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10th IEEE International Conference on Cyber Security and Cloud Computing and 9th IEEE International Conference on Edge Computing and Scalable Cloud, CSCloud-EdgeCom 2023

作者： Xu, Chenying Yin, Yanfei Chen, Yingwen National University of Defense Technology College of Computer Changsha China China Aerospace Academy of Systems Science and Engineering China

ISBN: (纸本)9798350312461

With the development of cloud computing, data owners generally use cloud services to reduce storage and computing overhead. However, data stored in cloud servers is out of the direct control of the data owners, causing serious security issues. Access control mechanism based on cryptography can effectively protect the security of cloud data and prevent unauthorized access to it. Nevertheless, users may redistribute data to other users after obtaining it, which can harm the copyright interests of the data owner. To address this issue, this paper proposes a secret and traceable approach for cloud data sharing. We combine the lattice-based proxy re-encryption with digital watermarking technology for redistribution tracking in cloud data sharing scenario. The lattice cipher used in this scheme is an encryption algorithm with homomorphic property based on the Ring-LWE problem. It has the advantage of reducing the ciphertext length and improving the efficiency of encryption. This paper demonstrates the feasibility and effectiveness of this scheme from a series of experiments. The encryption of an image of size 1024∗1024 pixels takes only 9.78 seconds on average. The computational performance of this scheme is roughly 91.434% better than the existing data sharing schemes supporting redistribution tracking. © 2023 IEEE.

关键词： Cryptography

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Parallel Implementation of DNA Cryptography Encryption Scheme using MPI and CUDA 1

Parallel Implementation of DNA Cryptography Encryption Schem...

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1st IEEE International Conference on Advances in Electronics, Communication, Computing and Intelligent Information Systems, ICAECIS 2023

作者： Kamath, Navaneeth N Manjunath, K.N. Roopalakshmi, R. Rana, Akhil Nayak, Ashalatha Neelima, B. Manipal Institute of Technology Manipal Academy of Higher Education Department of Computer Science and Engineering Karnataka Manipal576104 India

ISBN: (纸本)9798350348057

There is a great requirement for cryptographic systems to secure shared or transmitted data over the internet. Periodic modification of the currently used cryptographic scheme to encrypt the data is also suggested to keep data transmission more secure. Along with the complexity of cracking the cryptosystem, it is expected that the overall encryption or decryption process should be less time-consuming to use in real time for data transmission over the internet. In this paper, we propose a DNA (Deoxy-Ribose-Nucleic-Acid) Cryptography and Substitution method-based encryption scheme to secure the text data which takes O(n) time to complete the encryption process of text data containing n characters and it is implemented using MPI (Message Passing Interface) and CUDA (Compute Unified Device Architecture) programming. The computation time of the sequential C program, MPI program, and CUDA program were analyzed on different data. © 2023 IEEE.

关键词： Cryptography

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Dynamic Changing Trustability Based Secured Protocol For Collaborative Data Transmission In Mobile Adhoc Network 3

Dynamic Changing Trustability Based Secured Protocol For Col...

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3rd IEEE Asian Conference on Innovation in technology, ASIANCON 2023

作者： Mariappan, Umasree Balakrishnan, D. Devi, G. Durga Alagusundar, Nanditha Aravindan, T.M. Nalatharaj, R.Jebi Sri Vidya College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Virudhunagar626001 India Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamil Nadu Krishnankoil626126 India

ISBN: (纸本)9798350302288

Secured data transmission in mobile adhoc network is an more difficult where there will not be any decentralized environment to monitor the packet transmission progress. There are various methods has been introduced earlier for ensuring the secured data transmission. However those research methodologies tends to have more demerits such as reduced data delivery rate, increased delay and so on. These problems are focused and resolved in the proposed research methodology by introducing the method namely Dynamic Changing Trustability based Secured MANET Protocol (DCT-SMANET-P). In this method, trustable nodes in the network environment will be find out first, through which data transmission will be carried out. Once trust values are evaluated, direct route path between the network nodes will be estimated based on which most trustable nodes will be chooses and the network carrier changes will be calculated. After trust estimation, routing will be carried out by choosing the most suitable route path through which data transmission will be carried out. The overall simulation of the research work is carried out in the NS3 simulation environment from which it is proved that the proposed methodology attains better outcome than the existing methodologies. © 2023 IEEE.

关键词： Data communication systems

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RSM-NLP at BLP-2023 Task 2: Bangla Sentiment Analysis using Weighted and Majority Voted Fine-Tuned Transformers 1

RSM-NLP at BLP-2023 Task 2: Bangla Sentiment Analysis using ...

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1st Workshop on Bangla Language Processing, BLP 2023

作者： Seth, Pratinav Goel, Rashi Mathur, Komal Vemulapalli, Swetha Dept. of Data Science & Computer Applications Manipal Institute of Technology Manipal Academy of Higher Education Manipal India Dept. of Computer Science & Engineering Dept. of Information and Communication Technology

ISBN: (纸本)9798891760585

This paper describes our approach to submissions made at Shared Task 2 at BLP Workshop - Sentiment Analysis of Bangla Social Media Posts(Hasan et al., 2023a;Islam et al., 2021;Hasan et al., 2023b). Sentiment Analysis is an action research area in the digital age. With the rapid and constant growth of online social media sites and services and the increasing amount of textual data, the application of automatic Sentiment Analysis is on the rise. However, most of the research in this domain is based on the English language. Despite being the world’s sixth most widely spoken language, little work has been done in Bangla. This task aims to promote work on Bangla Sentiment Analysis while identifying the polarity of social media content by determining whether the sentiment expressed in the text is Positive, Negative, or Neutral. Our approach consists of experimenting and finetuning various multilingual and pre-trained BERT-based models on our downstream tasks and using a Majority Voting and Weighted ensemble model that outperforms individual baseline model scores. Our system scored 0.711 for the multiclass classification task and scored 10th place among the participants on the leaderboard for the shared task. Our code is available at https://***/ptnv-s/RSM-NLP-BLP-Task2. © 2023 Association for Computational Linguistics.

关键词： Sentiment analysis

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Multi-View Incongruity Learning for Multimodal Sarcasm Detection 31

Multi-View Incongruity Learning for Multimodal Sarcasm Detec...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Guo, Diandian Cao, Cong Yuan, Fangfang Liu, Yanbing Zeng, Guangjie Yu, Xiaoyan Peng, Hao Yu, Philip S. Institute of Information Engineering Chinese Academy of Sciences China School of Cyber Security University of Chinese Academy of Sciences China State Key Laboratory of Software Development Environment Beihang University China School of Computer Science and Technology Beijing Institute of Technology China Department of Computer Science University of Illinois Chicago United States

ISBN: (纸本)9798891761964

Multimodal sarcasm detection (MSD) is essential for various downstream tasks. Existing MSD methods tend to rely on spurious correlations. These methods often mistakenly prioritize non-essential features yet still make correct predictions, demonstrating poor generalizability beyond training environments. Regarding this phenomenon, this paper undertakes several initiatives. Firstly, we identify two primary causes that lead to the reliance of spurious correlations. Secondly, we address these challenges by proposing a novel method that integrate Multimodal Incongruities via Contrastive Learning (MICL) for multimodal sarcasm detection. Specifically, we first leverage incongruity to drive multi-view learning from three views: token-patch, entity-object, and sentiment. Then, we introduce extensive data augmentation to mitigate the biased learning of the textual modality. Additionally, we construct a test set, SPMSD, which consists potential spurious correlations to evaluate the the model's generalizability. Experimental results demonstrate the superiority of MICL on benchmark datasets, along with the analyses showcasing MICL's advancement in mitigating the effect of spurious correlation. © 2025 Association for Computational Linguistics.

关键词： Contrastive Learning

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Incorporating Artificial Intelligence Powered Immersive Realities to Improve Learning using Virtual Reality (VR) and Augmented Reality (AR) technology 3

Incorporating Artificial Intelligence Powered Immersive Real...

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3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Balushi, Jasim Sharki Ghulam Al Jabri, Malak Ibrahim Ahmed Al Palarimath, Suresh Maran, Pyingkodi Thenmozhi, K. Balakumar, C. Univesity of Technology and Applied Sciences College of Computing and Information Sciences Information Technology Department Salalah Oman Kongu Engineering College Department of Computer Applications Erode India Department of Computer Science Bengaluru India Karpagam Academy of Higher Education Department of Computer Science Coimbatore India

ISBN: (纸本)9798350375190

This study analyzes the transformative potential of combining artificial intelligence (AI) with immersive technologies, specifically virtual reality (VR) and augmented reality (AR), to elevate educational outcomes significantly. The synergy of AI and immersive technologies presents a unique opportunity to enhance students' motivation, memory retention, and comprehension of complex subjects, creating a distinct and impactful learning experience. The research comprehensively explores the current understanding of the effectiveness of VR and AR in educational settings, placing special emphasis on their applications in diverse fields such as science, technology, engineering, And Mathematics (STEM), medicine, language acquisition, and the development of interpersonal skills. Beyond highlighting the immense potential, the study acknowledges and addresses the obstacles that include the costs associated with equipment, training, and content creation. It underscores the importance of collaborative efforts among technology suppliers, educators, and content producers to overcome these challenges effectively. By recognizing and navigating these hurdles, the study aims to provide practical insights for educational institutions and policymakers, advocating for the integration of AI-powered immersive technology to enhance the overall learning experience for students. The findings underscore the transformative impact of such technologies, emphasizing their role in shaping the future of education and preparing students for the dynamic challenges of the modern world. © 2024 IEEE.

关键词： Augmented reality

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An Empirical Study of On-Policy and Off-Policy Actor-Critic Algorithms in the Context of Exploration-Exploitation Dilemma 3

An Empirical Study of On-Policy and Off-Policy Actor-Critic ...

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3rd International Conference on Emerging Techniques in Computational Intelligence, ICETCI 2023

作者： Seshagiri, Supriya Prema, K.V. Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Dept. of Computer Science and Engineering Manipal India

ISBN: (纸本)9798350300604

The Exploration-Exploitation dilemma in Reinforcement Learning (RL) algorithms is about deciding whether to select a sub-optimal path to the outcome and acquire a more varied learning of the environment or to select the greedy path and seek to maximize rewards. It is a fundamental challenge in RL algorithms which influences their learning efficiency. The on-policy and off-policy design of RL algorithms has an influence on their ability to explore non-greedy actions thereby affecting their learning ability. The paper presents the results of experiments conducted to analyze the effect of on-policy and off-policy design and the use of entropy in exploration in actor-critic algorithms and investigate the root causes of effective learning in algorithms. An empirical comparison of Soft Actor Critic (SAC) which is off-policy and Proximal Policy Optimization (PPO), an on-policy algorithm, are performed through these experiments in several continuous OpenAI Gym environments and the effect of exploration strategies like entropy, off-policy target update, and Generalized Advantage Estimate (GAE) factor on the bias-variance balance of these algorithms are analyzed. © 2023 IEEE.

关键词： Reinforcement learning

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GPU Side-Channel Attack Classification for Targeted Secure Shader Mitigation

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SN computer science 2024年第8期5卷 1-23页

作者： Lungu, Nelson Patra, Sudhansu Shekhar Mishra, Manoj Ranjan Dash, Bibhuti Bhusan Sasmal, Gopal Charan Pattnayak, Parthasarathi Singh, Satyendr Gourisaria, Mahendra Kumar Department of Electrical and Electronics Engineering University of Zambia Lusaka Zambia School of Computer Applications Kalinga Institute of Industrial Technology (KIIT) Deemed to be University Bhubaneswar India MCA Department Trident Academy of Creative Technology Bhubaneswar India Computer Science and Engineering Department BML Munjal University Gurugram India School of Computer Engineering Kalinga Institute of Industrial Technology (KIIT) Deemed to be University Bhubaneswar India

Graphics processing units (GPUs) provide massively parallel processing capabilities, enabling accelerated computation across diverse applications. However, their parallel architecture and shared resources also introduce significant security vulnerabilities, especially side-channel attacks that can compromise sensitive data. This article presents a systematic classification of GPU side-channel attack vectors, including power analysis, timing analysis, electromagnetic analysis, and combined attacks. This taxonomy proposes countermeasures for the NVIDIA GeForce RTX 3090 GPU to mitigate these threats. The countermeasures encompass hardware techniques such as isolated execution environments, secure memory partitioning, and hardware random number generators to reduce the attack surface. Software methods, including constant-time algorithms, data-independent execution paths, masking, and oblivious memory access, are also implemented to eliminate timing and cache side channels. Comprehensive experiments demonstrate the effectiveness of the countermeasures, achieving up to 95% reduction in power analysis leakage, 90% in timing analysis, and 92% in electromagnetic analysis with acceptable performance overheads. The secure shader programming framework provides robust mitigation against GPU side-channel attacks while maintaining efficiency and compatibility with the RTX 3090 architecture. This work contributes vital insights and solutions for analysing GPU security vulnerabilities, designing focused countermeasures, and enabling confidential computing leveraging modern GPU capabilities. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Graphics processing units security Hardware countermeasures NVIDIA GeForce RTX 3090 Secure shader Side-channel attacks Software mitigation

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Enhanced Health Monitoring System for Internet of Medical Things using Machine Learning 15

Enhanced Health Monitoring System for Internet of Medical Th...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Swedheetha, C. Manikandan, P. Rajalakshmi, J. Muthuraja, T. Kavin Kumar, K. Chandrasekaran, Gokul Sriram Srivathsan, N. Velammal College of Engineering and Technology Department of Computer Science and Engineering India Kalasalingam Academy of Research and Education Krishnankoil Department of Electronics and Communication Engineering Virudhunagar India Sethu Institute of Technology Department of Electronics and Communication Engineering Virudhnagar India Kongu Engineering College Perundurai Department of Electronics and Communication Engineering Erode638060 India Karpagam Institute of Technology Department of Electronics and Communication Engineering Coimbatore India Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India

ISBN: (纸本)9798350370249

This brief looks at mobile operation, speech recognition, and voice robotization. Patients with physical limitations, such as Parkinson's disease and cerebral palsy, as well as those with speech impairments, can express their requirements with this application. The initiative enhances the general well-being and independence of people with impairments. Increasing the automation of current technologies is the main objective of this design. © 2024 IEEE.

关键词： Neurodegenerative diseases

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Exploring Social Media Trends - A Kannada Dataset Analysis

Exploring Social Media Trends - A Kannada Dataset Analysis

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2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Dey, Amritangshu Aishwaryasri, J. Jai Surya, R. Jayanthi, M.G. Kannadaguli, Prashanth Cambridge Institute of Technology Department of Computer Science Engineering Bengaluru India Dhaarini Academy of Technical Education Bengaluru India

ISBN: (纸本)9798350313413

Platforms for social media are dynamic tools that help ideas spread and develop quickly. This study introduces a novel way of locating popular Kannada-language subjects on social networking sites. This study also involves data preprocessing, feature extraction, and data visualization approaches to reveal underlying patterns and insights using a sizable dataset made up of Kannada text, tweets, hashtags, and news headlines. This method efficiently incorporates both sophisticated Machine Learning models, such as N-grams and word tokenization, and Deep Learning models, including sentence transformers and U-map embeddings. The examination of coherence and silhouette scores is used to validate the models. The main goal of this research is to offer an in-depth analysis of issues that regularly come up in Kannada debates on social media. This enables organizations, researchers, and content producers to make well-informed decisions, comprehend user opinion more thoroughly, and keep up with rapidly changing technological developments. In essence, this study helps provide a thorough understanding of the constantly changing digital ecosystem. © 2023 IEEE.

关键词： Bidirectional Encoder Representations from Transformers (BERT) Kannada language Latent Dirichlet Allocation (LDA) Natural Language Processing (NLP) social media Topic modelling Transformer trend

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