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Analysis of blockchain protocol against static adversarial miners corrupted by long delay attackers

Science China(information Sciences) 2020年第3期63卷 49-63页

作者： Quan YUAN Puwen WEI Keting JIA Haiyang XUE Key Laboratory of Cryptologic Technology and Information Security Ministry of EducationShandong University Department of Computer Science and Technology Tsinghua University State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of Sciences Data Assurance and Communication Security Research Center Chinese Academy of Sciences

Bitcoin, which was initially introduced by Nakamoto, is the most disruptive and impactive cryptocurrency. The core Bitcoin technology is the so-called blockchain protocol. In recent years, several studies have focused on rigorous analyses of the security of Nakamoto’s blockchain protocol in an asynchronous network where network delay must be considered. Wei, Yuan, and Zheng investigated the effect of a long delay attack against Nakamoto’s blockchain protocol. However, their proof only holds in the honest miner setting. In this study, we improve Wei, Yuan and Zheng’s result using a stronger model where the adversary can perform long delay attacks and corrupt a certain fraction of the miners. We propose a method to analyze the converge event and demonstrate that the properties of chain growth, common prefix, and chain quality still hold with reasonable parameters in our stronger model.

关键词： blockchain bitcoin random oracle delay consensus protocol

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MIMO Underwater Acoustic Communication in Shallow Water with Ice Cover

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China Ocean Engineering 2019年第2期33卷 237-244页

作者： HAN Xiao YIN Jing-wei LIU Bing GUO Long-xiang Acoustic Science and Technology Laboratory Harbin Engineering University Key Laboratory of Marine Information Acquisition and Security (Harbin Engineering University) Ministry of Industry and Information Technology College of Underwater Acoustic Engineering Harbin Engineering University

Although multiple-input multiple-output(MIMO) underwater acoustic(UWA) communication has been intensively investigated in the past years, existing works mainly focus on open-water environment. There is no work reporting MIMO acoustic communication in under-ice environment. This paper presents results from a recent MIMO acoustic communication experiment which was conducted in Bohai Gulf during winter. In this experiment, high frequency MIMO signals centered at 10 kHz were transmitted from a two-element source array to a four-element vertical receiving array at 1 km range. According to the received signal of different array elements, MIMO acoustic communication in under-ice environment suffers less effect from co-channel interference compared with that in open-water environment. In this paper, time reversal followed by a single channel decision feedback equalizer is used to process the experimental data. It is demonstrated that this simple receiver is capable of realizing robust performance using fewer hydrophones(i.e. 2) without the explicit use of complex co-channel interference cancelation algorithms, such as parallel interference cancelation or serial interference cancelation.

关键词： underwater acoustic communication MIMO shallow water ice cover

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Selected-Mapping Peak-to-Average Power Reduction Method with Orthogonal Pilot Sequences in Underwater Acoustic OFDM System Without Side information

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Chinese Journal of Electronics 2021年第1期30卷 160-163页

作者： QIAO Gang XING Siyu ZHOU Feng Acoustic Science and Technology Laboratory Harbin Engineering University Key Laboratory of Marine Information Acquisition and Security (Harbin Engineering University) Ministry of Industry and Information Technology College of Underwater Acoustic Engineering Harbin Engineering University

A novel Selected-mapping(SLM) Peak-to-average power ratio(PAPR) reduction scheme requires no Side information(SI) in Underwater acoustic(UWA)OFDM system is proposed. In the proposed scheme,every distinct phase sequence is represented by a unique Orthogonal comb pilot sequence(OPS), and the orthogonal properties of the OPSs are used to distinguish the index of phase sequences at the receiver. Therefore, the proposed scheme does not need to reserve bits for transmitting SI,so that the data rate can be raised. Simulation results show that the PAPR reduction performance has almost 0.5 d B gains comparing to the Conventional SLM(C-SLM)scheme and the Bit error ratio(BER) performance is approximately the same as the SLM scheme with perfect SI. Field experimental results also demonstrate that the proposed scheme can differentiate phase sequences,therefore significantly enhance the quality of the UWA OFDM communication system.

关键词： 0.5dB gains OFDM modulation noise figure 0.5 dB Bit error ratio performance orthogonal pilot sequences orthogonal properties peak-to-average power reduction method C-SLM distinct phase sequence novel Selected-mapping phase sequences error statistics channel estimation UWA OFDM communication system unique Orthogonal comb pilot sequence Conventional SLM scheme perfect SI PAPR reduction performance Peak-to-average power ratio reduction scheme underwater acoustic communication underwater acoustic OFDM system

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Review of data security within energy blockchain:A comprehensive analysis of storage,management,and utilization

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High-Confidence Computing 2024年第3期4卷 82-102页

作者： Yunhua He Zhihao Zhou Yan Pan Fahui Chong Bin Wu Ke Xiao Hong Li School of Information Science and Technology North China University of TechnologyBeijing 100144China China Industrial Control Systems Cyber Emergency Response Team Beijing 100040China Key Laboratory in Blockchain and Data Security by Ministry of Industry and Information Technology Beijing 100040China Institute of Information Engineering Chinese Academy of Sciences Beijing 100195China

Energy systems are currently undergoing a transformation towards new paradigms characterized by decarbonization,decentralization,democratization,and *** this evolving context,energy blockchain,aiming to enhance efficiency,transparency,and security,emerges as an integrated technological solution designed to address the diverse challenges in this *** security is essential for the reliable and efficient functioning of energy *** pressing need to address challenges related to secure data storage,effective data management,and efficient data utilization is increasingly *** paper offers a comprehensive survey of academic discourse on energy blockchain data security over the past five years,adopting an all-encompassing perspective that spans data storage,management,and *** work systematically evaluates and contrasts the strengths and weaknesses of various research ***,this paper proposes an integrated hierarchical on-chain and off-chain security energy blockchain architecture,specifically designed to meet the complex security requirements of multi-blockchain business ***,this paper identifies key directions for future research,particularly in advancing the integration of storage,management,and utilization of energy blockchain data security.

关键词： Energy blockchain data security Storage Management Utilization

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Solving Multi-Objective Vehicle Routing Problems with Time Windows: A Decomposition-Based Multiform Optimization Approach

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Tsinghua Science and technology 2024年第2期29卷 305-324页

作者： Yiqiao Cai Zifan Lin Meiqin Cheng Peizhong Liu Ying Zhou Xiamen Key Laboratory of Data Security and Blockchain Technology College of Computer Science and TechnologyHuaqiao UniversityXiamen361021China College of Engineering Huaqiao UniversityQuanzhou362000China School of Computer Sciences Shenzhen Institute of Information TechnologyShenzhen518000China

In solving multi-objective vehicle routing problems with time windows (MOVRPTW),most existing algorithms focus on the optimization of a single problem formulation. However,little effort has been devoted to exploiting valuable knowledge from the alternate formulations of MOVRPTW for better optimization performance. Aiming at this insufficiency,this study proposes a decomposition-based multi-objective multiform evolutionary algorithm (MMFEA/D),which performs the evolutionary search on multiple alternate formulations of MOVRPTW simultaneously to complement each other. In particular,the main characteristics of MMFEA/D are three folds. First,a multiform construction (MFC) strategy is adopted to construct multiple alternate formulations,each of which is formulated by grouping several adjacent subproblems based on the decomposition of MOVRPTW. Second,a transfer reproduction (TFR) mechanism is designed to generate offspring for each formulation via transferring promising solutions from other formulations,making that the useful traits captured from different formulations can be shared and leveraged to guide the evolutionary search. Third,an adaptive local search (ALS) strategy is developed to invest search effort on different alternate formulations as per their usefulness for MOVRPTW,thus facilitating the efficient allocation of computational resources. Experimental studies have demonstrated the superior performance of MMFEA/D on the classical Solomon instances and the real-world instances.

关键词： MOVRPTW multiform optimization multiform construction knowledge transfer adaptive local search

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Model updating for real time dynamic substructures based on UKF algorithm

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Earthquake Engineering and Engineering Vibration 2020年第2期19卷 413-421页

作者： Su Tingli Tang Zhenyun Peng Lingyun Bai Yuting Jin Xuebo Kong Jianlei School of Computer Information and Engineering Beijing Technology and Business UniversityBeijing 100048China The Key Laboratory of Urban Security and Disaster Engineering Ministry of EducationBeijing University of TechnologyBeijing 100124China Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business UniversityBeijing 100048China China Light Industry Key Laboratory of Industrial Internet and Big Data Beijing Technology and Business UniversityBeijing 100048China

Combining the advantages of numerical simulation with experimental testing,real-time dynamic substructure(RTDS)testing provides a new experimental method for the investigation of engineered ***,not all unmodeled parts can be physically tested,as testing is often limited by the capacity of the test *** updating is a good option to improve the modeling accuracy for numerical substructures in *** this study,a model updating method is introduced,which has great performance in describing this *** order to determine the optimal parameters in this model,an Unscented Kalman Filter(UKF)-based algorithm was applied to extract the knowledge contained in the sensors *** the parameters that need to be identified are listed as the extended state variables,and the identification was achieved via the step-by-step state prediction and state update *** of the proposed method was verified through a group of experimental data,and results showed good ***,the proposed method was compared with the Extended Kalman Filter(EKF)-based method,and better accuracy was easily *** proposed parameter identification method has great applicability for structural objects with nonlinear behaviors and could be extended to research in other engineering fields.

关键词： dynamic substructure complex nonlinear model nonlinear estimation adaptive updating civil infrastructures

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Intelligent Fast Cell Association Scheme Based on Deep Q-Learning in Ultra-Dense Cellular Networks

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China Communications 2021年第2期18卷 259-270页

作者： Jinhua Pan Lusheng Wang Hai Lin Zhiheng Zha Caihong Kai Key Laboratory of Knowledge Engineering with Big Data Ministry of Education.School of Computer Science and Information EngineeringHefei University of TechnologyHefei 230601China Anhui Province Key Laboratory of Industry Safety and Emergency Technology Hefei 230601China Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education.School of Cyber Science and EngineeringWuhan UniversityWuhan 430072China

To support dramatically increased traffic loads,communication networks become *** cell association(CA)schemes are timeconsuming,forcing researchers to seek fast *** paper proposes a deep Q-learning based scheme,whose main idea is to train a deep neural network(DNN)to calculate the Q values of all the state-action pairs and the cell holding the maximum Q value is *** the training stage,the intelligent agent continuously generates samples through the trial-anderror method to train the DNN until *** the application stage,state vectors of all the users are inputted to the trained DNN to quickly obtain a satisfied CA result of a scenario with the same BS locations and user *** demonstrate that the proposed scheme provides satisfied CA results in a computational time several orders of magnitudes shorter than traditional ***,performance metrics,such as capacity and fairness,can be guaranteed.

关键词： ultra-dense cellular networks(UDCN) cell association(CA) deep Q-learning proportional fairness Q-learning

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IntML-KNN: A Few-Shot Radio Frequency Fingerprint Identification Scheme for Lora Devices

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IEEE Signal Processing Letters 2025年

作者： Cao, Xin Tan, Weijie Gao, Qiangqiang Hu, Zhilong Li, Chunguo Guizhou University College of Computer Science and Technology Guiyang550025 China Guizhou University State Key Laboratory of Public Big Data College of Computer Science and Technology Guiyang550025 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610025 China Ministry of Industry and Information Technology Laboratory of Cryptograph Application Technology Innovation and Testing Verification Beijing100015 China Southeast University School of Information Science and Engineering Nanjing210096 China

Deep learning (DL) is widely used in radio frequency fingerprint identification (RFFI). However, in few-shot case, traditional DL-based RFFI need to construct auxiliary dataset to realize radio frequency fingerprint identification. To address this issue, we propose a few-shot RFFI (FS-RFFI) method based on interpolating metric learning and KNN (IntML-KNN). Specifically, the method first extends the dataset with data augmentation, and CutMix interpolation. Secondly, combining with metric learning to enhance the generalization capacity of the model. Finally, KNN algorithm is designed to realize device classification and detection. The proposed IntML-KNN method is verified on the commercial available LoRa dataset. The experimental results indicate that the proposed scheme exhibits strong classification and generalization performance in FS-RFFI. Meanwhile, the recognition rate of the proposed IntML-KNN reaches 97.00% with only 10% samples. © 1994-2012 IEEE.

关键词： Deep learning

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Vertical Federated Learning Based on Consortium blockchain for data Sharing in Mobile Edge Computing

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Computer Modeling in Engineering & Sciences 2023年第10期137卷 345-361页

作者： Yonghao Zhang Yongtang Wu Tao Li Hui Zhou Yuling Chen State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China Blockchain Laboratory of Agricultural Vegetables Weifang University of Science and TechnologyWeifang262700China Guangxi Key Laboratory of Cryptography and Information Security Guilin University of Electronic TechnologyGuilin541004China

The data in Mobile Edge Computing(MEC)contains tremendousmarket value,and data sharing canmaximize the usefulness of the ***,certain data is quite sensitive,and sharing it directly may violate *** Federated Learning(VFL)is a secure distributed machine learning framework that completes joint model training by passing encryptedmodel parameters rather than raw data,so there is no data privacy leakage during the training ***,the VFL can build a bridge between data demander and owner to realize data sharing while protecting data ***,the VFL requires a third party for key distribution and decryption of training *** this article,we employ the consortium blockchain instead of the traditional third party and design a VFL architecture based on the consortium blockchain for data sharing in *** specifically,we propose a V-Raft consensus algorithm based on Verifiable Random Functions(VRFs),which is a variant of the *** VRaft is able to elect leader quickly and stably to assist data demander and owner to complete data sharing by ***,we apply secret sharing todistribute the private key to avoid the situationwhere the training result cannot be decrypted if the leader ***,we analyzed the performance of the V-Raft and carried out simulation experiments,and the results show that compared with Raft,the V-Raft has higher efficiency and better scalability.

关键词： Mobile edge computing vertical federated learning consortium blockchain consensus algorithm

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Cross-modality information Check for Detecting Jailbreaking in Multimodal Large Language Models

Cross-modality Information Check for Detecting Jailbreaking ...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Xu, Yue Qi, Xiuyuan Qin, Zhan Wang, Wenjie School of Information Science and Technology ShanghaiTech University China The State Key Laboratory of Blockchain and Data Security Zhejiang University China

ISBN: (纸本)9798891761681

Multimodal Large Language Models (MLLMs) extend the capacity of LLMs to understand multimodal information comprehensively, achieving remarkable performance in many vision-centric tasks. Despite that, recent studies have shown that these models are susceptible to jailbreak attacks, which refer to an exploitative technique where malicious users can break the safety alignment of the target model and generate misleading and harmful answers. This potential threat is caused by both the inherent vulnerabilities of LLM and the larger attack scope introduced by vision input. To enhance the security of MLLMs against jailbreak attacks, researchers have developed various defense techniques. However, these methods either require modifications to the model's internal structure or demand significant computational resources during the inference phase. Multimodal information is a double-edged sword. While it increases the risk of attacks, it also provides additional data that can enhance safeguards. Inspired by this, we propose Cross-modality information DEtectoR (CIDER), a plug-and-play jailbreaking detector designed to identify maliciously perturbed image inputs, utilizing the cross-modal similarity between harmful queries and adversarial images. CIDER is independent of the target MLLMs and requires less computation cost. Extensive experimental results demonstrate the effectiveness and efficiency of CIDER, as well as its transferability to both white-box and black-box MLLMs. The resource is available at https://***/PandragonXIII/CIDER. © 2024 Association for Computational Linguistics.

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