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共 18583 条记录，以下是31-40 订阅

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Comparison of data Encryption Standard (DES) and advanced Encryption Standard (AES) in Security Issues of Cloud computing: A Literature Review 12th

Comparison of Data Encryption Standard (DES) and Advanced En...

引用

12th international conference on Frontiers of intelligent computing: Theory and Applications, FICTA 2024

作者： Basco, Jhonna Zelle E. Romualdo, Annielyn F. Saluta, Jefferson A. Santiago, Cereneo S. Marfil, Rowee M. Cavite State University—Silang Campus Cavite Philippines Eulogio "Amang" Rodriguez Institute of Science and Technology Cavite Philippines

ISBN: (纸本)9789819601462

This paper compares the data Encryption Standard (DES) and the advanced Encryption Standard (AES) regarding cloud computing security issues. DES and AES, based on their performance in cloud computing, were synthesized. This review contains the common security issues encountered in cloud computing, helping the users to decide what algorithm is the best to use in securing data. A comprehensive analysis of related studies between 2014 and 2023 was done, utilizing reliable databases, including ieee, Google Scholar, and Science Direct. After a deep screening, 24 articles were selected, considering the scope and gap of the review. The results show that both algorithms are used to protect confidential data by blocking unauthorized individuals from reading or accessing sensitive data. The results provided the claim that resolving the cloud computing issues should consider the availability, responsibility, and especially security, as stated that cloud computing holds confidential and sensitive data. It includes hackers that use different techniques to attack and take advantage of the system, resulting in access without authentication, owing to the difference between vulnerability and attack, and providing AES as more secure compared to DES when implemented and supported by different studies. This study provides a strategic solution for choosing the best algorithm between DES and AES to solve cloud computing security issues. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cloud security

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Assessment and Management of Security Risks in Accounting Information systems from a Lifecycle Perspective

Assessment and Management of Security Risks in Accounting In...

引用

2024 international conference on Mechatronics and intelligent Control, ICMIC 2024

作者： Gong, Lijiahui Business School Wuhan Huaxia Institute of Technology Wuhan430223 China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

As the carrier of information assets, the importance of accounting information systems is increasing with the development of informatization. Meanwhile, information systems are facing more security threats. How to effectively ensure the security of information systems and prevent information assets from being stolen or damaged has become an inevitable challenge. Therefore, conducting research on the security issues of information systems is of great significance. In response to the data security risks in accounting information systems, this article first establishes a risk indicator system and proposes an information system risk assessment model based on adaptive fuzzy neural networks, which scores the risk indicator attributes during the assessment process. In addition, we propose a fine-grained weight adaptive adjustment algorithm in the model, which provides a quantitative method for the risk indicators of accounting information systems. The feasibility and applicability of the model have been verified through simulation testing. © 2025 SPIE.

关键词： Information security Risk assessment Network security Computer security computing systems Fuzzy logic Situational awareness sensors Neural networks systems modeling Prototyping

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Recommendation System using Emotion Detection 3

Recommendation System using Emotion Detection

引用

3rd international conference on intelligent data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Susindra, S. Sweta, B. Keerthikha Shri, R. Brindha, K. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798331527549

The need for a personalized user experience brought recommendation systems to the forefront of digital innovation. However, traditional approaches tend to often forget human emotions, which represent a critical driver in decision making. The paper proposes a new framework in which the detection of emotions becomes part of the recommendation system through advanced facial expression analysis and sentiment evaluation. The paper discusses a hybrid architecture combining emotion recognition via CNN and a collaborative filtering technique for dynamic recommendations. The study outcome demonstrated an enormous improvement in user engagement and satisfaction. It further underlines the transformative potential of emotion-aware systems. © 2025 ieee.

关键词： Emotion Recognition

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Design and Simulation of an intelligent Traffic Management System Using Vehicular Networks 3

Design and Simulation of an Intelligent Traffic Management S...

引用

3rd international conference on intelligent data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Tapan Datta, P. Lalith Kumar, D. Tanoj, S. Rajagopal, Shinu M. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

In this study, the reasearch is focused on the simulation of vehicular communication networks, especially intelligent traffic systems, to enhance dependability, safety, and optimality in communication. The simulation is performed using the OMNeT++ simulator and is integrated with the Veins framework that uses the ieee 802.11p protocol for V2V and V2I communications. Importing real-world traffic scenarios into the framework is obtained via the use of SUMO through TraCIScenarioManager. Other features of the framework include the definition of mobility models, dynamic obstacles, and detailed radio propagation modeling. TraCIDemo11p is used for mobility and communication by both RSUs and vehicles with applications in beaconing and channel switching. The whole framework analyzes smart traffic management solutions, providing as much insight into their performance based upon the communication reliability and overall efficiency in vehicular networks. © 2025 ieee.

关键词： Highway administration

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Research on the Application of Artificial Intelligence in Green Building Design Optimization

Research on the Application of Artificial Intelligence in Gr...

引用

2024 international conference Optoelectronic Information and Optical Engineering, OIOE 2024

作者： Yu, Yao Mingyueshan Forest Farm Nan'an District Chongqing City China

ISBN: (数字)9781510688209

ISBN: (纸本)9781510688193

Facing climate change and resource constraints, this article explores the innovative application of artificial intelligence in green building design. It proposes intelligent solutions based on machine learning and optimization algorithms, enhancing energy-saving systems, renewable energy utilization, and indoor environment control. Key findings include a 17.6% reduction in energy consumption, a 68% increase in renewable energy utilization, a 10.3% improvement in indoor comfort, and significant energy savings. The research constructs a comprehensive green building optimization system, achieving notable energy-saving and environmental protection effects, contributing to the development of intelligent green buildings. © 2025 SPIE.

关键词： Artificial intelligence Design data modeling Renewable energy Evolutionary algorithms Mathematical optimization Particle swarm optimization data acquisition Deep learning Thermal modeling

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Edge-Centric IoT Health Monitoring: Optimizing Real-Time Responsiveness, data Privacy, and Energy Efficiency 6

Edge-Centric IoT Health Monitoring: Optimizing Real-Time Res...

引用

6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Swathi, B. Veerabomma, Supraja Archana, M. Bhadru, Dharavath Somu, Naga Lakshmi Bhavsingh, M. Dept of CSE G Pulla Reddy Engineering College A.P. Kurnool India Department of ECE G Pullaiah College of Engineering and Technology A.P. Kurnool India Department of Computer Science and Engineering CVR College of Engineering Vasthunagar Hyderabad India CSE Department NarSimha Reddy Engineering college Telangana Maisammaguda India Shri Jagdishprasad Jhabarmal Tibrewala University Rajasthan Jhunjhunu India Department of CSE Ashoka Women’s Engineering College Andhra Pradesh Kurnool India

ISBN: (纸本)9798331522667

The innovation of IoT and edge computing has significantly advanced real-time health monitoring systems by providing timely data processing, improved responsiveness, and enhanced data privacy. This study introduces the Edge-Centric IoT Health Monitoring System (EC-HMS), which overcomes limitations observed in cloud-based and hybrid models, including high latency, data privacy vulnerabilities, and excessive energy consumption. EC-HMS leverages localized edge processing to reduce latency, safeguard sensitive data, and optimize energy efficiency, thereby enabling real-time health interventions. The proposed architecture integrates data acquisition, filtering, and anomaly detection at the edge layer, facilitating immediate decision-making and secure data transmission. Experimental evaluations highlight that EC-HMS achieves a 50 ms average latency, consumes 40% less energy compared to cloud-based systems, and ensures robust privacy through localized data handling. This research contributes to the advancement of scalable, responsive, and secure healthcare monitoring frameworks suitable for remote and resource-constrained environments. Future enhancements aim to incorporate predictive analytics and synchronization mechanisms to improve performance and adaptability further. © 2025 ieee.

关键词： Electronic health record

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Advancements in AI-Powered Robotic Cleaning systems: Autonomous Path Planning, Predictive Maintenance, and Cleanliness Assessment Frameworks 3

Advancements in AI-Powered Robotic Cleaning Systems: Autonom...

引用

3rd international conference on intelligent data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Jones Sarah, A. Nandhakumar, D. Kumar, Atchitha Magesh Pavithra, S. Department of Computer Science and Engineering Chennai Institute of Technology Tamilnadu Chennai600069 India

ISBN: (纸本)9798331527549

Artificial Intelligence (AI) is transforming robotic cleaning systems to be more efficient, safe, and adapt in various environments, including public spaces and industrial facilities. The novelty of these systems is the use of advanced sensing and deep learning to identify areas that need cleaning, plan paths, and save resources all while meeting high cleanliness standards required in sensitive areas like hospitals and pharmaceutical facilities. The objective is how recent developments in path planning, dirt detection, and predictive maintenance improve these systems, which reduce costs and perform without human supervision. Though these systems work well, challenges remain in deciding on cleaning paths for complex spaces, correctly detecting various types of dirt, adapting to changing environments, and maintaining to prevent breakdowns. © 2025 ieee.

关键词： Predictive maintenance

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Enhancing data Security and Privacy in Cloud computing: A Survey of Modern Techniques 3

Enhancing Data Security and Privacy in Cloud Computing: A Su...

引用

3rd international conference on intelligent data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Suganya, N. Gouthami, P. Sathiya, R. Sivaranjani, S. Murugesan, M. Department of Computer Science and Business Systems Dr. N.G.P. Institute of Technology Coimbatore India Department of Information Technology Thangavelu Engineering College Chennai India Departement of Electrical and Electronics Engineering Sri Krishna College of Engineering and Technology Coimbatore India Departement of Electrical and Electronics Engineering Karpagam Institute of Technology Coimbatore India

ISBN: (纸本)9798331527549

A computing system that is based on the internet and offers users all resources as on-demand services. Servers, storage, databases, software, and networking are among these on-demand services. Usually, the user must pay for the use of the resources;they are not their property. The number of people using this technology is increasing dramatically as a result of these features. Although it has benefits, cloud computing poses certain security and privacy risks. The authorized user’s data can be stolen easily. This current research thoroughly investigates modern strategies to these problems, highlighting identity management protocols, effective encryption and blockchain-based solutions. The article identifies research gaps, focuses attention to the inadequacies of current approaches, and recommends the possible ways to improve the efficiency, scalability and trustworthiness. © 2025 ieee.

关键词： Cloud security

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intelligent Control Mechanisms for Renewable Energy Integration Using Machine Learning Models

Intelligent Control Mechanisms for Renewable Energy Integrat...

引用

2025 international conference on Pervasive Computational Technologies, ICPCT 2025

作者： Chahar, Suman Kaur, Kawaljit Kaswan, Kuldeep Singh Malik, Kiran University Institute of Computing Chandigarh University Mohali India Galgotias University Department of Computer Science and Engineering Greater Noida India Gl Bajaj Institute of Technology and Management Department of Computer Science and Engineering-AIML Greater Noida India

ISBN: (纸本)9798331508685

The deployment of renewable energy sources (RES) in power systems used to be a major challenge owing to their intermittent and uncertain nature. Therefore, in this paper, the use of ML models as an intelligent control system to improve the operation of RES is studied. We survey different types of ML approaches, covering supervised learning for energy predic- tion, unsupervised learning for clustering demand, reinforcement learning for energy storage management, and deep learning for real time data processing. The intent of these advanced control strategies are to balance and stabilize the grid, harmonize demand response, and augment energy storage. We highlight the use-cases and impacts of ML from real-world cases across various geographies, showing operational gains and peak-demand savings. While these technologies hold great promise, they also face challenges like data privacy, interpretability of models, and availability of high-quality datasets. Moving forward, there is a need to improve transparency of algorithms and to strengthen the collaboration of different stakeholders. Our work paves the way for a systematic and automated approach to renewable energy integration, which can serve as a critical factor to build a reliable and efficient future modern power systems with machine learning. © 2025 ieee.

关键词： Adversarial machine learning

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An intelligent SCADA System for Power Distribution Network Cable Fault Detection with Real-Time Monitoring and Autonomous Maintenance 4

An Intelligent SCADA System for Power Distribution Network C...

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4th international conference on Robotics, Electrical and Signal Processing Techniques, ICREST 2025

作者： Nahidul Islam, S.M. Ahmad, Shameem Prodhan, Md. Mahbub-E-Elahi Khan Chowdhury, Md. Shoaib Bin Mizan, Sakib Ahmed, Abir Jahan, Effat Hazari, Md. Rifat Hossain, Chowdhury Akram American International University-Bangladesh Faculty of Engineering Department of Electrical and Electronic Engineering Dhaka1229 Bangladesh American International University-Bangladesh Faculty of Engineering Department of Computer Engineering Dhaka1229 Bangladesh

ISBN: (纸本)9798331530938

Supervisory Control and data acquisition (SCADA) systems are significant for boosting industrial operations, but established systems often struggle with fault management and real-time monitoring. To address these issues, this paper proposes an advanced SCADA system that integrates IoT technologies, multi-agent systems, and predictive maintenance for seamless data collection, analysis, and decision-making. Machine learning enhances fault detection and cybersecurity, while a modular hardware design allows scalability and flexibility to various industrial environments. The system is highly sensitive to detecting faults, including open circuit faults, line-to-ground faults, line-to-line faults, double line to ground faults and three-phase faults. It improves operational safety and efficiency by accurately locating faults and notifying professionals in real time. Extensive simulations and hardware tests were conducted to validate its performance in different fault scenarios. The results show that the proposed SCADA system has successfully detected different types of faults, offering a unified approach for fault management, maintenance, and real-time monitoring. © 2025 ieee.

关键词： SCADA systems

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