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Power data Federated Learning Privacy Policy Based on Optimized Homomorphic Encryption 6

Power Data Federated Learning Privacy Policy Based on Optimi...

引用

6th ieee international conference on Power, intelligent computing and systems, ICPICS 2024

作者： Zhang, Yiying Lu, Wenjie Yu, Qianao Zhang, Suxiang Li, Wenjing Liang, Kun School of Artificial Intelligence Tianjin University of Science and Technology Tianjin China State Grid Beijing Electric Power Company Information and Communication Department Beijing China State Grid Information & Telecommunication Co. Ltd. Information and Communication Department Beijing China State Grid Information & Communication Industry Group Co. Ltd. Information and Communication Department Beijing China

ISBN: (纸本)9798350374315

With the advent of big data in electricity power, concerns about privacy and security have led most power stations to avoid sharing their electricity data, resulting in 'data islands.' Federated learning emerged to address this, but it still poses privacy risks during training. Balancing privacy protection and data utilization is a current challenge. Federated learning involves exchanging intermediate results, and sending plaintext results can risk privacy breaches. Encryption during training increases computational and communication overhead, affecting efficiency, and is challenging in resource-limited environments. To address these issues, a federated learning model combining differential privacy with optimized Paillier homomorphic encryption has been proposed, ensuring data protection and improving training accuracy. © 2024 ieee.

关键词： Federated learning

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EXPRESS 2.0: An intelligent Service Management Framework for AIoT systems in the Edge 38

EXPRESS 2.0: An Intelligent Service Management Framework for...

引用

38th ieee/ACM international conference on Automated Software Engineering (ASE)

作者： Xu, Jia Liu, Xiao Pan, Wuzhen Li, Xuejun Yao, Aiting Yang, Yun Anhui Univ Sch Comp Sci & Technol Hefei Peoples R China Deakin Univ Sch Informat Technol Geelong Vic Australia Swinburne Univ Technol Dept Comp Technol Melbourne Vic Australia

ISBN: (纸本)9798350329964

AIoT (Artificial Intelligence of Things) which integrates AI and IoT has received rapidly growing interest from the software engineering community in recent years. It is crucial to design scalable, efficient, and reliable software solutions for large-scale AIoT systems in edge computing environments. However, the lack of effective service management including the support for service collaboration, AI application, and data security in the edge, has seriously limited the development of AIoT systems. To seal this gap, we propose EXPRESS 2.0 which is an intelligent service management framework for AIoT in the edge. Specifically, on top of the existing EXPRESS platform, EXPRESS 2.0 includes the intelligent service collaboration management module, AI application management module, and data security management module. To demonstrate the effectiveness of the framework, we design and implement a last-mile delivery system using both UAVs (Unmanned Aerial Vehicles) and UGVs (Unmanned Ground Vehicles). The EXPRESS 2.0 is open-sourced at https://***/ISEC-AHU/EXPRESS2.0. A video demonstration of EXPRESS 2.0 is at https://***/GHKD_VvJD88.

关键词： AIoT System Edge computing Service Collaboration AI Application data Security

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Envisioning the interactive convergence of Generative AI and Facial Expression Recognition 9

Envisioning the interactive convergence of Generative AI and...

引用

9th ieee international conference for Convergence in Technology, I2CT 2024

作者： Florance, G. Nirmala, M. Khan, Jumainah Saifudeen Hisham, K.M. New Horizon College of Engineering Computer Science And Engineering Bengaluru India

ISBN: (纸本)9798350394474

This paper explores and envisions a collaboration between Facial Expression Recognition (FER) and Generative Artificial Intelligence (GenAI) to create an advanced human-computer interaction (HCI) experience. Deep learning techniques are harnessed to interpret human emotions from facial expressions, using a structured approach that includes pre-processing, feature extraction, and classification. The data acquired from the FER stage informs GenAI systems - such as Generative Pre-trained Transformers (GPTs) - to produce contextually relevant and emotionally resonant responses. The proposed system leverages a sophisticated camera setup to capture facial data with high accuracy under diverse lighting conditions, ensuring robust and reliable emotion inference. Virtual avatars complete the multimodal experience by generating corresponding nonverbal cues. Special attention is given to creating a dynamic feedback loop for continuous learning and adaptation, leading to increasingly effective human-computer dialogues. Ethical implications, such as user privacy, data security, and bias mitigation, are central to the design and deployment of this system, underscoring the commitment to ethical standards and user empowerment. This paper aims to demonstrate how the convergence of FER and GenAI can revolutionize HCI, paving the way for enhanced empathetic and intelligent computing interfaces. © 2024 ieee.

关键词： intelligent systems

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Next-Generation Intrusion Detection systems with Machine Learning and Deep Learning-Based Firewalls 3

Next-Generation Intrusion Detection Systems with Machine Lea...

引用

3rd international conference on intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Rani, Ritu Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798331515911

The growing complexity of cyber-attacks has underlined the requirement of strong Intrusion Detection systems (IDS) able to instantly recognize a variety of hazards. This work offers a strategy for improving Next-Generation Intrusion Detection systems (NGIDs) combined with firewalls by use of machine learning (ML) and deep learning (DL) approaches. Using the NSL-KDD dataset - which includes both normal and attack network traffic - the work creates a system able to classify traffic patterns into "Normal"and "Attack"categories. The proposed method consists in four phases: data collecting, data preprocessing, feature selection and extraction, and classifier application. In the preprocessing stage, the dataset is cleaned and normalized;hence, suitable feature selection follows to increase classification accuracy. Trained and tested for classification using performance criteria including accuracy, precision, recall, and F1-score, naïve bayes and support vector machine (SVM) models are then compared in efficacy. The results reveal that the SVM classifier has low misclassification and great accuracy (97.29%), therefore proving its prospective use in advanced IDS. The article underlines how several models could be merged inside a firewall system to offer real-time network protection. Future studies will look at using deep learning techniques and ensemble methods to raise detection accuracy even more, therefore allowing NGIDS to be more adaptable and efficient in countering evolving cyber threats. © 2025 ieee.

关键词： Network intrusion

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Smart Elevator System with intelligent Floor Level Prioritization using Object Detection

Smart Elevator System with Intelligent Floor Level Prioritiz...

引用

2024 international conference on Advances in data Engineering and intelligent computing systems, ADICS 2024

作者： Suraparaju, Rohith Varma Anjemeti, Venkata Sai Revathy, S. Hindustan Institute Of Technology And Science Department Of Computer Science & Engineering Chennai India

ISBN: (纸本)9798350364828

The increasing need for effective vertical transit systems in present-day areas has led to the creation of clever elevator system solutions. In order to improve floor-level prioritizing, this study presents a Smart Elevator System (SES) that incorporates innovative object-detecting technologies. The proposed approach automatically alters elevator priority in realtime by using strong computer vision algorithms to identify and assess the number of passengers waiting on each floor. Computer vision algorithms identify and track passengers in realtime, allowing for the dynamic adjustment of elevator priorities based on the object detection count. Through the use of machine learning models, the system can detect user counts and make intelligent adjustments to reduce waiting times and energy usage. The integration of Internet of Things (IoT) devices, which improves system responsiveness overall, Our proposed work shows notable gains in waiting time and energy savings through intelligent floor-level prioritization. © 2024 ieee.

关键词： Object detection

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Design and Simulation of data acquisition system using Ethernet for Zynq 7000 SoC FPGA 16

Design and Simulation of Data Acquisition system using Ether...

引用

16th international conference on Electronics, Computers and Artificial Intelligence, ECAI 2024

作者： Angadi, Prajwal Satwika, S. Shreya, E. Jamuna, S. Dayananda College of Engineering Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350371154

data acquisition system using Ethernet for Zynq 7000 SoC FPGA, In autonomous vehicles, data transmission is essential for being reliable and for the efficient operation of the vehicle. In this project we are trying to implement the 10G Ethernet MAC for the data transmission. The advanced Driver Assistance System (ADAS) in autonomous vehicles now uses CAN networks, which are not very reliable in today's faster environment. The Ethernet is much faster than the CAN. Therefore, Ethernet is the protocol we're employing to achieve this fast data transmission. Analog data is transformed into digital data and stored in FIFO in this data acquisition system. Ethernet is used to transfer the data that is stored for analysis and visualization. The simulation is the primary emphasis of this project. This simulation's output is organized according to the ieee 802.3 Ethernet standard. This Ethernet output will be of use in ADAS system for increasing the rate of transmission and reliability. © 2024 ieee.

关键词： advanced driver assistance systems

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Research on Ship Remote Monitoring and intelligent Decision-making System Supported by 5G Communication 6

Research on Ship Remote Monitoring and Intelligent Decision-...

引用

6th ieee international conference on Civil Aviation Safety and Information Technology, ICCASIT 2024

作者： Qi, Shufei Sun, Wenyi Zong, Yonggang Binzhou Polytechnic Ocean Department Binzhou China

ISBN: (纸本)9798350389418

This paper proposes a remote monitoring and decision-making system for intelligent ships based on edge computing and distributed algorithms. Relying on the high bandwidth and low latency characteristics of 5 G communication, real-time data processing and remote monitoring of ship operation status are realized. The system localizes a large amount of sensor data through edge computing, and combines distributed algorithms to improve data fusion and decisionmaking efficiency. data transmission supported by 5G communication provides technical guarantee for seamless connection between ships and shore-based monitoring centers. Through real-time analysis of ship sensor data, the system can predict potential faults and optimize navigation strategies. Model simulation results show that the distributed algorithm based on edge computing has significant advantages in improving data processing speed, reducing decision response time by 15% and improving monitoring accuracy by 8.5%. This study provides technical support for remote monitoring and autonomous decision-making of intelligent ships, and verifies the broad application prospects of 5 G communication in the field of maritime communications. © 2024 ieee.

关键词： 5G mobile communication systems

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Cognitive data Underwriting

Cognitive Data Underwriting

引用

2024 ieee international conference on intelligent systems and advanced Applications, ICISAA 2024

作者： Patil, Sonali Chandrashekhar Das, Sudeep Patil, Vaishnavi Patil, Atharva Yadav, Shubham Dr. D.Y.Patil Institute of Technology Department of Information Technology Pimpri Pune India

ISBN: (纸本)9798331539948

The automation of underwriting processes in the insurance industry could significantly enhance operational efficiency by reducing the manual evaluation of risk factors. This paper presented a Natural Language Processing (NLP)based system designed to streamline the underwriting workflow. The system automated key steps such as converting PDF documents into text, pre-processing documents, and selectively extracting relevant data using custom corpora. A classification module was implemented to categorize extracted information into predefined risk classes, optimizing the evaluation process. Additionally, a summarization component condensed lengthy Attending Physician Statements (APS) into concise summaries, enabling quicker and more informed decision-making. The proposed system demonstrated its potential to simplify underwriting tasks, transforming complex documents into actionable insights for risk assessment. © 2024 ieee.

关键词： Risk assessment

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intelligent Accident Management System 3

Intelligent Accident Management System

引用

3rd international conference on Communication, Control, and intelligent systems, CCIS 2024

作者： Jayashree, Jayashree Chandana, R. Hiremath, Prerana B Kumar, Pavana Pawar, Suresh Computer Science and Engineering Nitte Meenakshi Intitute of Technology Bangalore India

ISBN: (纸本)9798331528201

With the growing population and the consequent surge in vehicular traffic, there is an urgent need for heightened safety measures. Addressing this challenge requires the integration of advanced systems equipped with highly sensitive sensors to proactively mitigate the risk of accidents. Ensuring vehicle reliability is paramount, leading to the incorporation of microcontrollers within each vehicle. These microcontrollers enable seamless data storage in cloud-based platforms and utilize SIM technology for uninterrupted communication and data transmission. Beyond data aggregation, these systems play a critical role in swiftly guiding individuals to emergency services in the event of an accident. Additionally, they provide crucial information and assistance to both drivers and passengers, both before and after an accident, thereby enhancing overall safety measures. This comprehensive approach not only prioritizes accident prevention but also ensures rapid and effective response mechanisms, thereby reducing potential risks and elevating overall road safety standards. © 2024 ieee.

关键词： Emergency services

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Research on multi-node gait information acquisition system and time synchronization based on BLE 6

Research on multi-node gait information acquisition system a...

引用

6th international conference on Robotics, intelligent Control and Artificial Intelligence, RICAI 2024

作者： Gao, Yuqi Yu, Chao Zhou, Xu Liu, Junjie Yao, Zhiming Lin, Ning Institute of intelligent Machines Hefei Institutes of Physical Science Chinese Academy of Sciences University of Science and Technology of China Hefei China Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China Department of Neurosurgery The Affliated Chuzhou Hospital of Anhui Medical University The First People's Hospital of Chuzhou Chuzhou China

ISBN: (纸本)9798331541699

Gait information is critical in various domains. However, achieving accurate time synchronization across multiple sensor nodes in wireless systems remains a challenge, particularly in gait information acquisition, where precise data alignment is essential. Current solutions are limited by high power consumption, system complexity, and transmission instability. This study proposes a multi-node gait information acquisition system incorporating a six-axis inertial sensor and a plantar pressure sensor, with the ESP32 serving as the core processing unit. The system utilizes the low-power Bluetooth protocol for real-time data transmission. To address the issue of time desynchronization, we introduce an average error-based time synchronization algorithm. The algorithm was tested in an experimental setup using a signal generator, two gait systems, and a mobile device. The results demonstrate that the average error method effectively estimates and corrects frequency drift, significantly reducing time synchronization errors. The system offers a low-power, high-precision solution for multi-node gait information acquisition, advancing the accuracy of gait data fusion and analysis. © 2024 ieee.

关键词： Sensor nodes

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