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CCM-FL:Covert communication mechanisms for federated learning in crowd sensing IoT

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Digital Communications and Networks 2024年第3期10卷 597-608页

作者： Hongruo Zhang Yifei Zou Haofei Yin Dongxiao Yu Xiuzhen Cheng institute of Intelligent computing School of Computer Science and TechnologyShandong UniversityQingdao266237China

The past decades have witnessed a wide application of federated learning in crowd sensing,to handle the numerous data collected by the sensors and provide the users with precise and customized ***,how to protect the private information of users in federated learning has become an important research *** with the differential privacy(DP)technique and secure multiparty computation(SMC)strategy,the covert communication mechanism in federated learning is more efficient and energy-saving in training the ma-chine learning *** this paper,we study the covert communication problem for federated learning in crowd sensing Internet-of-Things *** from the previous works about covert communication in federated learning,most of which are considered in a centralized framework and experimental-based,we firstly proposes a centralized covert communication mechanism for federated learning among n learning agents,the time complexity of which is O(log n),approximating to the optimal ***,for the federated learning without parameter server,which is a harder case,we show that solving such a problem is NP-hard and prove the existence of a distributed covert communication mechanism with O(log logΔlog n)times,approximating to the optimal solution.Δis the maximum distance between any pair of learning *** analysis and nu-merical simulations are presented to show the performance of our covert communication *** hope that our covert communication work can shed some light on how to protect the privacy of federated learning in crowd sensing from the view of communications.

关键词： Covert communications Federated learning Crowd sensing SINR model

Privacy Preserving Algorithm for Spectrum Sensing in Cognitive Vehicle Networks

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Chinese Journal of Electronics 2024年第1期33卷 30-42页

作者： Hongning LI Tonghui HU Jiexiong CHEN Xiuqiang WU Qingqi PEI Guangzhou institute of Technology Xidian University Guangzhou CEPREI Shaanxi Key Laboratory of Blockchain and Secure computing

The scarcity of spectrum resources fails to meet the increasing throughput demands of vehicular networks. There is an urgent need to maximize the utilization of spectrum bands in mobile networks. To ascertain the availability of spectrum bands, users should engage in wireless channel sensing and collaboration. However, spectrum sensing data always involves users’ privacy, such as their location. This paper first introduces sensing trajectory inference attack in cognitive vehicular networks and then proposes a data confusion-based privacy-preserving algorithm and a cryptonym array-based privacy-preserving aggregation scheme for spectrum sensing in cognitive vehicular networks. Unlike existing methods, the proposed schemes transmit confused data during the aggregation process. This deliberate obfuscation makes it almost impossible to infer users’ location from the transmitted data. The analysis demonstrates the resilience of the proposed schemes against sensing trajectory inference attack.

关键词： Privacy Data privacy Wireless sensor networks Authentication Data aggregation Throughput Inference algorithms

Extracting Integrated Features of Electronic Medical Records Big Data for Mortality and Phenotype Prediction

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Chinese Journal of Electronics 2024年第3期33卷 776-792页

作者： Fei LI Yiqiang CHEN Yang GU Yaowei WANG institute of computing Technology University of Chinese Academy of Sciences Pengcheng Laboratory

The key to synthesizing the features of electronic medical records(EMR) big data and using them for specific medical purposes,such as mortality and phenotype prediction,is to integrate the individual medical event and the overall multivariate time series feature extraction automatically,as well as to alleviate data imbalance *** paper provides a general feature extraction method to reduce manual intervention and automatically process large-scale *** processing uses two variational auto-encoders(VAEs) to automatically extract individual and global *** avoids the well-known posterior collapse problem of Transformer VAE through a uniquely designed "proportional and stabilizing" mechanism and forms a unique means to alleviate the data imbalance *** conducted experiments using ICU-STAY patients' data from the MIMIC-Ⅲ database and compared them with the mainstream EMR time series processing *** results show that the method extracts visible and comprehensive features,alleviates data imbalance problems and improves the accuracy in specific predicting tasks.

关键词： Databases Time series analysis MIMICs Manuals Big Data Feature extraction Transformers

Simulation study on the security of consensus algorithms in DAG-based distributed ledger

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Frontiers of Computer Science 2024年第3期18卷 171-182页

作者： Shuzhe LI Hongwei XU Qiong LI Qi HAN Faculty of computing Harbin Institute of TechnologyHarbin 150001China

Due to the advantages of high volume of transactions and low resource consumption,Directed Acyclic Graph(DAG)-based Distributed Ledger Technology(DLT)has been considered a possible next-generation alternative to ***,the security of the DAG-based system has yet to be comprehensively *** at verifying and evaluating the security of DAG-based DLT,we develop a Multi-Agent based IOTA Simulation platform called *** MAIOTASim,we model honest and malicious nodes and simulate the configurable network environment,including network topology and *** double-spending attack is a particular security issue related to *** perform the security verification of the consensus algorithms under multiple double-spending attack *** simulations show that the consensus algorithms can resist the parasite chain attack and partially resist the splitting attack,but they are ineffective under the large weight *** take the cumulative weight difference of transactions as the evaluation criterion and analyze the effect of different consensus algorithms with parameters under each attack ***,MAIOTASim enables users to perform largescale simulations with multiple nodes and tens of thousands of transactions more efficiently than state-of-the-art ones.

关键词： distributed ledger IOTA Multi-Agent system simulation

TULAM:trajectory-user linking via attention mechanism

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Science China(Information Sciences) 2024年第1期67卷 51-68页

作者： Hao LI Shuyu CAO Yaqing CHEN Min ZHANG Dengguo FENG Trusted computing and Information Assurance Laboratory Institute of SoftwareChinese Academy of Sciences university of Chinese Academy of Sciences

Recently,the application of location-based services(LBS) has become a prevalent means to provide convenience in customers’ everyday ***,because massive volumes of location information are collected by LBS applications,users may suffer from serious privacy *** studies have shown that the identities of users can be inferred from historical anonymous trajectories,which is formulated as the trajectory-user linking(TUL) *** some recurrent neural network(RNN)-based models have been proposed to capture implicit movement patterns among trajectories to improve TUL performance,they cannot learn the sequential and contextual semantics within any individual trajectory completely,leaving the advantages of RNNs *** therefore propose an RNN model with an attention mechanism called TULAM to improve the accuracy of the TUL *** learns sequential relationships within individual trajectories via RNN and captures contextual semantics from trajectories via a multi-head attention ***,we propose a novel location encoding method called approximate one-hot to solve the corpus shortage problem of trajectory *** were conducted on real datasets from the Gowalla and Foursquare LBS *** experimental results indicate that TULAM is a practical solution that achieves significant improvements over existing methods with satisfactory model complexity and convergence.

关键词： information security data security and privacy trajectory-user linking deep learning recurrent neural network attention mechanism

A Systematic Literature Review of Machine Learning and Deep Learning Approaches for Spectral Image Classification in Agricultural Applications Using Aerial Photography

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Computers, Materials & Continua 2024年第3期78卷 2967-3000页

作者： Usman Khan Muhammad Khalid Khan Muhammad Ayub Latif Muhammad Naveed Muhammad Mansoor Alam Salman A.Khan Mazliham Mohd Su’ud College of computing and Information Sciences Karachi Institute of Economics and TechnologyKarachi75190Pakistan Faculty of computing and Informatics(FCI) Multimedia UniversityCyberjaya63100Malaysia Faculty of computing Riphah International UniversityIslamabad46000Pakistan Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneySydneyAustralia

Recently,there has been a notable surge of interest in scientific research regarding spectral *** potential of these images to revolutionize the digital photography industry,like aerial photography through Unmanned Aerial Vehicles(UAVs),has captured considerable *** encouraging aspect is their combination with machine learning and deep learning algorithms,which have demonstrated remarkable outcomes in image *** a result of this powerful amalgamation,the adoption of spectral images has experienced exponential growth across various domains,with agriculture being one of the prominent *** paper presents an extensive survey encompassing multispectral and hyperspectral images,focusing on their applications for classification challenges in diverse agricultural areas,including plants,grains,fruits,and *** meticulously examining primary studies,we delve into the specific agricultural domains where multispectral and hyperspectral images have found practical ***,our attention is directed towards utilizing machine learning techniques for effectively classifying hyperspectral images within the agricultural *** findings of our investigation reveal that deep learning and support vector machines have emerged as widely employed methods for hyperspectral image classification in ***,we also shed light on the various issues and limitations of working with spectral *** comprehensive analysis aims to provide valuable insights into the current state of spectral imaging in agriculture and its potential for future advancements.

关键词： Machine learning deep learning unmanned aerial vehicles multi-spectral images image recognition object detection hyperspectral images aerial photography

A Parallel Discrete Event Simulation Engine for the Low-Earth-Orbit Satellite Constellation Networks

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China Communications 2024年第8期21卷 264-275页

作者： Su Hailong Liu Yaoqi Zhou Yiqing Shi Jinglin Li Hongguang Qian Manli institute of computing Technology Chinese Academy of SciencesBeijing 100190China university of Chinese Academy of Sciences Beijing 100049China State Key Lab of Processors Institute of Computing TechnologyCASBeijing 100190China Zhongke Nanjing Mobile Communication&computing Innovation institute Nanjing 211135China Beijing Sylincom Technology Co. Beijing 100190China

Low-Earth-Orbit satellite constellation networks(LEO-SCN)can provide low-cost,largescale,flexible coverage wireless communication *** dynamics and large topological sizes characterize *** development and application testing of LEO-SCN are challenging to carry out in a natural *** platforms are a more effective means of technology *** available simulators have a single function and limited simulation *** needs to be a simulator for full-featured *** this paper,we apply the parallel discrete-event simulation technique to the simulation of LEO-SCN to support large-scale complex system simulation at the packet *** solve the problem that single-process programs cannot cope with complex simulations containing numerous entities,we propose a parallel mechanism and algorithms LP-NM and LP-YAWNS for *** the experiment,we use ns-3 to verify the acceleration ratio and efficiency of the above *** results show that our proposed mechanism can provide parallel simulation engine support for the LEO-SCN.

关键词： constellation low earth orbit satellite ns-3 null-message parallel discrete-event simulation

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Multipass Streaming Algorithms for Regularized Submodular Maximization

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Tsinghua Science and Technology 2024年第1期29卷 76-85页

作者： Qinqin Gong Suixiang Gao Fengmin Wang Ruiqi Yang Beijing institute for Scientific and Engineering computing Beijing University of TechnologyBeijing 100124.China School of Mathematical Sciences University of Chinese Academy SciencesBeijing 100049China Beijing Jinghang Research institute of computing and Communication Beijing 100074China

In this work,we study a k-Cardinality Constrained Regularized Submodular Maximization(k-CCRSM)problem,in which the objective utility is expressed as the difference between a non-negative submodular and a modular *** multiplicative approximation algorithm exists for the regularized model,and most works have focused on designing weak approximation algorithms for this *** this study,we consider the k-CCRSM problem in a streaming fashion,wherein the elements are assumed to be visited individually and cannot be entirely stored in *** propose two multipass streaming algorithms with theoretical guarantees for the above problem,wherein submodular terms are monotonic and nonmonotonic.

关键词： submodular optimization regularized model streaming algorithms threshold

Partially-hiding functional encryption for degree-2 polynomials with fine-grained access control

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Frontiers of Computer Science 2024年第3期18卷 231-233页

作者： Haifeng QIAN Cheng LIN Qiaohan CHU Jie CHEN Shanghai Key Laboratory of Trustworthy computing Software Engineering InstituteEast China Normal UniversityShanghai 200062China

1 Introduction Boneh et al.[1]first systematically introduce the concept of Functional Encryption(FE)which overcomes all-or-nothing limitation of traditional public key ***,FE hides a potential problem:even if the secret key is obtained legitimately,once it is released,it can be used *** leads to that the secret key may leak information *** deal with this problem and make FE more practical,Abdalla et al.[2]recently constructed inner-product FE(IPFE)with fine-grained access control achieving strong security guarantees under standard assumptions.

关键词： grain Encryption encryption