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SMASK: parallel Probabilistic Privacy-Preserving Frequent Pattern Mining Technique for Big Data 3rd

SMASK: Parallel Probabilistic Privacy-Preserving Frequent Pa...

引用

3rd international conference on Advanced Network Technologies and Intelligent Computing (ANTIC)

作者： Sharma, Shivani Thapar Inst Engn & Technol Dept Comp Sci & Engn Patiala India

ISBN: (纸本)9783031640759;9783031640766

This paper introduces a spark-based fast solution for privacy-preserving frequent pattern mining problems for big data. Spark Resilient distributed Dataset (rdD) framework has been used to implement the Mask approach, which uses the probabilistic distortion method for maintaining data privacy while mining frequent patterns. The masking technique shows very promising results in terms of privacy and utility both. However, due to sequential nature limits the application to small or medium size data. The spark-based proposed technique introduces two-level parallelization i.e. data and algorithmic level which in turn paves a way to gain faster analytical results in a bounded amount of time while dealing with a large volume of datasets. This makes the application feasible for the current growth of data size. A number of experiments have been conducted to compare the performance of the proposed scheme with benchmark parallel approaches in terms of privacy, utility, and time complexity over real and simulated data sets. It has been observed that the proposed scheme preserves the privacy of sensitive data while maintaining utility within a real bound of time. Experiments show that the proposed Spark-based scheme i.e. S-Mask gains 16 times speedup on average over different benchmark data sets and maintains a desired ratio between privacy and utility of the data.

关键词： Spark distributed Computing parallelization Constraint-based data mining Sensitive Pattern Hiding Privacy Preservation

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Power Quality Disturbance Classification Method Based on Multimodal parallel Feature Extraction Network 3

Power Quality Disturbance Classification Method Based on Mul...

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3rd international conference on Advanced Algorithms and Neural Networks, AANN 2023

作者： Tong, Zhanbei Zhong, Yangxingyu Huang, Gan Tian, Jiajun Chen, Wu Zhong, Jianwei College of intelligent systems science and engineering Hubei Minzu University Enshi China Jianshi County Power Supply Company State Grid Hubei Electric Power Company Jianshi China Enshi Power Supply Company State Grid Hubei Electric Power Company Enshi China

ISBN: (纸本)9781510668355

The problems of power quality disturbance (PQD) in modern power systems are complex and diverse, while the traditional model can only extract features of a single mode, which obtains insufficient information and affects the accurate identification of PQD. In order to obtain more comprehensive information and improve classification accuracy, this paper proposes a multimodal parallel feature extraction network for power quality disturbance classification. The model uses Gated Recurrent Unit (GRU) to extract temporal features. Meanwhile, the lightweight EfficientNet (LEfficientNet) module is designed to extract spatial features and fuse multimodal features. Then output to support vector machines (SVM) for classification. The classification results of 20 PQD simulated signals show that the proposed model achieves 99.89% correct classification rate, which is not only better than the performance of a single modal model, but also has lower training cost. © 2023 SPIE.

关键词： Feature extraction

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Intelligent Image Captioning with InceptionV3, LSTM, and PySpark Integration 3

Intelligent Image Captioning with InceptionV3, LSTM, and PyS...

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3rd international conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Kurian, Thanu Mathew, Jimsha K. Syam Dev, R.S. Anand, P.K. Vignesh, A. Rakshith, B.S. New Horizon College of Engineering Dept of Artificial Intelligence and Machine Learning Bengaluru India

ISBN: (纸本)9798331515911

Image captioning is a challenging task in artificial intelligence that involves generating descriptive captions for images automatically. In this project, we propose a novel approach leveraging advanced technologies such as PySpark, LSTM, and InceptionV3 to develop an effective image captioning system. We harness the power of PySpark, a distributed computing framework, to efficiently process large-scale image datasets and extract high-level features from images using the InceptionV3 convolutional neural network (CNN) model. These features capture the semantic information present in the images and serve as input to the caption generation model. The caption generation model utilizes LSTM neural network as the decoder component. LSTM is well-suited for sequential data processing and is capable of generating coherent and contextually relevant captions based on the extracted image features. The InceptionV3 model acts as the encoder, extracting meaningful visual features from input images, while the LSTM decoder generates captions by decoding these features into natural language descriptions. This multimodal approach enables the model to understand and describe the content of images accurately. Through experimentation and evaluation on diverse image datasets, our proposed system demonstrates promising results in generating accurate and human-like captions for a wide range of images. By integrating PySpark, LSTM, and InceptionV3, our image captioning system achieves state-of-the-art performance, highlighting the effectiveness of leveraging advanced technologies in solving complex AI tasks. © 2025 IEEE.

关键词： Convolutional neural networks

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Research and Design of EtherCAT Master Station for distributed Energy systems in Industrial Parks 3

Research and Design of EtherCAT Master Station for Distribut...

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3rd international conference on Green Communication, Network, and Internet of Things, CNIoT 2023

作者： Li, Dong Huang, Liansheng He, Shiying Chen, Quan Zhang, Xiuqig Chen, Xiaojiao Xiang, Zhicai Institutes of Physical Science and Information Technology Anhui University Institutes of plasma physics Chinese Academy of Sciences Hefei China Institutes of plasma physics Chinese Academy of Sciences University of Science and Technology of China Hefei China Institutes of plasma physics Chinese Academy of Sciences Hefei China Rizhao Power Supply Company State Grid Shandong Electric Power Company RiZhao China

ISBN: (纸本)9781510668867

Addressing the issues of poor real-time data transmission, high network latency, and long response times in traditional Ethernet communication systems used in distributed energy systems within industrial parks, this research focuses on designing a distributed real-time communication system master station based on the EtherCAT transmission protocol. The system is developed using the Qt cross-platform development framework. The distributed real-time communication system consists of a master station that provides management and control functions and slave stations that receive response signals. The master station and slave stations are connected via standard Ethernet cables, and communication data is captured and analyzed using Wireshark. Test results demonstrate that the system exhibits good real-time performance and fast response speeds, effectively addressing issues such as network congestion, data frame collisions, and packet loss commonly encountered when using traditional Ethernet in distributed energy systems. © 2023 SPIE.

关键词： Ethernet

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Leveraging Block chain for Secure and Decentralized Identity Management 3

Leveraging Block chain for Secure and Decentralized Identity...

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3rd IEEE international conference on Blockchain and distributed systems Security, ICBDS 2024

作者： Tabbassum, Ayisha Chintale, Pradeep Akiri, Charankumar Bhasin, Nishit SEI United States Tennessee Tech University United States

ISBN: (纸本)9798350354348

It is impossible to overestimate the significance of effective and safe identity management in the current digital environment. Strong identity management systems are now more important than ever due to the growth of online services and the growing digitalization of personal and corporate data. Identity theft, data breaches, and security lapses are commonplace with traditional centralized identity management techniques that depend on a single authoritative body for identity verification and authentication. Growing interest has been shown in using blockchain technology for identity management as a solution to these problems. Originally created as the foundational technology for cryptocurrencies like Bitcoin, blockchain provides a decentralized, impenetrable structure for organizing and preserving digital documents. Blockchain guarantees transparency, immutability, and integrity by spreading data over a network of nodes and securing transactions with cryptographic techniques. This makes it a perfect fit for identity management systems. The idea of using blockchain technology for safe, decentralized identity management is examined in this study. We seek to investigate the possible advantages, difficulties, and real-world uses of blockchain-based identity management systems by an extensive analysis of the current literature, case studies, and real-world implementations. This study aims to give useful information for enterprises, governments, and researchers interested in deploying safe and decentralized identity management systems in a quickly expanding digital environment by synthesizing ideas from diverse sources. © 2024 IEEE.

关键词： blockchain decentralized identity digital identity distributed ledger technology identity management self-sovereign identity

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Multi-vehicle collaborative perception driven by parallel intelligence under communication constraints 3

Multi-vehicle collaborative perception driven by parallel in...

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3rd IEEE international conference on Digital Twins and parallel Intelligence, DTPI 2023

作者： Chen, Bin Cai, Chao Xu, Yanan Li, Jinglin Shao, Congzhang Zhu, Xuanhan China United Network Communications Co. Ltd Beijing China Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9798350318470

Multi-vehicle collaborative perception can provide more comprehensive information for intelligent vehicles by sharing sensory data. This helps overcome issues like blind spots and occlusion, realizing safer driving decisions. However, real-world scenarios often have limited communication resources. Existing collaborative perception methods treat communication solely as the means for transmitting information, without considering the interplay between the spatial and temporal perception needs of vehicles and the available communication resources, which affects the collaborative effectiveness. In this paper, we propose a multi-vehicle collaborative perception method based on parallel intelligence, which maps channel conditions, vehicle spatio-temporal location and vehicle perception demand into virtual space. We utilized parallel intelligence to train the resource allocation decision model, which takes into account the deep coupling between the perception demand of vehicles and the communication resources. Then guides the vehicles to achieve distributed independent decision-making by using resource allocation decision model. To evaluate our method, we implemented it on the OpenCDA autonomous driving simulation platform. The experimental results show that the parallel-intelligence collaborative perception algorithm proposed in this paper can autonomously learn the timing and content of the collaboration through training. Compared to the traditional centralized allocation strategies, our method improves perceptual satisfaction by 12.1% and reduces communication loss by 1.8%, which effectively improves the collaborative perception effect. © 2023 IEEE.

关键词： Autonomous vehicles

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Unified Security Framework for Cloud Applications with IoT Fusion via Decentralized Blockchain 3

Unified Security Framework for Cloud Applications with IoT F...

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3rd international conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Mohanraj, B. Kalpana A, M. Priya, M. Abdul Jaleel, D. Karthikeyan A, N. Velusamy, A. Sona College of Technology Department of Information Technology Salem India Government College of Engineering Department of Computer Science Engineering Salem India Knowledge Institute of Technology Department of Information Technology Salem India Madanapalle Institute of Technology & Science Department of Computer Science & Technology Madanapalle India Sri Venkateshwara College of Engineering Department of Cse - Artificial Intelligence Vidyanagar India

ISBN: (纸本)9798350375190

Recent advancements in blockchain-based cloud computing highlight its potential in providing robust data security, integrity, and confidentiality. While cloud computing is increasingly utilized for remote resource access, it presents significant security challenges that necessitate innovative solutions. This research proposes a novel SecureCloudChain IoT (SCC-IoT) architecture, which integrates blockchain technology into cloud-supportive platforms to enhance security measures. The SCC-IoT architecture includes a distributed blockchain approach to ensure data security while maintaining privacy and integrity. This system is designed to be adaptable and scalable, meeting real-world requirements effectively. By promoting a decentralized and efficient environment, SCC-IoT improves the reliability, stability, and load balancing of cloud services. Performance assessments through various experimental conditions have been conducted to evaluate the proposed system. The results demonstrate SCC-IoT's effectiveness in mitigating potential attacks and ensuring secure and reliable cloud computing. This research highlights the significance of integrating blockchain technology into cloud platforms, paving way for more secure and efficient cloud computing solutions. © 2024 IEEE.

关键词： Blockchain

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Quantum Resistant Cryptographic systems for Blockchain Network 3

Quantum Resistant Cryptographic Systems for Blockchain Netwo...

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3rd IEEE international conference on Intelligent Technologies, CONIT 2023

作者： Dharani, D. Soorya, R. Kumari, K. Anitha PSG College of Technology Department of Information Technology Coimbatore India PSG College of Technlogy Department of Information Technology Coimbatore India

ISBN: (纸本)9798350338607

This paper presents a comprehensive examination of post-quantum cryptographic techniques, also known as quantum encryption, which offer protection against quantum attacks. It explores various methods such as hash-based cryptography and lattice-based cryptography that can safeguard cryptographic hashing and encryption against the potential vulnerabilities posed by quantum computers. The focus is specifically on the implications for blockchain technology, as it is susceptible to compromise during quantum attacks. The study provides an overview of quantum cryptographic encryption techniques that are poised to withstand quantum attacks, ensuring the resilience and quantum-proof nature of cryptographic measures. Blockchain is a peer to peer network that maintains distributed ledger. The peers in the network shares information in the network that is secured using typical cryptographic mechanisms. The proposed system aims at integrating quantum resistant cryptographic techniques in the blockchain network which ensures enhanced security to the information shared in the network. The proposed algorithm improves level of security to the typical blockchain network. © 2023 IEEE.

关键词： Blockchain

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A distributed on-demand routing algorithm for large-scale low earth orbit constellation 3

A distributed on-demand routing algorithm for large-scale lo...

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3rd international conference on Algorithms, Microchips, and Network Applications, AMNA 2024

作者： Hu, Hefei Lv, Siyan He, Jun Feng, Simen School of Information and Communication Engineering University of Posts and Telecommunications Beijing100876 China School of Electronic Engineering University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9781510680098

With the advancement of satellite communication technology and space launch technology, low earth orbit (LEO) satellites have become the best choice to overcome geographical limitations and achieve global communication. In order to achieve efficient performance in the large-scale LEO constellation network, a routing algorithm adapted to satellite network is necessary. A routing algorithm based on on-demand routing is proposed to address the issues of high network overhead and difficult routing in the large-scale LEO constellation. "Maximum routing restriction area" is defined based on the satellite network structure to reduce the routing overhead in the large-scale constellation network and improve network performance. The simulation results show that this algorithm has better network performance in the large-scale constellation network compared to the other on-demand routing algorithms. © 2024 SPIE.

关键词： Orbits

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distributed Strain Measurement Method of Bridge Based on Weak FBG Sensing Array 3

Distributed Strain Measurement Method of Bridge Based on Wea...

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3rd international conference on Internet of Things and Smart City, IoTSC 2023

作者： Nan, Qiuming Lu, Jiuling Rao, Zhisheng National Engineering Research Center for Optical Fiber Sensing Technology and Networks Wuhan University of Technology Wuhan430070 China School of Information Engineering Wuhan University of Technology Wuhan430070 China

ISBN: (纸本)9781510666375

Strain is an important parameter that reflects the safety state of bridge structure, at present, distributed strain measurement is one of the research hotspots in the field of structural health monitoring (SHM). The sensors such as strain gauge, vibrational chord strain gauge and fiber Bragg grating (FBG) strain gauge is difficult to network and realize distributed measurement. The optical fiber sensing technology based on Brillouin scattering can realize distributed strain measurement, but it’s always low in the signal-to-noise ratio (SNR) and measurement accuracy, so the application is limited. In this paper, a distributed strain measurement method for bridge based on weak FBG (WFBG) array is proposed and verified by experiments. The continuous beam test results show that, the good sensing performance is demonstrated by grating array strain cable which can accurately measure the strain distribution of continuous beam, and the load point can be located by the strain cable, and its positioning accuracy is 0.5m, and the sensitivity of the cable is about 1.25μΕ/pm. The test results of real bridge show that strain distribution of the whole bridge under dynamic and static load can be measured, and the maximum deviation of dynamic and static measurements is 6.8% and 5.6%. The temperature compensation method is proposed for the temperature influence in the test process, and the effect is good. In conclusion, the feasibility of the distributed strain measurement method of bridge based on weak FBG sensing has been verified. © 2023 SPIE.

关键词： Cables

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