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Power Grid Encrypted Data Range Filtering Scheme Based on Order-revealing Encryption 21

Power Grid Encrypted Data Range Filtering Scheme Based on Or...

引用

21st IEEE international Symposium on Parallel and distributed Processing with Applications, 13th IEEE international conference on Big Data and Cloud computing, 16th IEEE international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Qiao, Hongyi Peng, Cong Luo, Min Wu, Po He, Debiao Wuhan University School of Cyber Science & Engineering Wuhan China Electric Power Research Institute State Grid Henan Electric Power Company Zhengzhou China

ISBN: (纸本)9798350329223

As the power internet of things (IoT) system accelerates, the IoT end devices within the power grid show an explosive growth, and generate massive electricity consumption data. While the diverse encryption technologies currently employed in the existing power grid system offer a degree of data privacy protection, they also make it difficult to filter and screen the data of the original node in the link. In addition, the traditional cryptographic technology can not resist the attack of uploading invalid data from the malicious terminal in the case that the power terminal is controlled by a malicious adversary. To address this issue, this paper presents an efficient bilinear pairing-free order-revealing encryption scheme (r-ORE) based on the modified GQ protocol, and constructs a power grid encrypted data range filtering scheme to realize the comparison of ciphertext without disclosing plaintext information. the scheme allows the IoT terminals in the power grid, such as smart meters, to encrypt the electricity consumption data before sending it to the edge server, and to filter the range of encrypted data through the query range ciphertext generated by the data center. the experimental evaluation shows that our r-ORE surpasses Cash et al.'s scheme in terms of execution costs, and its extended scheme is practical in the power grid environment. © 2023 IEEE.

关键词： internet of things

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Fine-grained IoT device identification method based on self-supervised ViT 21

Fine-grained IoT device identification method based on self-...

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作者： Peng, Kai Lu, Tong Mei, Song Xue, Nannan Shen, Yongchao Hu, Menglan Huazhong University of Science and Technology School of Electronic Information and Communications Wuhan China Huazhong University of Science and Technology School of Cyber Science and Engineering Wuhan China

ISBN: (纸本)9798350329223

the proliferation of internet of things(IoT) technology has introduced challenges in device management and network security due to the heterogeneous nature of IoT devices and the inherent security risks they pose. Achieving timely 'visibility' of devices becomes crucial in addressing these challenges. While prevailing research primarily relies on extensive labeled training data, which encounter limitations stemming from the rapid device iteration and cumbersome IoT labeling *** overcome these constraints, we propose a novel IoT device identification method based on a self-supervised Vision in Transformer(ViT) framework. this method translates the abstract traffic behaviors into concrete representations. Leveraging the power of self-supervised learning, the proposed approach capitalizes on unlabeled data to enable autonomous self-training. By employing the ViT model, the method effectively extracts salient features from the images, enabling end-to-end, automated, and high-precision device *** results show that on real-world dataset, our method achieves 99.01% accuracy for the binary classification task of distinguishing IoT devices. Moreover, it achieves fine-grained identification accuracy for IoT devices of 98.44% with Macro-F1 improving to 98.91%. these results surpass the performance of other existing IoT device identification models, such as RF and CNN. © 2023 IEEE.

关键词： internet of things

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Partial Deep Domain Adaptation for Non-Intrusive Load Monitoring 21

Partial Deep Domain Adaptation for Non-Intrusive Load Monito...

引用

作者： Li, Yuying Yang, Yang Wang, Chen Liu, Runqin Jiang, Hongbo Liu, Wenping Hubei University Key Laboratory of Intelligent Sensing System and Security Ministry of Education School of Artificial Intelligence Wuhan China Huazhong University of Science and Technology Wuhan China China Unicom Central South Research Institute Changsha China Hunan University Changsha China Hubei University of Economics Wuhan China

ISBN: (纸本)9798350329223

With the widespread deployment of smart meters and the burgeoning integration of the Ubiquitous Power internet of things (UPIoT), Non-Intrusive Load Monitoring (NILM) has emerged as an essential technology, providing granular insights into device-level energy consumption. However, NILM model generalization is impeded by user and appliance heterogeneity. Domain adaptation has been leveraged to enhance NILM models, but it typically necessitates consistent appliance categorization across households. Addressing this, our study presents Weighted Adaptation NILM (WeAd-NILM), a partial deep domain adaptation model designed for Partial Domain Adaptation (PDA) scenarios that accommodate diverse appliance categories, aligning with real-world load decomposition tasks. WeAd-NILM introduces a sample weighting mechanism tailored for PDA, mitigating negative transfer from outliers. through distribution analysis and multi-objective regression, WeAd-NILM effectively performs load decomposition, fostering knowledge transfer. Verified on UK-DALE and REFIT datasets, WeAd-NILM demonstrates exceptional transferability and load decomposition accuracy. © 2023 IEEE.

关键词： internet of things

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Ranking on Heterogeneous Manifold for Multimodal Information Retrieval 21

Ranking on Heterogeneous Manifold for Multimodal Information...

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作者： Jin, Zhenkun Wan, Xingshi Nie, Xin Zhou, Xinlei Yi, Yuanyuan Zhou, Gefei Wuhan Business University Wuhan Research Institute of Posts and Telecommunications Wuhan China Wuhan Research Institute of Posts and Telecommunications Wuhan China Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security Wuhan China Huazhong University of Science and Technology School of Journalism and Information Communication Wuhan China Huazhong University of Science and Technology School of Computer Science & Technology Wuhan China

ISBN: (纸本)9798350329223

In light of recent advancements in internet of Multimedia things (IoMT) and 5G technology, both the variety and quantity of data have been rapidly increasing. Consequently, handling zero-shot cross-modal retrieval (ZSCMR) of unlabeled multi-modal data has emerged as a prominent research topic. Early models utilized generative adversarial networks and class embeddings to assist in building a common feature space. However, this approach resulted in a loss of reliability in the feature distributions of individual modalities. In this paper, we propose a method called Ranking on Heterogeneous Manifold (RHM) to address the aforementioned issue. Our model comprises three feature extractors, each dedicated to extracting features from text, images and multimodal data. Subsequently, the relationship structures derived from these feature extractors are employed to construct a heterogeneous manifold. A diffusion process is then conducted on this heterogeneous manifold, ultimately yielding the final ranking scores. Comprehensive experiments demonstrate that the proposed modal has the capability to acquire more effective knowledge representation, thus enhancing the effectiveness of ZSCMR. © 2023 IEEE.

关键词： Knowledge representation

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DRL Based on Priority Evaluation for Collaborative Perception Task Offloading in internet of Vehicles 16

DRL Based on Priority Evaluation for Collaborative Perceptio...

引用

16th international conference on Wireless Communications and Signal Processing, WCSP 2024

作者： Huang, Xiaoge Yu, Caiwei Li, Wenjing Liang, ChengChao Chen, Qianbin School of Communications and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China

ISBN: (纸本)9798350390643

With the explosive growth of the internet of Vehicles (IoVs), autonomous driving has received numerous attention from academia and industry. However, the limited perceivable range of a single connected and automated vehicle (CAV) leads to missing real-time road condition information, which affects driving safety. Meanwhile, due to the complexity of applications and dependencies between tasks, perception tasks require high computing capability and low latency. However, a CAV has limited local computing capability, it is necessary to offload perception tasks to edge for processing. therefore, to improve perception coverage and reduce perception task processing la-tency, we propose a Priority Evaluation and Deep Reinforcement Learning Task Offloading (PDRTO) algorithm. Firstly, a dual layer IoVs architecture for task offloading is constructed to improve the perception coverage of CAVs and achieve safe driving through collaborative perception among CAVs. At the same time, considering task dependency and CAV's mobility, a multi-CAV collaborative perception task graph is proposed to model the optimization problem of minimizing the processing delay of perception subtasks. then, the optimization problem is transformed into a multi-objective mixed integer optimization problem, and solved by the proposed PDRTO algorithm to minimize the processing delay of perception tasks. Finally, the simulation results show that the proposed algorithm outperforms other compared algorithms in improving CAV perception cover-age and reducing perception task latency. © 2024 IEEE.

关键词： Deep reinforcement learning

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Traceable Ring Signature Scheme in internet of Vehicles Based on Lattice Cryptography 21

Traceable Ring Signature Scheme in Internet of Vehicles Base...

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作者： Liao, Wei Han, Lansheng Chen, Peng Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan China

ISBN: (纸本)9798350329223

Lattice cryptography, as a recognized Cryptosystem that can resist quantum computation, has great potential for development. Lattice based signature scheme is currently a research focus. In this paper, the traceable ring signature scheme based on lattice cryptography in the internet of Vehicles (IoV) environment is studied. Firstly, users' public and private keys are generated on the lattice, which effectively reduces the key size and time cost. Secondly, the scheme also achieves traceability by adding additional information. the scheme satisfies strong unforgeability, traceability, and anonymity. In addition, the traceable ring signature scheme based on lattice cryptography is applied in the IoV environment to effectively protect user privacy. Model communication can not only protect user privacy, but also trace the signer when necessary, achieving a balance between security and privacy. the simulation results show that the average delay of IoV of our scheme is better than that of similar schemes. the research in this paper improves the security of data transmission in the IoV environment, enables it to adapt to the complex and changeable new network environment, and effectively guarantees the information security of vehicles and owners. © 2023 IEEE.

关键词： Cryptography

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Graph-based Multi-view Clustering for Web services 21

Graph-based Multi-view Clustering for Web services

引用

作者： Yang, Wang Zhenzhen, Yuan Guosheng, Kang Buqing, Cao Jianxun, Liu Yong, Xiao Hnust Xiangtan China Hunan University of Science and Technology Hunan Provincial Key Lab. for Services Computing and Novel Software Technology Xiangtan China School of Computer Science and Engineering China

ISBN: (纸本)9798350329223

the number of Web services on the internet has been steadily increasing in recent years due to their growing popularity. Under the big data environment, how to effectively manage Web services is of significance for service discovery, service recommendation, etc. It is widely studied that Web services clustering is an effective way for service management. However, most of the current Web service clustering only extracts the information of Web services for clustering from one view, such as Web service content descriptions, networks in which Web services participate, and so on. Extracting information from Web services only unilaterally will not be able to provide a three-dimensional and comprehensive description of Web services, which may diminish the effect of Web service clustering. In addition, some Web service resources will be wasted if other information of Web services is not used at the same time. We find that multi-view clustering can simultaneously consider multiple information of a data at the same time, and multiple information can complement and enhance each other according to the characteristics of multiview clustering. therefore, in this paper, we apply Web services to graph-based multi-view clustering in multi-view clustering to improve the performance of Web service clustering by simultaneously considering multiple feature information about Web services and distributing different weights to different information in the clustering process. © 2023 IEEE.

关键词： Web services

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A Decentralized Vehicle-to-Vehicle Energy Trading System Based on Efficient Sharding Services 21

A Decentralized Vehicle-to-Vehicle Energy Trading System Bas...

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作者： Meng, Kun Sun, Lijun Chen, Xiao Wu, Haiqin Li, Shuaiyong Qingdao University of Science and Technology College of Information Science and Technology Shandong China University of Leicester School of Computing and Mathematical Sciences Leicester United Kingdom Software Engineering Institute Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing China

ISBN: (纸本)9798350329223

Vehicle-to-vehicle (V2V) energy trading stands as a significant technology, allowing electric vehicles (EVs) to share energy. this balances energy demand and supply, reducing pressure on the power grid. However, two substantial challenges require attention: 1) Creating a standardized protocol universally adoptable by EV manufacturers and energy trading participants to establish a common secure and reliable platform for real-time energy trading between EVs. 2) Determining a fair and transparent pricing and transaction management mechanism, accounting for factors such as energy demand and supply, location, and user preferences. To tackle these hurdles, this paper proposes a decentralized V2V energy trading system (VETS) based on a novel high-performance sharding blockchain framework. VETS incorporates a standard energy trading management protocol, achieving trustless and transparent transaction processing. It employs a blockchain sharding and parallel architecture for high transaction throughput, catering to a large number of EVs. Furthermore, an efficient consensus algorithm is developed to minimize service delays and adapt to real-time transaction demands. A practical testbed operationalizes VETS, facilitating experimental analysis within a real-world cloud environment. © 2023 IEEE.

关键词： Blockchain

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A New Dataset for Intrusion Detection in Industrial Control System: A Gas Pipeline Testbed Study 21

A New Dataset for Intrusion Detection in Industrial Control ...

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作者： Deng, Longmin Zhang, Xuemin Zheng, Qianrong Zhao, Dongdong Zhou, Junwei Xiang, Jianwen Wuhan University of Technology Hubei Key Laboratory of Transportation of Internet of Things School of Computer Science and Artifical Intelligence Wuhan China Wuhan University of Technology Chongqing Research Institute Chongqing China

ISBN: (纸本)9798350329223

the security of Industrial Control Systems (ICS) is a critical issue that has gained increasing attention in recent years. Machine learning based intrusion detection systems (IDS) have shown promise in detecting previously unknown attacks, but their performance depends heavily on the quality of the dataset. However, most existing datasets in the field are either outdated or do not reflect the specific characteristics of ICS. We construct a dataset of ICS network traffic collected from a gas pipeline testbed, which covers a range of normal and abnormal events specific to the domain. We detail our methodology for constructing the dataset based on the gas pipeline testbed. Moreover, the systematic and fundamental comparative experiments are performed, based on the collected dataset. Specifically, we evaluate the performance of five supervised machine learning models on it while comparing their results. Our experimental results show that the dataset can serve as a valuable resource for data-driven IDS research and that Random Forest is an effective model for detecting anomalies in ICS data. © 2023 IEEE.

关键词： Intrusion detection

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the Pivot: Identifying Emergent Tactics in distributed Epistemic Games 16

The Pivot: Identifying Emergent Tactics in Distributed Epist...

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16th international conference on Computer-Supported Collaborative Learning, CSCL 2023

作者： Matthews, Jenna Swanson, Hillary Utah State University United States

ISBN: (纸本)9781737330684

the theoretical machinery of epistemic forms and games has been used to describe the knowledge-building processes of individuals. Humanity is faced with challenging problems in an increasingly complex world, and it is clear that productive knowledge building across domains depends on collaboration. To better characterize this collaborative knowledge building, we present a framework we call distributed epistemic games, in which the knowledge-building activities are carried out by a group distributed across time, space, and expertise. these distributed games are supported by tools such as computing technology and the internet, which allow individuals to connect, communicate, and coordinate their work. We introduce the construct of a tactic: a collection of moves found in distributed epistemic games, which together serve a larger purpose. Finally, we describe a specific emergent tactic, which we call the pivot. © 2023 international Society of the Learning Sciences (ISLS). All rights reserved.

关键词： Computer aided instruction

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