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Artificial Intelligence, Networking and information Technology (AINIT), International Seminar on

作者： Yang Liu Zehui Xie Nong Xiao Zhiguang Chen Yang Ou Institute for Quantum Information & State Key Laboratory of High-Performance Computing College of Computer National University of Defense Technology Changsha China School of computer science and Engineering Sun Yat-sen University Guangzhou China College of Computer National University of Defense Technology Changsha China

The hybrid storage architecture incorporates a blockchain dual-index structure optimized for byte addressing in non-volatile memory, low-latency features, and the large capacity of SSD. This paper presents a novel LSM-Tree architecture that leverages the byte-addressing characteristics of non-volatile memory. The layers of the level 0 and level 1 are stored in non-volatile memory while employing a local key-value separation strategy to minimize read and write operations during compaction. A logic compression strategy is proposed to handle data compression tasks efficiently. A dual-index structure design is introduced for users to address the scope and multi-keyword queries in the blockchain system. During the compression process, keyword switching occurs during data reordering, ensuring that data within the same SSTable is rearranged according to user preferences. By effectively harnessing the advantages of each level in the hybrid storage architecture, this design significantly reduces both databases write time and the response time for complex queries.

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MCDS: An Effective Multi-UAV Collaborative Decision-Making System in Mobile Edge computing Networks

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IEEE Internet of Things Journal 2025年

作者： Xiong, Naixue Zhong, Weiyu Chen, Yuxiang He, Dacheng Li, Yuhui Chen, Linshu Liang, Wei Sanya Research Institute of Hunan University of Science and Technology School of Computer Science and Engineering Hunan University of Science and Technology Hunan Key Laboratory for Service Computing and Novel Software Technology China Sanya Research Institute of Hunan University of Science and Technology Hunan University School of Computer Science and Engineering Hunan University of Science and Technology Hunan Key Laboratory for Service Computing and Novel Software Technology School of Information Science and Engineering China The Hong Kong Polytechnic University Department of Computing Hong Kong

Mobile Edge computing (MEC) pushes computing resources from the network center to the network edge to provide efficient and reliable computing services. However, due to the mobility and diversity of mobile users (MUs), edge servers (ESs) are likely to be overloaded, which leads to a rapid decline in the quality of service provided by the MEC system. This paper introduces unmanned aerial vehicles (UAVs) to solve the problem of ES overload. This paper presents an effective Multi-UAV Collaborative Decision-Making System (MCDS) tailored to optimize task offloading and resource allocation in MEC networks. The proposed system seeks to reduce task computing delays and energy consumption while guaranteeing timely task completion and compliance with resource constraints. We design a distributed two-stage optimization algorithm to jointly optimize the task offloading decision and resource allocation of the collaborative computing system (UAVs, ESs, and MUs). To address the flight cooperation problem of multi-UAVs, we also proposed a task-aware scheduling algorithm for multi-UAVs. In addition, we conducted a large number of simulation experiments. Experimental results show that our two-stage optimization scheme is lower than other benchmark algorithms in terms of task completion delay, energy consumption and total cost of objective function. Specifically, compared with seven baseline algorithms under three different system setting scenarios, our algorithm reduces the total cost by an average of 38.79%, the energy consumption by an average of 40.70%, and the delay by an average of 15.67%. © 2014 IEEE.

关键词： Drones

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The Power of Bamboo: On the Post-Compromise Security for Searchable Symmetric Encryption 30

The Power of Bamboo: On the Post-Compromise Security for Sea...

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30th Annual Network and Distributed System Security Symposium, NDSS 2023

作者： Chen, Tianyang Xu, Peng Picek, Stjepan Luo, Bo Susilo, Willy Jin, Hai Liang, Kaitai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab China Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering China Cluster and Grid Computing Lab School of Computer Science and Technology China Huazhong University of Science and Technology Wuhan430074 China Digital Security Group Radboud University Nijmegen Netherlands Department of EECS Institute of Information Sciences The University of Kansas LawrenceKS United States Institute of Cybersecurity and Cryptology School of Computing and Information Technology University of Wollongong WollongongNSW2522 Australia Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628 CD Netherlands

ISBN: (纸本)1891562835

Dynamic searchable symmetric encryption (DSSE) enables users to delegate the keyword search over dynamically updated encrypted databases to an honest-but-curious server without losing keyword privacy. This paper studies a new and practical security risk to DSSE, namely, secret key compromise (e.g., a user’s secret key is leaked or stolen), which threatens all the security guarantees offered by existing DSSE schemes. To address this open problem, we introduce the notion of searchable encryption with key-update (SEKU) that provides users with the option of non-interactive key updates. We further define the notion of post-compromise secure with respect to leakage functions to study whether DSSE schemes can still provide data security after the client’s secret key is compromised. We demonstrate that post-compromise security is achievable with a proposed protocol called "Bamboo". Interestingly, the leakage functions of Bamboo satisfy the requirements for both forward and backward security. We conduct a performance evaluation of Bamboo using a real-world dataset and compare its runtime efficiency with the existing forward-and-backward secure DSSE schemes. The result shows that Bamboo provides strong security with better or comparable performance. © 2023 30th Annual Network and Distributed System Security Symposium, NDSS 2023. All Rights Reserved.

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LazyDB: I/O Optimization of Blockchain Storage System Based on Non-Volatile Memory

LazyDB: I/O Optimization of Blockchain Storage System Based ...

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information science, Parallel and Distributed Systems (ISPDS), International Conference on

作者： Yang Liu Xuran Ge Nong Xiao Zhiguang Chen Yang Ou State Key Laboratory of High-Performance Computing Institute for Quantum Information College of Computer National University of Defense Technology Changsha China School of computer science and Engineering Sun Yat-sen University Guangzhou China College of Computer National University of Defense Technology Changsha China

For the blockchain storage system, this paper proposes an I/O optimization scheme based on non-volatile memory based on the storage performance requirements of the blockchain system application. This scheme adopts the key-value separation strategy. Due to the uncertain size of transaction data, by separating the “key” and “value” of transaction data, the inherent read-write amplification problem of the LSM-Tree structure is solved. The key-value separation strategy redesigns the storage system's space management and garbage collection mechanisms. Therefore, this chapter uses the byte-addressing characteristics of non-volatile memory to build a new data storage structure, a lazy compression mechanism, and a lazy garbage collection mechanism. On this basis, this paper builds a LazyDB database system for blockchain storage. To ensure the safe and reliable operation of the blockchain system, it can make full use of the storage medium and data characteristics, reducing the blockchain reading and writing process. The I/O overhead in the storage system improves the storage performance of the system. The experimental results show that compared with the most commonly used databases, such as LevelDB and RocksDB in the blockchain system, LazyDB effectively reduces the write amplification of the system and has higher read, write, and data update performance.

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A survey on user-centric cell-free massive MIMO systems

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Digital Communications and Networks 2022年第5期8卷 695-719页

作者： Shuaifei Chen Jiayi Zhang Jing Zhang Emil Björnson Bo Ai School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing100044China Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong UniversityBeijing100044China Department of Computer Science KTH Royal Institute of TechnologySE-16440KistaSweden Department of Electrical Engineering(ISY) Linköping UniversitySE-58183LinköpingSweden State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing100044China

The mobile data traffic has been exponentially growing during the last several *** was enabled by the densification of the network infrastructure in terms of increased cell density(i.e.,Ultra-Dense Network(UDN))and/or the increased number of active antennas per Access Point(AP)(i.e.,massive Multiple-Input Multiple-Output(mMIMO)).However,neither UDN nor mMIMO will meet the increasing demand for the data rate of the Sixth Generation(6G)wireless communications due to the inter-cell interference and large quality-of-service ***-Free(CF)mMIMO,which combines the best aspects of UDN and mMIMO,is viewed as a key solution to this *** such systems,each User Equipment(UE)is served by a preferred set of surrounding APs *** this paper,we provide a survey of the state-of-the-art literature on CF *** a starting point,the significance and the basic properties of CF mMIMO are *** then present the canonical framework to discuss the essential details(i.e.,transmission procedure and mathematical system model).Next,we provide a deep look at the resource allocation and signal processing problems related to CF mMIMO and survey the up-to-date schemes and *** that,we discuss the practical issues in implementing CF mMIMO and point out the potential future ***,we conclude this paper with a summary of the key lessons learned in this field.

关键词： 6G network User-centric cell-free network Massive multiple-input multiple-output

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DESIGN AND DEVELOPMENT OF MORPHOLOGICAL ANALYZER FOR TIGRIGNA VERBS USING HYBRID APPROACH

Research Square

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Research Square 2023年

作者： Gebremeskel, Hagos Gebremedhin Chong, Feng Heyan, Huang Beijing Engineering Research Center of High Volume Language Information Processing Cloud Computing Applications Laboratory School of Computer Science and Technology Beijing Institute of Technology China Department of Computer Science Mekelle University Tigray Mekelle231 Ethiopia

Morphological analyzer is the base for various high-level NLP applications such as information retrieval, spell checking, grammar checking, machine translation, speech recognition, POS tagging and automatic sentence construction. This paper is carefully designed for design and analysis of morphological analyzer Tigrigna verbs using hybrid of memory learning and rules based approaches. The experiment have conducted using Python 3 where TiMBL algorithms IB2 and TRIBL2, and Finite State Transducer rules are used. The performance of the system has been evaluated using 10 fold cross validation technique. Testing was conducted using optimized parameter settings for regular verbs and linguistic rules of the Tigrigna language allomorph and phonology for the irregular verbs. The accuracy of the memory based approach with optimized parameters of TiMBL algorithm IB2 and TRIBL2 was 93.24% and 92.31%, respectively. Finally, the hybrid approach had an actual performance of 95.6% using linguistic rules for handling irregular and copula verbs. © 2023, CC BY.

关键词： Machine learning

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DEGSTalk: Decomposed Per-Embedding Gaussian Fields for Hair-Preserving Talking Face Synthesis

arXiv

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arXiv 2024年

作者： Deng, Kaijun Zheng, Dezhi Xie, Jindong Wang, Jinbao Xie, Weicheng Shen, Linlin Song, Siyang Computer Vision Institute School of Computer Science and Software Engineering Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Guangdong Provincial Key Laboratory of Intelligent Information Processing China Department of Computer Science University of Exeter United Kingdom

Accurately synthesizing talking face videos and capturing fine facial features for individuals with long hair presents a significant challenge. To tackle these challenges in existing methods, we propose a decomposed per-embedding Gaussian fields (DEGSTalk), a 3D Gaussian Splatting (3DGS)-based talking face synthesis method for generating realistic talking faces with long hairs. Our DEGSTalk employs Deformable Pre-Embedding Gaussian Fields, which dynamically adjust pre-embedding Gaussian primitives using implicit expression coefficients. This enables precise capture of dynamic facial regions and subtle expressions. Additionally, we propose a Dynamic Hair-Preserving Portrait Rendering technique to enhance the realism of long hair motions in the synthesized videos. Results show that DEGSTalk achieves improved realism and synthesis quality compared to existing approaches, particularly in handling complex facial dynamics and hair preservation. Our code will be publicly available at https://***/CVI-SZU/DEGSTalk. Copyright © 2024, The Authors. All rights reserved.

关键词： Gaussian distribution

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ANF: Attention-Based Noise Filtering Strategy for Unsupervised Few-Shot Classification 18th

ANF: Attention-Based Noise Filtering Strategy for Unsupervis...

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18th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2021

作者： Ni, Guangsen Zhang, Hongguang Zhao, Jing Xu, Liyang Yang, Wenjing Lan, Long Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha410073 China Systems Engineering Institute AMS Beijing China

ISBN: (纸本)9783030893699

How to learn concepts from few-shot samples remains an open challenge in the deep learning era. The previous meta-learning methods require a large number of annotated samples in the training phase, which still contributes to high manual-labeling costs. In this paper, we propose a unsupervised few-shot learning framework and pointed out that negative queue constructed via randomly sampling contains many false-negative samples (noise), which has negative impacts on the model’s generalized performance especially when only few samples are available. Specially, we propose an Attention-based Noise Filtering (ANF) strategy to make momentum contrastive loss more applicable to few-shot learning scenario. In addition, we also propose a dynamic momentum update method, which can greatly improve the classification accuracy. Our evaluations demonstrate state-of-the-art unsupervised few-shot learning performance, which is comparable to supervised baseline models. © 2021, Springer Nature Switzerland AG.

关键词： computer vision

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Learning From Single-Expert Annotated Labels for Automatic Sleep Staging 48

Learning From Single-Expert Annotated Labels for Automatic S...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Luan, Zhiheng Ren, Yanzhen Peng, Li Chen, Xiong Yang, Xiuping Tu, Weiping Yang, Yuhong Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education China Wuhan University School of Cyber Science and Engineering China Zhongnan Hospital of Wuhan University Head and Neck Surgery Department of Otorhinolaryngology China Zhongnan Hospital of Wuhan University Sleep Medicine Centre China Wuhan University School of Computer Science China

ISBN: (纸本)9781728163277

Existing automatic sleep staging algorithms rely on accurately labeled data. However, due to the subjectivity of sleep experts, accurate labels must be obtained through joint labeling by multiple experts, which results in high time and labor costs. In this work, we treat labels mislabeled by a single expert as noisy labels and first propose SE-ASS, an automatic sleep staging learning framework based on single-expert annotated data. Since multiple models tend to produce inconsistent predictions for instances with incorrect labels during training, we use two networks with the same structure but different initializations and regularize them with a prediction consistency loss to prevent overfitting to noisy labels. Furthermore, we use a contrastive loss between models to enhance the exploration of feature representations without relying on potentially noisy labels. Our results on two publicly available datasets show that SE-ASS can effectively improve the performance of automatic sleep staging models trained on single-expert annotated datasets. © 2023 IEEE.

关键词： Deep learning

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Towards Evidence-Based Cybersecurity Assessment of Programmable Systems to Ensure the Protection of Critical IT Infrastructure 12

Towards Evidence-Based Cybersecurity Assessment of Programma...

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12th IEEE International Conference on Intelligent Data Acquisition and Advanced computing Systems: Technology and Applications, IDAACS 2023

作者： Illiashenko, Oleg Kharchenko, Vyacheslav Odarushchenko, Oleg National Aerospace University 'KhAI' Department of Computer Systems and Networks Kharkiv61070 Ukraine Institute of Information Science and Technologies 'Alessandro Faedo' - Isti Cnr Software Engineering & Dependable Computing Laboratory Pisa56124 Italy Research and Production Enterprise Rpc Radics Llc Kropyvnytskyi25009 Ukraine

ISBN: (纸本)9798350358056

The paper is devoted to developing scientific principles, methods, means, and information technology of model-oriented verification and evidence-based assessment using functional safety and cybersecurity cases for programmable systems of critical applications (PSCA). In particular, information and control systems important for the safety of nuclear power plants (NPPs), aerospace systems, railway domains, etc., developed using Field Programmable Gate Arrays (FPGAs) and hardware platforms are reviewed. The goal is to ensure the guaranteed completeness and reliability of its functional safety and cybersecurity assessment by developing and implementing a set of formal and semi-formal methods and tools that consider defects of different nature - physical, design, trojans, and vulnerabilities that can be attacked and lead to a fatal system failure, which results in damaging the critical IT infrastructure. The methods shown are based on integrating algebraic, tabular, graph models, and case assessment methodology. The methods are implemented as appropriate technologies for evidence-based verification and evaluation of PSCA. For formal methods, a prototype of a translator of Very high-Speed Integrated Circuits Hardware Description Language (VHDL) code is developed into an algebra of behaviors. It provides evidence-based verification and a framework and tools to design reports on assessing the cybersecurity and functional safety of programmable systems. © 2023 IEEE.

关键词： critical IT infrastructure cybersecurity FPGA functional safety programmable systems of critical applications

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