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41st International Conference on Machine Learning, ICML 2024

作者： Lei, Fenghao Yang, Long Wen, Shiting Huang, Zhixiong Zhang, Zhiwang Pang, Chaoyi College of Computer Science and Technology Zhejiang University Hangzhou China School of Artificial Intelligence Peking University Beijing China School of Computer and Data Engneering NingboTech University Ningbo China

Optimization and sampling based algorithms are two branches of methods in machine learning, while existing safe reinforcement learning (RL) algorithms are mainly based on optimization, it is still unclear whether sampling based methods can lead to desirable performance with safe policy. This paper formulates the Langevin policy for safe RL, and proposes Langevin Actor-Critic (LAC) to accelerate the process of policy inference. Concretely, instead of parametric policy, the proposed Langevin policy provides a stochastic process that directly infers actions, which is the numerical solver to the Langevin dynamic of actions on the continuous time. Furthermore, to make Langevin policy practical on RL tasks, the proposed LAC accumulates the transitions induced by Langevin policy and reproduces them with a generator. Finally, extensive empirical results show the effectiveness and superiority of LAC on the MuJoCo-based and Safety Gym tasks. Our implementation is available at https://***/Lfh404/LAC. Copyright 2024 by the author(s)

关键词： Adversarial machine learning

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SMAKAP: Secure Mutual Authentication and Key Agreement Protocol for RFID Systems 17

SMAKAP: Secure Mutual Authentication and Key Agreement Proto...

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17th International Conference on Security of Information and Networks, SIN 2024

作者： Naziri, Shayesta Wang, Xu Yu, Guangsheng Xu, Jian Shrestha, Sudhir Liang, Christy Jie School of Electrical and Data Engineering University of Technology SydneyNSW2007 Australia School of Computer Science University of Technology SydneyNSW2007 Australia

ISBN: (纸本)9798331509736

Radio Frequency Identification (RFID) is a crucial technology in the Internet of Things (IoT), enabling seamless wireless communication and data exchange. However, these technologies can pose significant security chal-lenges if not implemented with proper attention to security protocols-especially in communication, where pre-shared keys are not used between active tags and readers for device authentication. Some recent authentication protocols rely solely on a hash function, nonce, and single public kay agreement, which can lead to failure to implement robust security and proper authentication or ineffective for high security application environments. To effectively address these challenges this paper proposes a secure Elliptic Curve Cryptography (ECC) based lightweight mutual authentication protocol utilizing a hybrid key agreement protocol between active tag and reader for secure communication in RFID-enabled devices in the IoT environments. The informal analysis demonstrates a secure communication environment for data privacy and flexibility through effective key management. This protocol is adaptable to various applications by addressing specific requirements and limitations. © 2024 IEEE.

关键词： Authentication Protocol

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Metaverse:Perspectives from graphics,interactions and visualization

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Visual Informatics 2022年第1期6卷 56-67页

作者： Yuheng Zhao Jinjing Jiang Yi Chen Richen Liu Yalong Yang Xiangyang Xue Siming Chen School of Data Science Fudan UniversityChina Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business UniversityChina School of Computer and Electronic Information Nanjing Normal UniversityChina Department of Computer Science Virginia TechUSA

The metaverse is a visual world that blends the physical world and digital *** present,the development of the metaverse is still in the early stage,and there lacks a framework for the visual construction and exploration of the *** this paper,we propose a framework that summarizes how graphics,interaction,and visualization techniques support the visual construction of the metaverse and user-centric *** introduce three kinds of visual elements that compose the metaverse and the two graphical construction methods in a *** propose a taxonomy of interaction technologies based on interaction tasks,user actions,feedback and various sensory channels,and a taxonomy of visualization techniques that assist user *** potential applications and future opportunities are discussed in the context of visual construction and exploration of the *** hope this paper can provide a stepping stone for further research in the area of graphics,interaction and visualization in the metaverse.

关键词： Metaverse Virtual reality/Augmented reality computer graphics User interaction Immersive visualization

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Analysis of Bitcoin Prediction using Transparent and Opaque Machine Learning Algorithms 15

Analysis of Bitcoin Prediction using Transparent and Opaque ...

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Singh, Kavita R. Jamar, Anushri V. Khadgi, Pracheta P. Kapse, Smita Kumar, Ajay Department of Computer Technology Yeshwantrao Chavan College of Engineering Maharashtra Nagpur India School of Big Data and Computer Science Guizhou Province Guiyang City China

ISBN: (纸本)9798331300579

The unpredictable nature of cryptocurrency markets, particularly Bitcoin, has attracted significant attention from investors, researchers, and financial institutions seeking to understand and predict price movements. This study aims to analyse the effectiveness of both transparent and opaque machine learning algorithms in predicting Bitcoin prices. Transparent algorithms, such as linear regression and decision trees, provide clear insights into the factors influencing predictions. On the other hand, opaque algorithms, like ensemble methods, offer complex, non-linear models that may capture intricate patterns in the data. The main analysis is to lower the mean absolute error and enhance the r2 square, both key indicators of forecast accuracy. The study presents that linear regression and random forest outperformed others, achieving the smallest error and highest variance explanation, suggesting their effectiveness in Bitcoin price prediction with and without outliers respectively. In contrast, the support vector machine underperforms compared to all other machine learning algorithms under consideration. This paper sheds light on the most capable machine-learning techniques for Bitcoin forecasting, aiding trader investment choices and guiding academic study in the field of prediction. © Grenze Scientific Society, 2024.

关键词： Prediction models

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Evaluating Tourism Service Quality Using Large Language Models: A Sentiment Analysis Approach 9

Evaluating Tourism Service Quality Using Large Language Mode...

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9th IEEE International Conference on Progress in Informatics and Computing, PIC 2024

作者： Feng, Yate Zhao, Ying Pan, Junyang Wen, Yimin Guilin Tourism University School of Tourism Data Guilin China Guilin University of Electronic Technology School of Computer Science and Information Security Guilin China

ISBN: (纸本)9798350363203

With the continuous expansion of the tourism industry, understanding and enhancing tourism service quality has become increasingly critical. This study introduces an innovative method for evaluating tourism service quality using large language models (LLMs) and aspect-based sentiment analysis of travelogue data. By leveraging the advanced capabilities of LLMs, this method enables nuanced sentiment recognition at the aspect level, which significantly enhances the understanding of customer sentiments towards various tourism services. Analyzing over 1,000 travelogues sourced from an online platform, this research reveals the strengths of using LLMs in processing large volumes of unstructured data, resulting in a richer, data-driven understanding of customer experiences. The insights derived from this study provide valuable information for industry stakeholders, empowering them to tailor their services more effectively and ultimately enhance overall tourist satisfaction. © 2024 IEEE.

关键词： Leisure

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Lightweight Authenticated Key Agreement Protocol for Smart Power Grid Systems Using PUF

IEEE Open Journal of the Communications Society

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IEEE Open Journal of the Communications Society 2024年 5卷 3568-3580页

作者： Zahoor, Amina Mahmood, Khalid Saleem, Muhammad Asad Badar, Hafiz Muhammad Sanaullah Le, Tuan-Vinh Das, Ashok Kumar Department of Computer Science Sahiwal57000 Pakistan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Emerson University Multan Department of Emerging Computing Technologies Multan61000 Pakistan Fu Jen Catholic University Bachelor's Program of Artificial Intelligence and Information Security New Taipei City24206 Taiwan International Institute of Information Technology Hyderabad Center for Security Theory and Algorithmic Research Hyderabad500032 India

The Smart Power Grid (SPG) is pivotal in orchestrating and managing demand response in contemporary smart cities, leveraging the prowess of Information and Communication Technologies (ICTs). Within the immersive SPG environment, the ubiquitous deployment of smart meters stands as a testament to their paramount importance in the realm of vigilant monitoring and oversight. These smart meters are installed on high-tension electricity lines and transmit information about electricity outages and other issues to the utility center. To access services from utility centers, smart meters need to communicate securely over a public channel, even though the network itself is insecure. However, potential attacks from adversaries ( Ad) can exploit this communication. Therefore, protecting this communication is of utmost importance. Several privacy-preserving authentication protocols designed for SPG have been introduced in the literature. Nevertheless, a significant number of these protocols exhibit vulnerabilities to diverse security attacks. This article introduces a lightweight and anonymous authentication protocol specifically designed to address these concerns in the SPG environment. Our protocol ensures both security and efficiency, surpassing other comparable protocols in terms of its lightweight nature. By employing both formal and informal analysis, we showcase the robustness of our protocol against significant attacks while remaining lightweight. The proposed protocol provides added security features and incurs 23.8879% lower computation cost than related protocols. Consequently, our protocol is highly suitable for implementation in the SPG system. © 2020 IEEE.

关键词： Hash functions

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Partial Compilation of SAT Using Selective Backbones 26

Partial Compilation of SAT Using Selective Backbones

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26th European Conference on Artificial Intelligence, ECAI 2023

作者： Balogh, Andrea Escamocher, Guillaume O'Sullivan, Barry Insight Sfi Research Centre for Data Analytics School of Computer Science & It University College Cork Ireland Confirm Centre for Smart Manufacturing School of Computer Science & It University College Cork Ireland

ISBN: (纸本)9781643684369

Our goal in this paper is to significantly decrease the compiled size of a given Boolean instance with a large representation, while preserving as much information about the instance as possible. We achieve this by assigning values to a subset of the variables in such a way that the resulting instance has a much smaller representation than the original one, and its number of solutions is almost as high as the starting one. We call the set of variable instantiations that we make the selective backbone of the solutions that we keep. Large selective backbones allow for smaller representations, but also eliminate more solutions. We compare different methods of computing the selective backbone that offer the best compromise. © 2023 The Authors.

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Fortifying Smart Grids: A Holistic Assessment Strategy against Cyber Attacks and Physical Threats for Intelligent Electronic Devices

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computers, Materials & Continua 2024年第8期80卷 2579-2609页

作者： Yangrong Chen June Li Yu Xia Ruiwen Zhang Lingling Li Xiaoyu Li Lin Ge School of Computer Science Zhengzhou University of AeronauticsZhengzhou450046China Henan Xin’an Century Technology Co. Ltd.Henan Data Security Engineering Technology Research CenterZhengzhou450046China Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of EducationSchool of Cyber Science and EngineeringWuhan UniversityWuhan430072China

Intelligent electronic devices(IEDs)are interconnected via communication networks and play pivotal roles in transmitting grid-related operational data and executing control *** the context of the heightened security challenges within smart grids,IEDs pose significant risks due to inherent hardware and software vulner-abilities,as well as the openness and vulnerability of communication *** grid security,distinct from traditional internet security,mainly relies on monitoring network security events at the platform layer,lacking an effective assessment mechanism for ***,we incorporate considerations for both cyber-attacks and physical faults,presenting security assessment indicators and methods specifically tailored for ***,we outline the security monitoring technology for IEDs,considering the necessary data sources for their security ***,we classify IEDs and establish a comprehensive security monitoring index system,incorporating factors such as running states,network traffic,and abnormal *** index system contains 18 indicators in 3 ***,we elucidate quantitative methods for various indicators and propose a hybrid security assessment method known as GRCW-hybrid,combining grey relational analysis(GRA),analytic hierarchy process(AHP),and entropy weight method(EWM).According to the proposed assessment method,the security risk level of IEDs can be graded into 6 levels,namely 0,1,2,3,4,and *** higher the level,the greater the security ***,we assess and simulate 15 scenarios in 3 categories,which are based on monitoring indicators and real-world situations encountered by *** results show that calculated security risk level based on the proposed assessment method are consistent with actual ***,the reasonableness and effectiveness of the proposed index system and assessment method are validated.

关键词： Smart grid intelligent electronic device security assessment abnormal behaviors network traffic running states

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Collaborative Filtering of Malicious Information from the MULTimedia data Using s 1

Collaborative Filtering of Malicious Information from the MU...

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1st International Conference on computer science and Emerging Technologies, CSET 2023

作者： Parasuraman, Manikandan Abirami, G. Arockia Raj, A. Krishnan, Batri Munnangi, Ashok Kumar Kumaresan, M. School of Computer Science and Engineering Jain Deemed to Be University Bengaluru India Sathyabama Institute of Science and Technology Department of Computer Science Chennai India Madanapalle Institute of Technology and Science Department of Computer Science and Engineering - Data Science Madanapalle India Velagapudi Ramakrishna Siddhartha Engineering College Vijayawada India

ISBN: (纸本)9798350341737

Due to high proliferation of unsolicited information in the text, image and video files, the social media analytics engine suffers from losing its user, user privacy and others. The unsolicited information is been a huge threat to the service provides as it affects the reputations of the services provided and hence it is necessary to develop an intelligent model. Modern machine learning techniques are applied to identify and filter unsolicited information. However, some of the conventional methods are designed in an insecure way while processing all the text file, image and video files. © 2023 IEEE.

关键词： Collaborative filtering

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Deep Learning in Medical Imaging: Image Processing - From Augmenting Accuracy to Enhancing Efficiency 24

Deep Learning in Medical Imaging: Image Processing - From Au...

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7th International Conference on Digital Medicine and Image Processing, DMIP 2024

作者： Lakshmi Vara Prasad, G. Murali, A. Bhaskar Reddy, Y.V. Marturi, Haribabu Paul, Valeru Vision Centre for Data Science AI and ML QIS College of Engineering and Technology Andhra Pradesh Ongole India School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India

ISBN: (纸本)9798400709586

Deep learning has transformed medical imaging by significantly improving accuracy and efficiency in image processing tasks such as disease detection, segmentation, and classification. This paper explores the role of convolutional neural networks (CNNs), recurrent neural networks (RNNs), and other advanced architectures in enhancing image interpretation across various medical imaging modalities. By analyzing MRI, CT, and ultrasound data, this study demonstrates the efficacy of deep learning in automating critical diagnostic tasks, reducing human error, and improving patient outcomes. We propose a comprehensive framework for applying deep learning techniques in medical imaging, providing insights into future advancements in the field. Copyright © 2024 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Convolutional neural networks

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