检索结果-内蒙古大学图书馆

Provably Secure Efficient Key-Exchange Protocol for Intelligent Supply Line Surveillance in Smart Grids

IEEE Internet of Things Journal 2025年第12期12卷 21784-21792页

作者： Ayub, Muhammad Faizan Li, Xiong Mahmood, Khalid Alenazi, Mohammed J. F. Das, Ashok Kumar Wang, Guijuan University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh12311 Saudi Arabia International Institute of Information Technology Hyderabad Center for Security Theory and Algorithmic Research Hyderabad500032 India Korea University College of Informatics Department of Computer Science and Engineering Seoul02841 Korea Republic of Key Laboratory of Computing Power Network and Information Security Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Ministry of Education Shandong Computer Science Center Jinan250353 China

Intelligent supply line surveillance is critical for modern smart grids (SGs). Smart sensors and gateway nodes are strategically deployed along supply lines to achieve intelligent surveillance. They collect data continuously and transmit it to the control centre in real-time. It enables real-time monitoring, fault detection, and efficient energy management across distribution networks. This advanced surveillance system ensures continuous monitoring of supply lines, detecting anomalies, and optimizing operations to maintain the stability and reliability of the SG. However, the reliance of all participating nodes on public communication channels to transmit supply line surveillance data exposes these systems to critical cyber attacks. These cyber attacks include impersonation, physical tampering, ephemeral secret leakage (ESL), and desynchronization attacks. To address these issues, existing key-exchange protocols often fail to ensure robust security while imposing high computation and communication overheads, limiting their practicality for resource-constrained environments. Therefore, we propose a secure and efficient key exchange and tamper-resistant authentication protocol using elliptic curve cryptography (ECC) and physical unclonable functions (PUFs). The PUF mechanism provides robust resistance against physical tampering and cloning attacks, ensuring enhanced physical security for supply line devices. We validate the security robustness of the devised protocol using the random or real (ROR) model. Furthermore, informal security analysis demonstrates the protocol’s robustness in rigorously resisting various attacks, including physical tampering, impersonation, ESL and desynchronization. Moreover, we determine the performance evaluation that reveals the protocol’s superior efficiency compared to competing protocols, achieving significant reductions of 28.64% in computation overhead and 9.96% in communication overhead. © 2014 IEEE.

关键词： Authentication Protocol

来源：评论

学校读者我要写书评

暂无评论

Efficient Algorithms for Maximizing Group Influence in Social Networks

引用

Tsinghua science and Technology 2022年第5期27卷 832-842页

作者： Peihuang Huang Longkun Guo Yuting Zhong College of Mathematics and Data Science Minjiang UniversityFuzhou 350108China College of Mathematics and Computer Science Fuzhou UniversityFuzhou 350116China

In social network applications,individual opinion is often influenced by groups,and most decisions usually reflect the majority’s *** imposes the group influence maximization(GIM) problem that selects k initial nodes,where each node belongs to multiple groups for a given social network and each group has a weight,to maximize the weight of the eventually activated *** GIM problem is apparently NP-hard,given the NP-hardness of the influence maximization(IM) problem that does not consider *** on activating groups rather than individuals,this paper proposes the complementary maximum coverage(CMC) algorithm,which greedily and iteratively removes the node with the approximate least group influence until at most k nodes *** the evaluation of the current group influence against each node is only approximate,it nevertheless ensures the success of activating an approximate maximum number of ***,we also propose the improved reverse influence sampling(IRIS) algorithm through fine-tuning of the renowned reverse influence sampling algorithm for ***,we carry out experiments to evaluate CMC and IRIS,demonstrating that they both outperform the baseline algorithms respective of their average number of activated groups under the independent cascade(IC)model.

关键词： complementary maximum coverage(CMC) improved reverse influence sampling(IRIS) group influence maximization(GIM) independent cascade(IC)model

来源：评论

学校读者我要写书评

暂无评论

Optimal score estimation via empirical Bayes smoothing 37

Optimal score estimation via empirical Bayes smoothing

引用

37th Annual Conference on Learning Theory, COLT 2024

作者： Wibisono, Andre Wu, Yihong Yang, Kaylee Yingxi Department of Computer Science Yale University United States Department of Statistics and Data Science Yale University United States

We study the problem of estimating the score function of an unknown probability distribution ρ∗ from n independent and identically distributed observations in d dimensions. Assuming that ρ∗ is subgaussian and has a Lipschitz-continuous score function s∗, we establish the optimal rate of Θ˜(n-2/d+4) for this estimation problem under the loss function ŝ - s∗2L2(ρ∗) that is commonly used in the score matching literature, highlighting the curse of dimensionality where sample complexity for accurate score estimation grows exponentially with the dimension d. Leveraging key insights in empirical Bayes theory as well as a new convergence rate of smoothed empirical distribution in Hellinger distance, we show that a regularized score estimator based on a Gaussian kernel attains this rate, shown optimal by a matching minimax lower bound. We also discuss extensions to estimating β-Hölder continuous scores with β ≤ 1, as well as the implication of our theory on the sample complexity of score-based generative models. © 2024 A. Wibisono, Y. Wu & K.Y. Yang.

关键词： Probability distributions

来源：评论

学校读者我要写书评

暂无评论

Large Language Models for Financial Aid in Financial Time-series Forecasting

Large Language Models for Financial Aid in Financial Time-se...

引用

2024 IEEE International Conference on Big data, Bigdata 2024

作者： Islam, Md Khairul Karmacharya, Ayush Sue, Timothy Fox, Judy University of Virginia Computer Science Department United States University of Virginia School of Data Science Charlottesville United States

ISBN: (纸本)9798350362480

Considering the difficulty of financial time series forecasting in financial aid, much of the current research focuses on leveraging big data analytics in financial services. One modern approach is to utilize "predictive analysis", analogous to forecasting financial trends. However, many of these time series data in Financial Aid (FA) pose unique challenges due to limited historical datasets and high dimensional financial information, which hinder the development of effective predictive models that balance accuracy with efficient runtime and memory usage. Pre-trained foundation models are employed to address these challenging tasks. We use state-of-the-art time series models including pre-trained LLMs (GPT-2 as backbone), transformers, and linear models to demonstrate their ability to outperform traditional approaches, even with minimal ("few-shot") or no fine-tuning ("zero-shot"). Our benchmark study, which includes financial aid with seven other time series tasks, shows the potential of using LLMs for scarce financial datasets. © 2024 IEEE.

关键词： Decentralized finance

来源：评论

学校读者我要写书评

暂无评论

Leveraging user-item interactions and hotel characteristics for hotel recommendations in Indonesia with graph neural networks 9th

Leveraging user-item interactions and hotel characteristics ...

引用

9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Panarto, Francis Alexander Phanghegar, Tyrone Matthew Gunardi, Vincent Cenggoro, Tjeng Wawan Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia

Travelers usually check information about the destination before they decide to go. However, sometimes the information is too much to handle and causes confusion. A filtering mechanism is needed to help them make their choices. The solution is to implement a recommendation system;some common techniques that are used for this are Collaborative Filtering and content-based filtering, but both techniques have their flaws. Therefore, we propose a solution to combine those two methods through Graph Neural Network architectures to help fix their flaws. The proposed method will be used for recommending hotels in Indonesia using the HotelRec dataset as the base dataset and hotel features acquired from the TripAdvisor API. We use several GNN architectures, such as GCN, LightGCN, GraphSAGE, and GAT, to implement our approach. Then, we compare it to several baseline models, such as SVD and NeuMF, which are common baselines in recommendation systems. The performance of these models is calculated based on three metrics: HitRate@K, NDCG@K, and Recall@K. Based on the result of this experiment, we found that incorporating hotel features into the learning process of the model, accompanied by user-item interactions, boosted the model's performance by at least 20% in all metrics, especially in datasets with a smaller number of interactions. © 2024 The Authors.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Music Recommendation Model Based on Personalized Measurement and Game Theory

引用

Chinese Journal of Electronics 2023年第6期32卷 1319-1328页

作者： WU Yun LIN Jian MA Yanlong The State Key Laboratory of Public Big Data Guizhou University College of Computer Science and Technology Guizhou University

Music recommendation algorithms, from the perspective of real-time, can be classified into two categories: offline recommendation algorithms and online recommendation algorithms. To improve music recommendation accuracy, especially for the new music(users have no historic listening records on it), and real-time recommendation ability, and solve the interest drift problem simultaneously, we propose a hybrid music recommendation model based on personalized measurement and game theory. This model can be separated into two parts: an offline recommendation part(OFFLRP) and an online recommendation part(ONLRP). In the offline part, we emphasize users personalization. We introduce two metrics named user pursue-novelty degree(UPND) and music popularity(MP) to improve the traditional items-based collaborative filtering algorithm. In the online part, we try to solve the interest drift problem, which is a thorny problem in the offline part. We propose a novel online recommendation algorithm based on game theory. Experiments verify that the hybrid music recommendation model has higher new music recommendation accuracy, decent dynamical personalized recommendation ability, and real-time recommendation capability, and can substantially mitigate the problem of interest drift.

关键词： Measurement Collaborative filtering Heuristic algorithms Market research Real-time systems data models Classification algorithms

来源：评论

学校读者我要写书评

暂无评论

Fine-grained Text-Video Fusion for Referring Video Object Segmentation 4

Fine-grained Text-Video Fusion for Referring Video Object Se...

引用

4th IEEE International Conference on Power, Electronics and computer Applications, ICPECA 2024

作者： Li, Yonglin Wan, Jiaqi Teng, Xiao Lan, Long College of Computer Science and Technology National University of Defense Technology Department of Intelligent Data Science Changsha410073 China

ISBN: (纸本)9798350359589

Referring video object segmentation (RVOS) aims at segmenting an object in a video with its text description. The core of RVOS lies in the modal alignment between the vision and text. To improve the performance, most previous RVOS methods are devoted to exploring more sophisticated visual cues. However, these methods fail to fully exert the inherent structured properties of text and only use coarse text features to tackle vision-text interaction. In this paper, we propose FTVR, an approach that utilizes Fine-grain Text-Video method for Referring video object segmentation to explore fine-grain text information. We introduce a LLM to split the text sentence into different functional phrases and propose three novel modules to enhance the cross-modal alignment. Concretely, we design a dynamic-aware perception module to deal with motion-related phrases and a following global-aware attention module to fuse the outputted motion information. To deal with entity-related phrases, our FTVR also introduces an entity-aware augmentation module to highlight entity information. Extensive experiments show the effectiveness of our method on four popular benchmarks. © 2024 IEEE.

关键词： fine grained fusion large language model Referring video object segmentation

来源：评论

学校读者我要写书评

暂无评论

A survey on dynamic graph processing on GPUs: concepts, terminologies and systems

引用

Frontiers of computer science 2024年第4期18卷 1-23页

作者： Hongru GAO Xiaofei LIAO Zhiyuan SHAO Kexin LI Jiajie CHEN Hai JIN National Engineering Research Center for Big Data Technology and System/Services Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Zhejiang Lab Hangzhou 311121China

Graphs that are used to model real-world entities with vertices and relationships among entities with edges,have proven to be a powerful tool for describing real-world problems in *** most real-world scenarios,entities and their relationships are subject to constant *** that record such changes are called dynamic *** recent years,the widespread application scenarios of dynamic graphs have stimulated extensive research on dynamic graph processing systems that continuously ingest graph updates and produce up-to-date graph analytics *** the scale of dynamic graphs becomes larger,higher performance requirements are demanded to dynamic graph processing *** the massive parallel processing power and high memory bandwidth,GPUs become mainstream vehicles to accelerate dynamic graph processing ***-based dynamic graph processing systems mainly address two challenges:maintaining the graph data when updates occur(i.e.,graph updating)and producing analytics results in time(i.e.,graph computing).In this paper,we survey GPU-based dynamic graph processing systems and review their methods on addressing both graph updating and graph *** comprehensively discuss existing dynamic graph processing systems on GPUs,we first introduce the terminologies of dynamic graph processing and then develop a taxonomy to describe the methods employed for graph updating and graph *** addition,we discuss the challenges and future research directions of dynamic graph processing on GPUs.

关键词： dynamic graphs graph processing graph algorithms GPUs

来源：评论

学校读者我要写书评

暂无评论

MagicNaming: Consistent Identity Generation by Finding a "Name Space" in T2I Diffusion Models 39

MagicNaming: Consistent Identity Generation by Finding a "Na...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zhao, Jing Zheng, Heliang Wang, Chaoyue Lan, Long Huang, Wanrong Tang, Yuhua Department of Intelligent Data Science College of Computer Science National University of Defense Technology China HPCL College of Computer Science National University of Defense Technology China University of Science and Technology of China China University of Sydney Australia

ISBN: (纸本)157735897X

Large-scale text-to-image diffusion models, (e.g., DALL-E, SDXL) are capable of generating famous persons by simply referring to their names. Is it possible to make such models generate generic identities as simple as the famous ones, e.g., just use a name? In this paper, we explore the existence of a "Name Space", where any point in the space corresponds to a specific identity. Fortunately, we find some clues in the feature space spanned by text embedding of celebrities' names. Specifically, we first extract the embeddings of celebrities' names in the Laion5B dataset with the text encoder of diffusion models. Such embeddings are used as supervision to learn an encoder that can predict the name (actually an embedding) of a given face image. We experimentally find that such name embeddings work well in promising the generated image with good identity consistency. Note that like the names of celebrities, our predicted name embeddings are disentangled from the semantics of text inputs, making the original generation capability of text-to-image models well-preserved. Moreover, by simply plugging such name embeddings, all variants (e.g., from Civitai) derived from the same base model (i.e., SDXL) readily become identity-aware text-to-image models. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Optimization Algorithms for Feature Selection in Heart Disease Classification 2nd

Comparative Analysis of Optimization Algorithms for Feature ...

引用

2nd International Conference on Intelligent Computing Systems and Applications, ICICSA 2023

作者： Kapila, Ramdas Saleti, Sumalatha Telangana Maisammaguda Secunderabad India Data Science Laboratory Computer Science and Engineering SRM University-AP Amaravathi India

ISBN: (纸本)9789819754113

In order to classify the Cleveland Heart Disease dataset, this study evaluates the performance of three optimization methods, namely Fruit Fly Optimization (FFO), Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO). The top 10 features are identified using FFO, with remarkable results for accuracy (88.52%), precision (87.88%), recall (90.63%), and f1-score (89.23%). After using PSO, the accuracy, precision, recall, specificity, and f1-score are all 85.25%, 87.10%, 84.38%, and 85.71% respectively. Finally, GWO is used, which results in precision, accuracy, recall, and f1-score values of 93.33%, 90.16%, 90.11%, 87.5%, and 90.32% respectively, highlighting its consistent superior performance. FFO shows competitive outcomes with notable accuracy and recall through a comparative examination. PSO displays comparable precision and recall while displaying a somewhat poorer accuracy. In contrast, GWO performs better than both FFO and PSO, displaying great accuracy and precision along with remarkable recall and specificity. These results provide important information on the effectiveness of feature selection methods utilized in optimization algorithms for heart disease classification. The study also highlights the need for more investigation into the potential of these optimization algorithms in many fields, broadening their use beyond the classification of disease. This kind of work might improve the progress of the field of feature selection and aid in the creation of better classification models. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：