ensuring the security of online transaction is still a critical issue. In this context, blockchain technology is promising by offering decentralization, transferability and cryptographic security. This article presents a new way to increase the security of electronic banking payments by combining blockchain technology with cloud computing. The system plans to use the cloud to host business applications and services, and use blockchain to securely record and verify transactions. Smart contracts are used to streamline the payment process and manage transactions, providing transparency and trust. Additionally, encryption technology is used to encrypt sensitive information and protect the user's identity. Using this solution provides many benefits, including improving the security, transparency and efficiency of electronic banking. Research articles and experimental results demonstrate the effectiveness and applicability of the proposed process in real life. Overall, the integration of blockchain technology with cloud banking provides a solution to solve security issues and increase the reliability of online payments.

Integrated Two-Level New Energy Monitoring and Big Data Centers: A Comprehensive Approach for Urban Sustainability

This study examines the transition to green energy in Wenzhou City and suggests a novel plan for integrating an energy monitoring and data center. The aim is to improve the city's sustainability through the building of a large-scale wind-solar integrated energy monitoring system by a group in Wenzhou City. The solution uses the Internet of Things and intelligent data analysis technology to realize real-time data collection, processing and operation and maintenance decision support for distributed power stations. The system adopts storage-computer separation and data encryption technology to ensure data security and system stability and improves data processing efficiency through containerization and microservice architecture. In addition, the study also explores the application potential of this technical scheme in regional energy planning, which provides a new idea for Wenzhou to achieve green energy transformation and low-carbon development.

Lossless and lossy remote sensing image encryption-compression algorithm based on DeepLabv3+ and 2D CS

With the advancement of remote sensing technology, the amount of remote sensing image (RSI) has increased sharply. The explosion in data volume requires higher standards of image compression and encryption technology. This paper proposes a lossless and lossy encryption-compression method for RSI. Because RSIs contain important and unimportant information, using a normal algorithm could ignore their important information or reduce the computational efficiency, so we use the trained model by DeepLabv3+ to segment the region of interest (ROI) and the region of non-interest (RONI), and implement lossless and lossy algorithms respectively. The whole algorithm is based on the newly proposed hyperchaotic system 2D Tent coupled Infinite collapse map (2D TICM). According to the 2D TICM, the dynamic 3D Latin cube is generated. This cube is then used for dynamic scrambling algorithms between multiple planes (3D LMBS), within planes (3D LMIS), and for the multiple dynamic S boxes substitution algorithm. Due to the large size of RSI, the image is divided into blocks, and MATLAB parallel mechanism is used to encrypt each block at the same time. First, the lossy part is scrambled by 3D LMIS, then compressed with 2D compressive sensing (2D CS). Finally, each block is substituted with a different S box. A CS reconstruction algorithm combining decryption and reconstruction, 2D projection gradient chaotic decryption algorithm (2D PG-CD), is proposed. The lossless part embeds the encryption into JPEG-LS, encrypts while compressing, and then encrypts according to 3D LMBS and S boxes. The algorithm in this paper considers the characteristics of RSI, experiments show that it has good security and compression performance.

A Survey on the Advanced Encryption Standard (AES): A Pillar of Modern Cryptography

As the digital landscape expands and our reliance on secure data transmission grows, the adoption of encryption technologies has become paramount. Over time, we have witnessed a progression from rudimentary ciphering methods, like substitution ciphers, to the sophisticated algorithms of today, epitomized by the Advanced Encryption Standard (AES). AES’s ascendancy to the forefront of encryption can be attributed to its unparalleled security features, surpassing its predecessors such as the Data Encryption Standard (DES). AES boasts robust security measures, rendering it virtually impervious to conventional cryptographic attacks. Its resilience against decryption is underscored by its intricate encryption process, which involves intricate operations such as byte substitution, row shifting, column mixing and round key addition. Conversely, decryption reverses these steps, ensuring the confidentiality of encrypted data remains intact. Despite the emergence of various cryptographic attacks, none have posed a significant threat to a properly implemented Full-AES algorithm. Most attacks target incomplete implementations, highlighting the importance of proper implementation practices in maximizing AES’s security benefits. Beyond its security prowess, AES stands out for its efficiency, sustainability and simplicity. Despite its widespread adoption and robustness against cryptanalytic attacks, AES exhibits an intriguing phenomenon known as error propagation. Through theoretical analysis and empirical investigations, we elucidate the mechanisms by which errors propagate within AES, shedding light on the vulnerabilities they introduce. Additionally, we explore the implications of error propagation in practical scenarios, including its impact on cryptographic protocols, error correction mechanisms and overall system reliability. Our findings underscore the importance of comprehensively understanding and mitigating the effects of error propagation in AES implementations, offering insights into enhancing the resilience of cryptographic systems against unforeseen adversities.

Polyacrylamide/sodium alginate/sodium chloride photochromic hydrogel with high conductivity, anti-freezing property and fast response for information storage and electronic skin

Photochromic hydrogels have promising prospects in areas such as wearable device, information encryption technology, optoelectronic display technology, and electronic skin. However, there are strict requirements for the properties of photochromic hydrogels in practical engineering applications, especially in some extreme application environments. The preparation of photochromic hydrogels with high transparency, high toughness, fast response, colour reversibility, excellent electrical conductivity, and anti-freezing property remains a challenge. In this study, a novel photochromic hydrogel (PAAm/SA/NaCl-Mo7) was prepared by loading ammonium molybdate (Mo7) and sodium chloride (NaCl) into a dual-network hydrogel of polyacrylamide (PAAm) and sodium alginate (SA) using a simple one-pot method. PAAm/SA/NaCl-Mo7 hydrogel has excellent conductivity (175.9 S/cm), water retention capacity and anti-freezing properties, which can work normally at a low temperature of −28.4 °C. In addition, the prepared PAAm/SA/NaCl-Mo7 hydrogel exhibits fast response (<15 s), high transparency (>70 %), good toughness (maximum elongation up to 1500 %), good cyclic compression properties at high compressive strains (60 %), good biocompatibility (78.5 %), stable reversible discolouration and excellent sensing properties, which can be used for photoelectric display, information storage and motion monitoring. This work provides a new inspiration for the development of flexible electronic skin devices.

Enhancing Security and Sensors Emerging Internet of Things (IoT) Technology of Homophone-Based Encryption using MANET‐IoT Networks Technique

The emerging Internet of Things (IoT) technology brings several benefits to the real-time applications of the smart city project. The IoT-enabled technologies are driven by the networks like Mobile Ad hoc Network (MANET), Vehicular Ad Hoc Network (VANET), Wireless Sensor Network (WSN), Underwater Wireless Sensor Network (UWSN), etc. The core functionality of IoT-enabled technologies mainly depends on routing functionality. The focus of this work is on the IoT-enabled MANET, i.e., IoT-MANET routing methods. There are several types of research conducted so far on the efficiency of MANET in different areas such as routing protocol, MAC protocol, queue, etc. Routing protocols are the major domain on which the performance of IoT-MANET has been analyzed. There are different types of routing protocols have introduced for the MANETs. The use and selection routing methods are done as per the real-time application needs. An average Ad hoc On-Demand Vector (AODV) routing protocol had shown good results under any type of network. The increase in internet usage for communication has led to a significant growth in the volume of data being transmitted over the internet, including computer data, text, video, audio, sound, and images. However, due to limited network capacities, efficient compression methods are needed to reduce the amount of data while preserving its quality and ensuring timely transmission. Data confidentiality is a crucial aspect of network security, and the homophone-based encryption with compression (HEC) technique offers a viable solution in this regard.

CoTNeT: Contextual transformer network for encrypted traffic classification

As network infrastructures continue to grow and traffic encryption technologies evolve at a rapid pace, the task of classifying encrypted traffic has become significantly more intricate. These emerging encryption methods render conventional approaches ineffectual in discerning traffic types, consequently posing novel challenges to network security and administration. Evidently, conventional traffic classification techniques are inadequate when it comes to encrypted traffic. Consequently, researchers have turned to machine learning and deep learning models to address this challenge, achieving remarkable results in this domain. Nonetheless, contemporary deep learning models exhibit a propensity to overly depend on self-attention mechanisms while processing 2D feature maps. This mechanism typically focuses only on individual query-key pairs, neglecting the rich contextual information among adjacent keys, thereby limiting their performance in encrypted traffic classification. To address this limitation, our study examines an innovative approach called CoTNet. The CoT module is integrated into the ResNet model to more comprehensively exploit the contextual associations among input keys. This innovation engenders a sturdier and more potent classification model, adept at comprehensively capturing the inherent patterns and correlated information within input features. The suggested method enhances the ResNet model by substituting the conventional 3x3 convolution operations with CoT modules, thereby more effectively harnessing the contextual associations among input keys. In particular, we integrate self-attention mechanisms at various model levels to more thoroughly capture the inherent patterns and correlated information within input features. Experimental results on two real-world datasets show that CoTNet outperforms multiple state-of-the-art methods in the encrypted traffic classification task.

Exploring Financial Risks and Risk Mitigation Strategies in Digital Currencies

This paper comprehensively analyzes the financial risks faced by digital currency, using digital renminbi as a case study. The risks include operational risks, privacy risks, legal and regulatory risks, currency sovereignty risks, and the impact on traditional financial systems. Corresponding risk mitigation strategies are proposed. By strengthening system architecture, employing advanced encryption technologies, enhancing legal and regulatory frameworks, maintaining policy stability, and promoting financial integration, these measures effectively mitigate financial risks associated with digital currency, fostering its sustainable development and innovation.

Design of Privacy Protection System for Target Search Based on Selection Algorithm and Sustainable Iteration Index

The data self-destruct method based on privacy cloud proposed in this paper can realize the automatic destruction of cloud data after expiration, and based on this method, a self-destruct image protection system is implemented. This project intends to combine the adaptive scale invariant Feature conversion (SIFT) extraction of ciphertext images with binary SIFT to ensure the confidentiality of the images uploaded to the server in the ciphertext space. The security protection of data is realized using Paillier homomorphic encryption technology. The feature of SIFT is extracted from the encrypted region, and it is expressed in binary form to reduce the amount of computation and memory overhead. The experimental results show that this method can effectively prevent the automatic destruction of images after expiration, so as to ensure that the user's personal information is not leaked.

Silicon Vacancies Diamond/Silk/PVA Hierarchical Physical Unclonable Functions for Multi-Level Encryption.

Physical unclonable functions (PUFs) have emerged as a promising encryption technology, utilizing intrinsic physical identifiers that offer enhanced security and tamper resistance. Multi-level PUFs boost system complexity, thereby improving system reliability and fault tolerance. However, crosstalk-free multi-level PUFs remain a persistent challenge. In this study, a hierarchical PUF system that harnesses the spontaneous phase separation of silk fibroin /PVA blend and the random distribution of silicon-vacancy diamonds within the blend is presented. The thermodynamic instability of phase separation and inherent unpredictability of diamond dispersion gives rise to intricate random patterns at two distinct scales, enabling time-efficient hierarchical authentication for cryptographic keys. These patterns are complementary yet independent, inherently resistant to replication and damage thus affording robust security and reliability to the proposed system. Furthermore, customized authentication algorithms are constructed: visual PUFs authentication utilizes neural network combined structural similarity index measure, while spectral PUFs authentication employs Hamming distance and cross-correlation bit operation. This hierarchical PUF system attains a high recognition rate without interscale crosstalk. Additionally, the coding capacity is exponentially enhanced using M-ary encoding to reinforce multi-level encryption. Hierarchical PUFs hold significant potential for immediate application, offering unprecedented data protection and cryptographic key authentication capabilities.

Banks, open banking and data protection

As economic systems continue to evolve, with a particular focus on digital, the banking sector is at the forefront of technological advances, revolutionizing the way customers' finances are managed. With the rapid digitization of financial technologies, the importance of bank data protection and confidentiality measures increases, especially in the context of cross-border data transfers in which different actors are involved, both from the regulated financial-banking area and from less regulated areas, which together can offer open banking services (open-banking). Banking entities around the world are entrusted with customers' sensitive personal and financial data, making the principle of data security a primary concern for maintaining customer trust. Effective data protection in banking encompasses a complex approach, in strict compliance with applicable national and international regulations, state-of-the-art encryption technologies and comprehensive risk management strategies to maintain the highest standards of security, transparency and trust in the system banking.

The Dark Web: Challenges and Countermeasures in Combating Cybercrime

Abstract: This research paper delves into the complexities surrounding "The Dark Web: Challenges and Countermeasures in Combating Cybercrime." As the Dark Web continues to be a breeding ground for illicit activities, this study examines the multifaceted challenges faced by law enforcement. Factors such as limited visibility, encryption technologies, and jurisdictional obstacles hinder effective intervention. In exploring countermeasures, the paper evaluates technological advancements and legal frameworks deployed to mitigate cyber threats. Ethical considerations are scrutinized in striking a balance between privacy rights and the imperative to combat criminal activities. The abstract encapsulates an analysis of these challenges and proposes insights into the evolving landscape of cybercrime prevention on the Dark Web

Application analysis of data encryption technology

Data encryption technology is a key method to secure sensitive data. The privacy and confidentiality of data is protected by encrypting the data, i.e., transforming the original data into a form that cannot be understood without authorization. However, the security of traditional encryption algorithms is gradually challenged with the increase in computing power. Therefore, studying how to apply more advanced encryption techniques has become a current research hotspot. This study aims to analyze the application of data encryption techniques and explore the advantages and applicability of emerging encryption algorithms. This paper presents a variety of methods for preventing users' privacy breaches, with a primary focus on the principles of homomorphic encryption and how data can be accessed by users without decryption. Additionally, the working principles of secure multiparty computation are discussed, allowing multiple users to perform calculations on shared data while preserving data privacy. Furthermore, the paper explores data encryption techniques that employ specific algorithms to convert plaintext into ciphertext, ensuring both data consistency and privacy. Finally, a summary and future prospects are provided.