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AgileShard: Turning the Sharded Blockchain into a Real-Time Transaction Processing System 44

AgileShard: Turning the Sharded Blockchain into a Real-Time ...

引用

44th IEEE Real-Time Systems Symposium, RTSS 2023

作者： Shi, Jianfeng Wu, Heng Liu, Wang Gao, Heran Zhang, Wenbo University of Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Nanjing China Software Engineering Technology Research and Development Center Institute of Software Chinese Academy of Sciences Beijing China Nanjing Institute of Software Technology Nanjing China Institute of Software Chinese Academy of Sciences State Key Laboratory of Computer Science Beijing China

ISBN: (纸本)9798350328578

Blockchain, as an emerging transaction processing system, suffers from low throughput and high latency. Sharded blockchains can significantly increase throughput by dividing nodes into groups (i.e., shards) to process disjoint transactions in parallel. However, the diverse latency requirements of transactions in current sharded blockchains are not well met. Three challenges prevent the sharded blockchain from becoming a real-time transaction processing system, namely, the static block size, the first-come-first-served transaction packing strategy, and the load imbalance. Therefore, this paper proposes 3 methods to help turn the sharded blockchain into a real-time transaction processing system. First, we propose an inter-shard dynamic block size negotiation method that enables shards to adaptively determine the globally optimal block size based on the deadlines of pending transactions. Then, we propose a DAG-based transaction packing method for reducing the number of deadline violations and improving parallelism. Finally, we propose a minimum-cost-flow-based shard reconfiguration method to address load imbalance. Under real datasets on Ethereum, experimental results show that AgileShard using the above three methods can effectively improve the transaction deadline satisfaction rate. © 2023 IEEE.

关键词： Blockchain

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eSROP Attack: Leveraging Signal Handler to Implement Turing-Complete Attack Under CFI Defense 1

引用

18th EAI International Conference on Security and Privacy in Communication Networks, SecureComm 2022

作者： Zhang, Tianning Cai, Miao Zhang, Diming Huang, Hao Department of Computer Science and Technology Nanjing University Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai University Nanjing China School of Computer and Information Hohai University Nanjing China College of Computer Engineering Jiangsu University of Science and Technology Nanjing China

ISBN: (数字)9783031255380

ISBN: (纸本)9783031255373

Signal Return Oriented Programming (SROP) is a dangerous code reuse attack method. Recently, defense techniques have been proposed to defeat SROP attacks. In this paper, we leverage the signal nesting mechanism provided by current operating systems and propose a new variant of SROP attack called enhanced SROP (eSROP) attack. eSROP provides the ability of invoking arbitrary system calls, simulating Turing-complete computation, and even bypassing the fine-grained label-based CFI defense, without modifying the return address and instruction register in the signal frame. Because the signal returns to the interrupted instruction, the shadow stack defense can hardly detect our attack. Signal has strong flexibility which can interrupt the normal control flow. We leverage such flexibility to design a new code reuse attack. To evaluate eSROP, we perform two exploits on two real-world programs, namely Proftpd and Wu-ftpd. In our attacks, adversaries can invoke arbitrary system calls and obtain a root shell. Both attacks succeed within 10 min under strict system defense such as data execution prevention, address space layout randomization, and coarse-grained control flow integrity. © 2023, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Network security

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Privacy-preserving and efficient user matching based on attribute encryption in mobile social networks

Privacy-preserving and efficient user matching based on attr...

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作者： Wu, Lei Zhao, Shengnan Wei, Xia Meng, Lingzhen School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan China

With the rapid popularity of social networking platforms, users can be matched when sharing their profiles. However, there is a risk of leakage of sensitive user information during the user matching process, which leads to the lack of user privacy protection. In this paper, we propose a privacy protection scheme based on the encryption of hidden attributes during user matching in mobile social networks, which uses linear secret sharing scheme (LSSS) as the access structure based on ciphertext policy attribute-based encryption (CP-ABE), and the match server can perform friend recommendation by completing bi-directional attribute matching determination without disclosing user attribute information. In addition, the use of selective keywords protects the privacy of requesters and publishers in selecting keywords and selecting plaintext attacks. The scheme reduces the encryption and decryption overhead for users by dividing encryption into a preparation phase and an online phase and shifting most of the decryption overhead from the requester to the match server. The experimental results show that the scheme ensures user privacy while effectively reducing communication overhead. © 2021 John Wiley & Sons, Ltd.

关键词： Cost reduction

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Research on Quality Model for Quantum Simulator software 26

Research on Quality Model for Quantum Simulator Software

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26th ACIS International Winter Conference on software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD-Winter 2023

作者： Wang, Chao Chen, Jingwei Ge, JianXin Wu, XueZhong Qu, QianQian Luo, Le Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai Development Center of Computer Software Technology Shanghai China Qudoor Technologies Inc. Hefei China Software Engineering of Computer and Information Engineering College Shanghai Polytechnic University Shanghai China Qudoor Technologies Inc. School of Physics and Astronomy Sun Yat-Sen University Zhuhai China

ISBN: (纸本)9798350345865

In recent years, the demand for arithmetic power from all walks of life is growing, especially the increasing popularity of AIGC, which makes people realize that huge technological progress cannot be made without the support of large arithmetic power. Quantum computing may bring a leap in computing power and become a 'trigger' and 'catalyst' to accelerate the development of science and technology innovation, and its technical development trend and application prospects have become a hot issue of concern, and quantum simulators are a very important part of the development process. The development of quantum simulators is a very important part of the process. However, due to the lack of systematic evaluation theories and methods, it is difficult to quantify and analyze the quality of the increasing number of simulators on the market, which may hinder researchers from practicing their quantum algorithms objectively or developing quantum technologies. For these reasons, this paper proposes a quality model for quantum simulator software, which reflects the quality characteristics of simulators in seven aspects, such as functionality and performance efficiency, and selects some simulators for experimental validation of the proposed model to prove its rationality. © 2023 IEEE.

关键词： Quality control

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A Feature-Aware Transformer Approach for Enhanced Maritime Trajectory Prediction

A Feature-Aware Transformer Approach for Enhanced Maritime T...

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2024 International Conference Optoelectronic Information and Optical Engineering, OIOE 2024

作者： Wang, Wuyong Ma, Xingkong Liu, Bo College of Computer Science and Technology National University of Defense Technology Changsha410073 China State Key Laboratory of Complex & Critical Software Environment Changsha410073 China Strategic Evaluation and Consultation Center Academy of Military Sciences Beijing100000 China

ISBN: (数字)9781510688209

ISBN: (纸本)9781510688193

Predicting ship trajectories is vital for enhancing maritime safety, optimizing route planning, and boosting the efficiency of maritime traffic management. Current research often neglects the complex marine environment and the effect of ship performance on prediction accuracy. To address these deficiencies, we present a feature-aware transformer-based methodology that integrates meteorological and ship performance data. Our method begins with a time interpolation technique to synchronize the inconsistent time resolutions between meteorological and trajectory data, thereby establishing a comprehensive multi-source dataset. We develop a feature-aware module using transformer architecture to consolidate ship and meteorological features into a unified low-dimensional space, thus enabling the modeling of feature interactions. Experiments on Automatic Identification System (AIS) datasets indicate that our approach reduces the average prediction error to within 4 kilometers over a prediction period of up to 6 hours, achieving a 13% improvement over the state-of-the-art transformer-based methods. © 2025 SPIE.

关键词： Vehicle performance

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Generating Targeted Universal Adversarial Perturbation against Automatic Speech Recognition via Phoneme Tailoring

Generating Targeted Universal Adversarial Perturbation again...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Zhang, Yujun Chen, Yanqu Wang, Jiakai Hu, Jin Tao, Renshuai Liu, Xianglong State Key Laboratory of Complex & Critical Software Environment Beihang University China School of Computer Science and Engineering Beihang University China College of Computer Science Beijing University of Technology China Zhongguancun Laboratory China School of Computer and Information Technology Beijing Jiaotong University China Institute of Data Space Hefei Comprehensive National Science Center China

ISBN: (纸本)9798350368741

There is a growing concern about adversarial attacks against automatic speech recognition (ASR) systems. Although research into targeted universal adversarial examples (AEs) has progressed, current methods are constrained by inefficient exploitation of audio features, demonstrating insufficient attack ability and robustness in the physical world. To solve this problem, we propose a phoneme-tailored attack (PTA) to improve the quality of the generated AEs. Specifically, to improve attack ability, we propose a Diverse Audio Composition Enrichment method, which enhances the utilization of audio features through phoneme-level slicing and recombination. To adapt AEs to complex environments, we propose a Natural Noise Pattern Guidance method to align AEs with natural noise patterns to improve their robustness. Experiments show that our method achieves an average accuracy of more than 72.34% and 98% with and without a norm constraint, and also demonstrates excellent performance in terms of generalization across datasets and resilience to MP3 compression. © 2025 IEEE.

关键词： Automatic speech recognition natural noise pattern phoneme-level targeted universal adversarial examples

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Bi-Orthogonal Projection Learning for Dimensionality Reduction 3

Bi-Orthogonal Projection Learning for Dimensionality Reducti...

引用

3rd International Conference on Intelligent Power and Systems, ICIPS 2023

作者： Liang, Yingyi Fan, Junjun Li, Chunsheng Wen, Jiajun Guangdong University of Technology Guangzhou China Shenzhen University College of Computer Science & Software Engineering Shenzhen China Laboratory for Artificial Intelligence in Design Hong Kong

ISBN: (纸本)9798350328691

This paper proposes a novel bi-orthogonal projection learning (BOPL) for dimensionality reduction (DR) methods, which further extends the existing DR to a more flexible, robust, and sparse embedding framework. Unlike conventional methods that use only one kind of projection for learning in DR, the proposed BOPL introduces two kinds of projection, which are orthogonal and provides the true projection the freedom for more accurate data transformation in subspace learning. Inspired by the observation that the two projections share many similar data structures, the projections are expected to preserve the similarity structure of data by using two different reconstruction ways. The proposed method can also handle data corrupted by noises since a sparse item is employed to compensate for the noises during DR. Several novel unsupervised DR methods (i.e., BOPL_PCA, BOPL_NPE, and BOPL_LPP) are derived from the proposed framework. The results of experiments on the natural and synthetic data sets demonstrate that the proposed methods outperform the existing well-established DR methods. ©2023 IEEE.

关键词： Metadata

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Measurement and Optimization of Repetition Scheme in NB-IoT Uplink 26

Measurement and Optimization of Repetition Scheme in NB-IoT ...

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26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： Chen, Kai Chang, Xiangmao Zhan, Jun Zhao, Yanchao Nanjing University of Aeronautics and Astronautics Computer Science and Technology Nanjing China Key Laboratory of Safety-Critical Software Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9798350331684

Narrowband Internet of Things (NB-IoT) is an low-power wide area network based on cellar architecture. The repetition scheme is a key solution to achieve enhanced coverage with low complexity in the uplink. However, the impact of the current repetition scheme on energy consumption and coverage performance of NB-IoT are still unclear. In this paper, we conduct field measurements of the repetition scheme in terms of energy efficiency. We find that most of repetition values configured by the eNodeB lead to non-optimal energy efficiency. Then we propose an adaptive repetition scheme based on a regression block delivery rate (BDR) model which can be derived from a theoretical model and a small number of measurements. We conduct simulations based on real-world measurement data. The results show that the proposed adaptive repetition scheme outperforms the default repetition scheme in both energy efficiency and data transmission rate. © 2023 IEEE.

关键词： Internet of things

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SLAM: Towards Efficient Multilingual Reasoning via Selective Language Alignment 31

SLAM: Towards Efficient Multilingual Reasoning via Selective...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Fan, Yuchun Mu, Yongyu Wang, Yilin Huang, Lei Ruan, Junhao Li, Bei Xiao, Tong Huang, Shujian Feng, Xiaocheng Zhu, Jingbo NLP Lab School of Computer Science and Engineering Northeastern University Shenyang China NiuTrans Research Shenyang China Harbin Institute of Technology Harbin China Meituan Inc. National Key Laboratory for Novel Software Technology Nanjing University China

ISBN: (纸本)9798891761964

Despite the significant improvements achieved by large language models (LLMs) in English reasoning tasks, these models continue to struggle with multilingual reasoning. Recent studies leverage a full-parameter and two-stage training paradigm to teach models to first understand non-English questions and then reason. However, this method suffers from both substantial computational resource computing and catastrophic forgetting. The fundamental cause is that, with the primary goal of enhancing multilingual comprehension, an excessive number of irrelevant layers and parameters are tuned during the first stage. Given our findings that the representation learning of languages is merely conducted in lower-level layers, we propose an efficient multilingual reasoning alignment approach that precisely identifies and fine-tunes the layers responsible for handling multilingualism. Experimental results show that our method, SLAM, only tunes 6 layers' feed-forward sub-layers including 6.5−8% of all parameters within 7B and 13B LLMs, achieving superior average performance than all strong baselines across 10 languages. Meanwhile, SLAM only involves one training stage, reducing training time by 4.1 − 11.9× compared to the two-stage method. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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A Dynamic Interest-Aware Message-Passing GCN for Recommendation 24

A Dynamic Interest-Aware Message-Passing GCN for Recommendat...

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24th IEEE International Conference on software Quality, Reliability and Security Companion, QRS-C 2024

作者： He, Weichao Zhu, Yi Song, Mei Wu, Zixin Hao, Guosheng School of Computer Science and Technology Jiangsu Normal University Jiangsu Xuzhou China Jiangsu Engineering Technology Research Center of Ict in Education Jiangsu Xuzhou China Ministry of Industry and Information Technology Key Laboratory of Safety-Critical Software Jiangsu Nanjing China

ISBN: (纸本)9798350365658

Over the past few years, Graph Convolutional Networks (GCN) have emerged as a promising tool in the field of recommendation. They have the ability to effectively learn user and item embeddings by leveraging collaborative signals from higher-order neighbors. Nevertheless, the recommendation models based on GCN also face a common issue. As more layers are added, the node embeddings start to become increasingly similar and eventually become indistin-guishable, leading to a decline in performance. To address the issues at hand, we present a recommendation model called DIMP-GCN. This model utilizes a Dynamic Interest-aware Message-Passing approach, where users and interacted items are organized into distinct subgraphs based on their interests. Within each subgraph, single-layer graph convolution operations are performed. As a result, the users who have been updated are divided based on their interests once again, leading to dynamic changes in subgraph partitioning as the network layers stack. Nodes are able to acquire more accurate representations through this process. We conduct extensive experiments on three established datasets, showcasing the superior performance of our DIMP-GCN compared to other state-of-the-art GCN-based recommendation models. © 2024 IEEE.

关键词： Message passing

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