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IEEE International Conference on Cloud Networking (CLOUDNET)

作者： Andrew D’Angelo Chenglong Fu Xiaojiang Du Paul Ratazzi Department of Electrical and Computer Engineering Stevens Institute of Technology Hoboken NJ USA Department of Software and Information Systems University of North Carolina at Charlotte Charlotte NC USA Information Warfare Division Air Force Research Laboratory Rome NY USA

IoT-enabled smart homes can be double-edged swords. On one side, the convenience and efficiency brought about by smart device integrations can improve the standard of living dramatically. However, on the other side, the prevalent interconnectivity among home devices can drastically increase the potential risk of attack. Therefore, in order to reduce the possibility of a successful attack we propose a complex correlation-based anomaly detection system powered by intricate two-to-one correlations. Through the use of a state-of-the-art transformer model, we present a novel correlation mining mechanism that leverages the power of attention weights to develop an understanding of the underlying correlations that exist between IoT events in a smart home environment. Using this knowledge, we use a special validation algorithm to verify 52 two-to-one correlations in our system. Furthermore, we simulate four distinct attack scenarios and attain an average detection accuracy and recall of 96.59% and 97.38% respectively. Our results indicate that our method is effective at identifying a range of IoT attacks and successfully demonstrates the capabilities of IoT correlations.

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Multi-View Landmark-Assisted UAV Swarm 6-DoF Pose Estimation Using Resonant Beam and VIO

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IEEE Internet of Things Journal 2025年

作者： Du, Siyuan Xu, Mengyuan Li, Yixuan Fang, Wen Liu, Qingwen Yi, Peng Hong, Yiguang Tongji University School of Computer Science and Technology Shanghai201804 China Tongji University College of Electronic and Information Engineering Shanghai201804 China Chinese Academy of Sciences Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing100190 China

As an essential aerial platform in Internet of Things (IoT) applications, UAV swarms require high-precision attitude estimation in GPS-limited and dynamic environments, which supports higher-level IoT functions such as smart logistics, disaster response, and environmental monitoring. However, most odometry-based pose estimation methods in dynamic scenarios without GPS encounter issues with cumulative errors over time. In this paper, we propose a method to reduce these cumulative errors by constraining the absolute positioning of Visual-Inertial Odometry (VIO) using relative poses obtained from multi-view landmark and Resonant-Beam (RBeam) sensors between UAVs. For synchronous moments, we estimate the 6 Degree-of-Freedom (DoF) relative pose using the Angle of Arrival and Time of Flight data from the RBeam, combined with nonlinear optimization. For asynchronous moments, a two-stage visual estimation method is introduced, combining multi-camera epipolar geometry for rotation recovery and depth reconstruction optimization for translation recovery, enabling the estimation of asynchronous relative poses. Finally, we design a global objective function based on a sliding window and factor graph, integrating RBeam, multi-view landmark, and VIO for absolute 6-DoF pose optimization of the UAV swarm. Simulation results demonstrate that optimizing with the addition of RBeam synchronous relative poses improves overall positioning accuracy by 32.94% compared to pure VIO. Incorporating both RBeam synchronous and visual asynchronous relative poses further enhances overall positioning accuracy by 37.65%. Additionally, the UAV’s attitude benefits from the rotational constraints provided by the RBeam, achieving over 30% improvement in the pitch and yaw directions. © 2014 IEEE.

关键词： Global positioning system

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SvaVoting: A Novel Secret Sharing-Based Verifiable and Anonymous E-Voting Scheme in Blockchain systems

SvaVoting: A Novel Secret Sharing-Based Verifiable and Anony...

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International Conference on Parallel and Distributed systems (ICPADS)

作者： Jingyu Zhang Chenghao Wu Jin Yang Lailong Luo School of Computer and Communication Engineering Changsha University of Science and Technology Changsha China Science and Technology on Information Systems Engineering Laboratory School of Systems Engineering National University of Defense Technology Changsha China

E-Voting systems play a vital role in various communities, aiming to enhance the efficiency, transparency, and citizen engagement in elections. However, as technology advances, ensuring the security and reliability of e-voting systems becomes profound. While researchers have explored the integration of blockchain technology to improve e-voting systems, there still are technical challenges, particularly regarding voters’ privacy, ballots’ confidentiality, and system performance. To address these challenges, we propose SvaVoting, an innovative blockchain-based e-voting scheme. SvaVoting utilizes the Borda counting method and the identity-based ring signature based on symmetric primitives to anonymously verify the validity of the voter’s identity and ballot format. In addition, we introduce secret sharing and a Cloud Service Provider (CSP) to conduct the final counting while preserving the privacy of the ballots. All users in the system can verify the results of CSP calculations, thereby meeting security goals such as correctness, unforgeability, anonymity and verifiability. The identity-based ring signature in our scheme provides 128-bit security, and even it can work in a quantum computing environment. Experimental results demonstrate that our solution significantly enhances the security and performance of e-voting systems, offering a practical path forward for future e-voting systems.

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Digital Human Techniques for Education Reform 24

Digital Human Techniques for Education Reform

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7th International Conference on Educational Technology Management, ICETM 2024

作者： Guo, Peirong Zhang, Qi Tian, Chunwei Xue, Wanli Feng, Xiaocheng School of Software Northwestern Polytechnical University Shaanxi Xi’an China School of Economics and Management Harbin Institute of Technology at Weihai Shandong Weihai China Shenzhen Research Institute of Northwestern Polytechnical University Northwestern Polytechnical University Guangdong Shenzhen China School of Computer Science and Engineering Tianjin University of Technology Tianjin China Research Center for Social Computing and Information Retrieval Harbin Institute of Technology Heilongjiang Harbin China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen Key Laboratory of Media Security Shenzhen University Guangdong Shenzhen China

ISBN: (纸本)9798400717468

The rapid evolution of artificial intelligence, big data, and generative AI models has ushered in significant transformations across various sectors, including education. Digital Human Technique, an innovative technology grounded in advanced computer science and artificial intelligence, is reshaping educational paradigms by enabling virtual humans to simulate human behavior, express emotions, and interact with users. This paper explores the application of Digital Human Technique in education reform, focusing on creating immersive, intelligent classroom experiences that foster meaningful interactions between teachers and students. We define Digital Human Technique and delve into its key technical components such as character modeling and rendering, natural language processing, computer vision, and augmented reality technologies. Our methodology involves analyzing the role of educational digital humans created through these technologies, assessing their impact on educational processes, and examining various application scenarios in educational reform. Results indicate that Digital Human Technique significantly enhances the learning experience by enabling personalized teaching, increasing engagement, and fostering emotional connections. Educational digital humans serve as virtual teachers, interactive learning aids, and facilitators of emotional interaction, effectively addressing the challenges of traditional educational methods. They also promote a deeper understanding of complex concepts through simulated environments and interactive digital content. © 2024 Copyright held by the owner/author(s).

关键词： Digital elevation model

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A Space-Efficient Digital Wallet Service in Blockchain systems

A Space-Efficient Digital Wallet Service in Blockchain Syste...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Jingyu Zhang Jin Yang Chenghao Wu Lailong Luo School of Computer and Communication Engineering Changsha University of Science and Technology Changsha China Science and Technology on Information Systems Engineering Laboratory School of Systems Engineering National University of Defense Technology Changsha China

As an indispensable key network service in blockchain systems, digital wallet service is crucial for promoting the widespread application of blockchain technology and the development of the digital economy. However, with the increasing popularity of blockchain technology, the scale of the Unspent Transaction Output (UTXO) dataset continues to increase. A significant number of low-value UTXOs occupied the main dataset space, leading to blockchain dataset expansion. This has affected the performance of digital wallet service and the overall system performance. To address this issue, this paper proposes a Space-Efficient Digital Wallet (SEDW) service in blockchain systems. This strategy employs a Multidimensional Space Simulated Annealing (MSA) algorithm to obtain transaction input UTXOs. MSA can be combined with the UTXO dynamic adjustment mechanism, achieving the rapid consumption of low-value UTXOs without increasing the transaction fees. Experimental results demonstrate that the proposed SEDW strategy effectively optimized the selection of UTXOs in blockchain systems. It alleviated the expansion issue of the UTXO dataset, and controlled the generation of transaction fees, thereby achieving performance enhancement of digital wallet service.

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A High-Performance Data Verification Mechanism in Blockchain-Based IoT systems

A High-Performance Data Verification Mechanism in Blockchain...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Jingyu Zhang Pian Zhou Yongtao Sun Lailong Luo School of Computer and Communication Engineering Changsha University of Science and Technology Changsha China Science and Technology on Information Systems Engineering Laboratory School of Systems Engineering National University of Defense Technology Changsha China

With the rapid development of the distributed network and communication, the Internet of Things (IoT) systems have been applied to all walks of life. Blockchain technology is one of the most popular research fields recently, which can provide a reliable storage solution and solve information security issues for IoT systems. Transaction information is the most critical fundamental data in the blockchain systems, which needs to be verified to avoid being tempered with by malicious nodes in the process of transmission. With the exponential growth of the number of IoT devices, the limitations of the current storage structure put too much pressure on the system nodes. How to improve verification efficiency has become a key challenge. To alleviate this problem, this paper proposes a novel high-performance verification mechanism for data security protection in blockchain-based IoT systems. We design a new storage structure based on Huffman trunk tree (HTT), and conduct the quantitative analysis of transaction weights. Transactions are stored in full-featured devices in the form of Huffman Merkle tree (HMT), and only the content of HTT is saved in lightweight devices. Finally, the performance superiority of our mechanism is proved through theoretical analysis and experimental evaluation. In blockchain-based IoT systems, our mechanism significantly reduces the data transmission cost and computation overhead, effectively improving the efficiency of data verification.

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Transaction Data Management Optimization Based on Multi-Partitioning in Blockchain systems

Transaction Data Management Optimization Based on Multi-Part...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Jingyu Zhang Xingxing Hou Yilong Teng Lailong Luo School of Computer and Communication Engineering Changsha University of Science and Technology Changsha China Science and Technology on Information Systems Engineering Laboratory School of Systems Engineering National University of Defense Technology Changsha China

Unspent Transaction Output (UTXO) is part of the transaction data set, which represents the digital cryptocurrency asset in transaction-based blockchain systems. The data management capability, storage method and occupied space of UTXOs will greatly affect the running efficiency and the verification performance of blockchain systems. Especially, with the popularity of blockchain technology, the relevant UTXO data sets have been growing, and all the stored data can no longer be almost completely stored in memory. How should the UTXO transaction data be stored and managed at this time, it is an urgent issue to be solved in bitcoin-like blockchain systems. This paper provides a blockchain transaction data management optimization mechanism based on multi-partitioning. First, we analyze the influencing factors of transactions through real blockchain data. The proposed method can evaluate the time interval and transaction frequency factors, and use the received information to realize the efficient transaction data storage. In our design, UTXOs with lower likelihood to be used in new transactions will be stored in the disk, and the other UTXOs with higher likelihood to be used in new generated transactions should be stored in the cache. This approach aims to minimize memory consumption for the transaction data sets, accelerate UTXO access time during block verification, and ultimately decrease the overall time required for verification, leading to efficient UTXO transaction data management. Finally, the effectiveness of the proposed optimization mechanism is verified through theoretical analysis and simulation experiments, and the UXTO access time has been reduced compared with state-of-the-art methods.

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NBMon: NB-IoT-based UAV Network Routing Monitoring System 24

NBMon: NB-IoT-based UAV Network Routing Monitoring System

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24th IEEE International Conference on High Performance Computing and Communications, 8th IEEE International Conference on Data Science and systems, 20th IEEE International Conference on Smart City and 8th IEEE International Conference on Dependability in Sensor, Cloud and Big Data systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Tang, Ji'ao Zhu, Xiaojun Dong, Chao Zhang, Lei College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics China College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics China Nanjing University State Key Laboratory of Novel Software Technology Nanjing China

ISBN: (纸本)9798350319934

The routing state of UAV networks is difficult to monitor, making many new routing protocols hard to evaluate on UAVs. In this paper, we propose NBMon, an NB-IoT-based routing monitoring system for UAV networks, which can upload the routing table information from the host device to a control station through the NB-IoT network. At the same time, the control station can also send commands to the monitored devices to change routes. However, one challenge is that both NB-IoT modules and the control station are behind NAT without global IP addresses. We propose a NAT traversal method on top of NB- IoT. It allows communication between the NB-IoT modules and the control station in different networks. Finally, we implement NBMon and evaluate the performance of NB-IoT devices through real-world experiments. © 2022 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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A Smart Assistive Device for the Blind People 7th

A Smart Assistive Device for the Blind People

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7th International Conference on information and Communication Technology for Competitive Strategies , ICTCS 2022

作者： Valarmathi, B. Gupta, N. Srinivasa Chellatamilan, T. Santhi, K. Reddy, R. Hemadri Department of Software and Systems Engineering School of Information Technology and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Manufacturing School of Mechanical Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Analytics School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Mathematics School of Advanced Sciences Vellore Institute of Technology Tamil Nadu Vellore India

ISBN: (纸本)9789811996375

Mobility is the biggest issue for blind individuals. In order to move around, they must rely on others. Therefore, we are creating a navigational aid for blind people, to help the blind people in the world from various difficulties they face in day-to-day life. The World Health Organization (WHO) reported that a survey was conducted in 2014 and that there are an estimated 285 million visually impaired persons worldwide, of which 37 million are blind, with over 15 million of them being Indian. The majority of blind persons depend on other people for their activities since INDIA accounts for 21% of the global population of blind people (Khanam et al. in Int J Adv Res Sci Eng 7:195–199, 2018). Smart shoes play an important role. Obstacle detection is performed using ultrasonic sensor which is also done by many people in the previous projects or researches. The new concept that is included in this paper is that it can also detect any flame and potholes around the person using flame sensor and ultrasonic sensor, respectively. And we use shock sensor to detect any shock that occurs. If the smart assistive device or smart shoes senses an object, a pothole, a fire (from about three feet away), or a shock in front of the user, a buzzer will sound. These sensors are integrated using Arduino Uno. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Obstacle detectors

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Federated Learning-Based Intelligent Indoor Smoke and Fire Detection System for Smart Buildings

Federated Learning-Based Intelligent Indoor Smoke and Fire D...

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2024 International Conference on Telecommunications and Intelligent systems, ICTIS 2024

作者： Aymene Berkani, Mohamed Rafik Chouchane, Ammar Himeur, Yassine Abdennebi, Anes Sagiroglu, Seref Amira, Abbes Medea Algeria University Biskra University Center of Barika Laboratory of LI3C Amdoukal Road Barika05001 Algeria University of Dubai College of Engineering and Information Technology Dubai United Arab Emirates École de Technologie Supérieure Software and Information Technology Engineering Montréal Canada Analytics Security R&D Center Gazi University Artificial Intelligence and Big Data Ankara Turkey University of Sharjah Department of Computer Science Sharjah United Arab Emirates

ISBN: (纸本)9798331527396

Ensuring safety in smart buildings is crucial due to the increasing prevalence of smoke and fire hazards in modern environments. This paper introduces a novel privacy-preserving FL approach based on a CNN1D for smoke and fire detection in smart buildings. Our system integrates data from wearable environmental sensors to train a lightweight, edge-deployable DL-CNN1D model, ensuring data privacy while enabling collaborative learning across distributed clients using Federated Averaging (FedAvg) aggregation. Experiments conducted on a comprehensive air measurement dataset for smoke and fire detection demonstrate exceptional performance, with the global model achieving 99.97% accuracy, 99.96% precision, in smoke and fire recognition. Our model demonstrates a low communication cost of 0.4 MB, underscoring its efficiency for real-time applications. Our FL-based approach represents a significant step towards balancing the need for robust safety systems with growing privacy concerns in smart building environments. © 2024 IEEE.

关键词： Federated learning

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