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检索条件"任意字段=Conference on Advances in Optical Data Storage Technology"

共 5078 条记录，以下是21-30 订阅

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The study on the circuit architecture of reconfigurable physics-based unclonable technology 5

The study on the circuit architecture of reconfigurable phys...

引用

5th International conference on Signal Processing and Computer Science, SPCS 2024

作者： He, Baigen Qiu, Ganggang Jiangsu Automation Research Institute Jiangsu Lianyungang222000 China

ISBN: (数字)9781510686731

ISBN: (纸本)9781510686724

With the rapid development of computer technology and internet technology, the issue of information security has become increasingly prominent. Physical Unclonable technology (PUT), based on circuit implementation, is a high-security technology that differs from traditional cryptography in that it employs logic gates with variable quantities and distinct gate circuits. PUT can be applied in various fields such as authentication, secure encryption, cryptographic computation, and more. Compared to traditional cryptography, PUT offers advantages including high security, strong resistance to attacks, and flexible operation, which has led to its widespread application in the field of information security. Information security refers to the protection and maintenance of information resources from unauthorized or inappropriate access, use, modification, and other potential hazards. It is a product of the information age, encompassing any actions or events that may cause or potentially cause damage to information resources. Traditional cryptography has some drawbacks in ensuring data security, such as the ease of device loss, inconvenient key storage, and difficulties in decryption. Therefore, the development of new cryptographic technologies is necessary to address these issues. © 2025 SPIE.

关键词： Digital storage

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Intelligent connected vehicle data security based on Blockchain combining Zero-Knowledge Proof and Post-Quantum Cryptography 2

Intelligent connected vehicle data security based on Blockch...

引用

2nd International conference on Big data, Computational Intelligence, and Applications, BDCIA 2024

作者： Luo, Yunxi Guangxi Vocational Normal University Guangxi Nanning China Key Laboratory of Application Technology of Intelligent Connected Vehicle Guangxi Vocational Normal University Education Department of Guangxi Zhuang Autonomous Region Guangxi Nanning China

ISBN: (纸本)9781510689053

Aiming at the severe challenges of Intelligent Connected Vehicle (ICV) in the field of data security, this paper designs a four-layer ICV data security framework, which covers the whole process from data collection, processing, storage and sharing to privacy protection. In the security framework, three technical methods of Blockchain, Zero-Knowledge Proof (ZKP) and Post-Quantum Cryptography (PQC) are integrated. Blockchain is used to provide distributed trust mechanism and tamper-resistant data storage. ZKP is used to protect data privacy and realize data verification without leaking sensitive information. PQC is used to enhance data encryption and authentication mechanism to resist quantum computing attacks. At the same time, the data sharing security strategy is formulated, including initialization and key generation, data transmission preparation, zero-knowledge proof generation and verification, data reception and verification, Blockchain recording and consensus, access control and data usage, etc., to ensure the security and privacy protection of data during the sharing process. The simulation experiment data of delay time, throughput and privacy protection intensity in the simulation environment show that the scheme not only enhances data privacy protection and data integrity verification, but also improves the system's ability to resist future quantum computing threats, and provides a solid guarantee for the data security of intelligent connected vehicles. © 2025 SPIE.

关键词： data integrity

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Algorithm Implementation of Digital Protection System for Traditional Cultural Industry Based on Grey Clustering

Algorithm Implementation of Digital Protection System for Tr...

引用

2024 International conference on Mechatronics and Intelligent Control, ICMIC 2024

作者： Chen, Hongxia Hou, Lanbao School of Literature and Media Jingchu University of Technology Jingmen448000 China School of Mathematics and Physics Jingchu University of Technology Jingmen448000 China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

The protection mode of digitalization effectively transforms various national traditional cultures into digital products, providing a way of thinking for the protection of national traditional cultures. This mode still lacks the mode of how to mine the data of national traditional culture and analyze the internal relationship structure after facing the massive data, which can guide the digital protection of national traditional culture under the complex social conditions in the future. This paper discusses the significance of digitalization for the protection of traditional national culture under the environment and ideology of big data development. The possibility of protecting traditional national culture based on big data was analyzed and discussed. This paper designs and establishes the digital perception analysis system of traditional culture. The system uses grey clustering algorithm to identify the characteristics of cultural products. The experimental results show that this method can improve the efficiency of traditional cultural product classification. This method has certain reference value for the research of digital protection system of traditional cultural industry. © 2025 SPIE.

关键词： Augmented reality Visualization Telecommunications Computing systems Cultural heritage data communications Image processing Video data storage Cameras

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Development of a Python-based comprehensive employment data visualization platform 2

Development of a Python-based comprehensive employment data ...

引用

2nd International conference on Big data, Computational Intelligence, and Applications, BDCIA 2024

作者： Wu, Yuanyuan Li, Shenghao School of Big Data and Internet of Things Chongqing Vocational Institute of Engineering Chongqing404100 China

ISBN: (纸本)9781510689053

In order to achieve real-time monitoring of employment positions and evaluate industry development potential, a method for building a B/S based employment position data visualization monitoring platform was explored. Through core processes such as data collection, data cleaning, feature extraction, and visualization analysis, it provides support for relevant departments' supervision and decision-making. The platform calls the PyEcharts third-party library to achieve data visualization monitoring, uses Python to process and analyze employment data, draws data into analyzable charts, and stores them in the database. Then, relying on the Bootstrap framework, HTML, CSS, and JavaScript technologies are used to complete the front-end interactive pages of the platform. The data visualization monitoring platform is used to achieve data sharing and visualization chart analysis in the database, providing strong technical support for industry regulation. © 2025 SPIE.

关键词： data visualization Visualization data processing Industry data analysis data storage databases data modeling Image processing Analytical research

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Design and construction of remote data disaster recovery center based on cloud storage 5

Design and construction of remote data disaster recovery cen...

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5th International conference on Telecommunications, Optics, and Computer Science, TOCS 2024

作者： Song, Tao Zhou, Hang Liaoning Economic Vocational Technological Institute Shenyang 110122 China

ISBN: (纸本)9781510691667

With the rapid development of information technology, data centers have become increasingly central to modern enterprises and government agencies. To ensure data security and business continuity, a disaster recovery backup system is crucial for data centers. However, traditional disaster recovery solutions face high deployment costs, low recovery efficiency, and limited scalability, especially when dealing with complex business needs and constantly changing technical environments. This study proposes a cloud-based disaster recovery center design solution, aiming to achieve off-site backup, real-time data synchronization, and rapid recovery by combining cloud storage technology with advanced disaster recovery strategies. The solution significantly enhances data security and business continuity, especially in addressing risks such as natural disasters, equipment failures, and human errors, providing more efficient and flexible solutions. The research shows that the cloud-based disaster recovery solution not only reduces the high costs of traditional disaster recovery backup solutions but also ensures zero data loss (RPO=0) and rapid recovery (RTO≈5 minutes) under complex business environments, meeting the data protection needs of complex business environments. This study provides new ideas for the design and optimization of disaster recovery backup systems for data centers, and provides theoretical support and practical guidance for the future application of cloud storage technology in disaster recovery systems. © 2025 SPIE.

关键词： cloud storage continuous data protection data centers remote data disaster recovery

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Intelligent data transmission system for digital power enterprise architecture: Based on deep reinforcement learning 2

Intelligent data transmission system for digital power enter...

引用

2nd International conference on Big data, Computational Intelligence, and Applications, BDCIA 2024

作者： Zhang, Yu Liu, Yaqing Hu, Dongliang Zhang, Chengping Meng, Dejian Yan, Weisi Co. Ltd. Beijing102211 China Beijing SGITG Accenture Information Technology Center Co. Ltd. Beijing100190 China

ISBN: (纸本)9781510689053

Under the framework of digital power enterprise, the research of data transmission system is crucial to improving the intelligent level of power data processing. In order to efficiently and safely transmit massive and scattered power data, while ensuring the security and integrity of the data. The paper proposes an intelligent data transmission system based on improving the deep reinforcement learning process. The transmission strategy is dynamically adjusted through the Actor-Critic framework, the data transmission path is optimized, and the data compression and decompression technology is introduced to reduce the transmission cost and improve the security. The experimental results show that the performance coverage of the algorithm is 94% and 97.8%;the case coverage remains above 90% and 92%. In the task time effect analysis, the data processing time of the system is at least 1h, and the maximum time is not more than 5h, indicating that the system has strong data generation ability. It proves that the research and designed intelligent data transmission system provides an effective solution for the data management and transmission of power enterprises, provides a solid foundation for the development of smart grid, and improves the efficiency and stability of data transmission. © 2025 SPIE.

关键词： data transmission data processing Intelligence systems Wavelets data storage Transportation Computer security Deep learning Education and training Power grids

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Automated execution algorithm for smart contracts in payment systems based on blockchain and big data 4

Automated execution algorithm for smart contracts in payment...

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4th International conference on Computer Vision, Application, and Algorithm, CVAA 2024

作者： Lin, Shuhong Ruan, Juanping Chen, Lihong Lin, Yishan Zou, Limei Pan, Liumei Fu Jian Yi Li Dian Li Ke Ji Co. Ltd. Fuzhou350001 China State Grid Info & Telecom Group Fuzhou350001 China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

Smart contracts, as one of the important applications of blockchain technology, provide the possibility for automated execution of payment systems. This article explores an automated execution algorithm for smart contracts in payment systems based on blockchain and big data technology to address the issues of low accuracy and efficiency in contract execution. This algorithm utilizes the immutability and decentralization features of blockchain to ensure the security and transparency of payment transactions. At the same time, combined with the powerful analytical capabilities of big data, deep mining of transaction data is carried out to achieve accurate prediction and risk management of transactions. The automated execution function of smart contracts further simplifies the transaction process, reduces human intervention, and improves the efficiency and reliability of payment systems. The experimental results show that through the proposed algorithm, the payment system can provide more secure, efficient, and personalized services, promoting the digital transformation and development of the financial transaction field. © 2025 SPIE.

关键词： Blockchain data modeling data processing Automation Computer security data storage Transparency data communications Statistical modeling Symmetric key encryption

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20th IFIP WG 11.9 International conference on Digital Forensics, DigitalForensics 2024

20th IFIP WG 11.9 International Conference on Digital Forens...

引用

20th IFIP WG 11.9 International conference on Digital Forensics, DigitalForensics 2024

ISBN: (纸本)9783031710247

The proceedings contain 15 papers. The special focus in this conference is on Digital Forensics. The topics include: Forensic Analysis of Third-Party Cloud Software Development Kits for Android Apps;identifying and Analyzing Vault Apps;using Microposture Features and optical Flows for Deepfake Detection;assessing Backdoor Risk in Deepfake Detection;user Behavior Forensics on Encrypted Traffic in the Industrial Internet of Things;digital Forensic Acquisition Using Private Internet of Things Cloud Application Programming Interfaces;fingerprinting Malware Families Under Uncertainty;improving Android Malware Detection in Imbalanced data Scenarios;text File Recovery Using an N-Gram Model;generating Usable and Assessable datasets Containing Anti-Forensic Traces at the Filesystem Level;leveraging Client-Side User Account data in Digital Forensic Investigations;honeypot-Based data Collection for Dark Web Investigations Using the Tor Network;modeling Analyst Intentions Using a Markov Chain for Investigative Action Recommendations.

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Optimized Hybrid Cryptographic Technique Using Symmetric and Asymmetric Encryption for Cloud Computing 5

Optimized Hybrid Cryptographic Technique Using Symmetric and...

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5th IEEE International conference on advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2025

作者： Suresh, R. Dayana, T.R. Nisha Vel's Institute of Science Technology and Advanced Studies Department of Computer Science Tamil Nadu Chennai India

ISBN: (纸本)9798350356236

Cloud Computing (CC) is an expanding computing concept in which computing resources are given as Internetbased services. Security and confidentiality of cloud storage services are critical and pose a difficulty in cloud computing owing to loss of control over data and reliance on the cloud computing provider. While there is a big number of transmitting data in the cloud system, the risk of data access by attackers raises. CC requires encryption to maintain the privacy and security of data stored, processed, and transported on the cloud. Encryption ensures that confidential information saved in the cloud stays private and accessible only to authorized parties. The field of cryptography is continuously evolving to deal with current challenges in cybersecurity, confidentiality, and computing power. Optimizing encryption algorithms entails enhancing security, performance, and efficiency while reducing resource usage. This study suggests a optimized framework for encryption using RSA, an asymmetric key cryptography for key exchange and Advanced / Encryption Standard (AES), a symmetric key cryptography for bulk message encryption to improve the efficiency of encryption. The suggested models's performance evaluated with RSA with data Encrytpion Standard(DES) and RSA with BlowFish algorithms and the efficiency of RSA with AES is found to more in terms of Execution time, Throughput, memory usage and latency. © 2025 IEEE.

关键词： Sensitive data

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Historical data-driven approach for energy storage system state of charge estimation

Historical data-driven approach for energy storage system st...

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2024 International conference on Energy technology and Electrical Power, ETEP 2024

作者： Guan, Baiyao Jiang, He Guo, Rui School of Renewable Energy Shenyang Institute of Engineering Shenyang 110136 China

ISBN: (纸本)9781510690400

State of charge (SOC) is a key parameter in lithium battery management technology, and accurate estimation of the SOC of an energy storage system facilitates its grid-connected operation and control. In this paper, a historical data-driven SOC estimation method is proposed to analyse the relationship between the storage system voltage, current, average temperature and other factors on the SOC, and to obtain the predicted value of the SOC. In this paper, a bidirectional long and short-term memory multi-head neural network is used for prediction, and particle swarm optimization algorithm (PSO) is used to find the optimal of its parameters, which makes the predicted SOC of energy storage system closer to the real value compared with other models, with a better training effect, and the performance is better than that of the traditional single neural network model, and improves the accuracy of prediction. © 2025 SPIE.

关键词： Energy storage system long and short-term memory networks particle swarm optimization state of charge

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