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Efficient cache replacement framework based on access hotness for spacecraft processors

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中国空间科学技术（中英文） 2024年第2期44卷 74-88页

作者： GAO Xin NIAN Jiawei LIU Hongjin YANG Mengfei Beijing Institute of co.trol Engineering Beijing 100190China Beijing SunWise space technology co. Ltd.Beijing 100190China School of co.puter science and technology Xidian UniversityXi'an 710071China China Academy of space technology Beijing 100094China

A notable portion of cachelines in real-world workloads exhibits inner non-uniform access behaviors.However,modern cache management rarely co.siders this fine-grained feature,which impacts the effective cache capacity of co.temporary high-performance spacecraft processors.To harness these non-uniform access behaviors,an efficient cache replacement framework featuring an auxiliary cache specifically designed to retain evicted hot data was proposed.This framework reco.structs the cache replacement policy,facilitating data migration between the main cache and the auxiliary cache.Unlike traditional cacheline-granularity policies,the approach excels at identifying and evicting infrequently used data,thereby optimizing cache utilization.The evaluation shows impressive performance improvement,especially on workloads with irregular access patterns.Benefiting from fine granularity,the proposal achieves superior storage efficiency co.pared with co.monly used cache management schemes,providing a potential optimization opportunity for modern resource-co.strained processors,such as spacecraft processors.Furthermore,the framework co.plements existing modern cache replacement policies and can be seamlessly integrated with minimal modifications,enhancing their overall efficacy.

关键词： spacecraft processors cache management replacement policy storage efficiency memory hierarchy microarchitecture

NFHP-RN:AMethod of Few-Shot Network Attack Detection Based on the Network Flow Holographic Picture-ResNet

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co.puter Modeling in Engineering & sciences 2024年第7期140卷 929-955页

作者： Tao Yi Xingshu Chen Mingdong Yang Qindong Li Yi Zhu School of cyber science and Engineering Sichuan UniversityChengdu610065China cyberscience Research Institute Sichuan UniversityChengdu610065China Chengdu Fengwei technology co. Ltd.Chengdu610041China

Due to the rapid evolution of Advanced Persistent Threats(APTs)attacks,the emergence of new and rare attack samples,and even those never seen before,make it challenging for traditional rule-based detection methods to extract universal rules for effective detection.With the progress in techniques such as transfer learning and meta-learning,few-shot network attack detection has progressed.However,challenges in few-shot network attack detection arise from the inability of time sequence flow features to adapt to the fixed length input requirement of deep learning,difficulties in capturing rich information from original flow in the case of insufficient samples,and the challenge of high-level abstract representation.To address these challenges,a few-shot network attack detection based on NFHP(Network Flow Holographic Picture)-RN(ResNet)is proposed.Specifically,leveraging inherent properties of images such as translation invariance,rotation invariance,scale invariance,and illumination invariance,network attack traffic features and co.textual relationships are intuitively represented in NFHP.In addition,an improved RN network model is employed for high-level abstract feature extraction,ensuring that the extracted high-level abstract features maintain the detailed characteristics of the original traffic behavior,regardless of changes in background traffic.Finally,a meta-learning model based on the self-attention mechanism is co.structed,achieving the detection of novel APT few-shot network attacks through the empirical generalization of high-level abstract feature representations of known-class network attack behaviors.Experimental results demonstrate that the proposed method can learn high-level abstract features of network attacks across different traffic detail granularities.co.paredwith state-of-the-artmethods,it achieves favorable accuracy,precision,recall,and F1 sco.es for the identification of unknown-class network attacks through cross-validation onmultiple datasets.

关键词： APT attacks spatial pyramid pooling NFHP(network flow holo-graphic picture) ResNet self-attention mechanism meta-learning

Fast fixed-time three-dimensional terminal guidance with non-co.cave trajectory co.straint

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Chinese Journal of Aeronautics 2024年第3期37卷 208-218页

作者： Youmin GONG Yanning GUO Yueyong LYU Dongyu LI Guangfu MA Department of co.trol science and Engineering Harbin Institute of TechnologyHarbin 150001China School of cyber science and technology Beihang UniversityBeijing 100191China

Focusing on the non-co.cave trajectory co.straint,a sliding-mode-based nonsingular feedback fast fixed-time three-dimensional terminal guidance of rotor unmanned aerial vehicle landing,planetary landing and spacecraft rendezvous and docking terminal phase with external disturbance is investigated in this paper.Firstly,a fixed-time observer based on real-time differentiator is developed to co.pensate for the external disturbance,whose estimation error can co.verge to zero after a time independent of the initial state.Then,a sliding surface ensuring fixed-time co.vergence is presented.This sliding surface can guarantee that the vehicle achieves a non-co.cave trajectory,which is better for avoiding co.lision and maintaining the visibility of the landing site or docking port.Next,the nonsingular guidance ensuring the fixed-time co.vergence of the sliding surface is proposed,which is co.tinuous and chatter free.At last,three numerical simulations of Mars landing are performed to validate the effectiveness and co.rectness of the designed scheme.

关键词： Three-dimensional Terminal guidance Non-co.cave trajectory co.straint Fast fixed-time co.trol Sliding mode co.trol

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A Trust Evaluation Mechanism Based on Autoenco.er Clustering Algorithm for Edge Device Access of IoT

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co.puters, Materials & co.tinua 2024年第2期78卷 1881-1895页

作者： Xiao Feng Zheng Yuan cyber Security Academy Beijing University of Posts and TelecommunicationsBeijing100876China Department of cyberspace Security Beijing Electronic Science and Technology InstituteBeijing100070China State Grid Info-Teleco. Great Power science and technology co. Ltd.Beijing102211China

First,we propose a cross-domain authentication architecture based on trust evaluation mechanism,including registration,certificate issuance,and cross-domain authentication processes.A direct trust evaluation mechanism based on the time decay factor is proposed,taking into acco.nt the influence of historical interaction reco.ds.We weight the time attenuation factor to each historical interaction reco.d for updating and got the new historical reco.d data.We refer to the beta distribution to enhance the flexibility and adaptability of the direct trust assessment model to better capture time trends in the historical reco.d.Then we propose an autoenco.er-based trust clustering algorithm.We perform feature extraction based on autoenco.ers.Kullback leibler(KL)divergence is used to calculate the reco.struction error.When co.structing a co.volutional autoenco.er,we introduce co.volutional neural networks to improve training efficiency and introduce sparse co.straints into the hidden layer of the autoenco.er.The sparse penalty term in the loss function measures the difference through the KL divergence.Trust clustering is performed based on the density based spatial clustering of applications with noise(DBSCAN)clustering algorithm.During the clustering process,edge nodes have a variety of trustworthy attribute characteristics.We assign different attribute weights acco.ding to the relative importance of each attribute in the clustering process,and a larger weight means that the attribute occupies a greater weight in the calculation of distance.Finally,we introduced adaptive weights to calculate co.prehensive trust evaluation.Simulation experiments prove that our trust evaluation mechanism has excellent reliability and accuracy.

关键词： Cross-domain authentication trust evaluation autoenco.er

IHVFL: a privacy-enhanced intention-hiding vertical federated learning framework for medical data

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cybersecurity 2024年第2期7卷 96-112页

作者： Fei Tang Shikai Liang Guowei Ling Jinyong Shan co.lege of co.puter science and technology Chongqing University of Posts and TelecommunicationsNo.2Chongwen RoadNan'an DistrictChongqing 400065China School of cyber Security and Information Law Chongqing University of Posts and TelecommunicationsChongqing 400065China sudo technology co. LTD.Beijing 100083China

Vertical Federated Learning(VFL)has many applications in the field of smart healthcare with excellent performance.However,current VFL systems usually primarily focus on the privacy protection during model training,while the preparation of training data receives little attention.In real-world applications,like smart healthcare,the process of the training data preparation may involve some participant's intention which co.ld be privacy information for this partici-pant.To protect the privacy of the model training intention,we describe the idea of Intention-Hiding Vertical Feder-ated Learning(IHVFL)and illustrate a framework to achieve this privacy-preserving goal.First,we co.struct two secure screening protoco.s to enhance the privacy protection in feature engineering.Seco.d,we implement the work of sample alignment bases on a novel private set intersection protoco..Finally,we use the logistic regression algorithm to demonstrate the process of IHVFL.Experiments show that our model can perform better efficiency(less than 5min)and accuracy(97%)on Breast Cancer medical dataset while maintaining the intention-hiding goal.

关键词： Medical data Vertical federated learning Privacy-presserving Intention-hiding Logistic regression

Sandwich-type co.posited solid polymer electrolytes to strengthen the interfacial ionic transportation and bulk co.ductivity for all-solid-state lithium batteries from room temperature to 120 °C

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Journal of Energy Chemistry 2024年第8期95卷 288-295页

作者： Jiewen Tan Zhen Wang Jiawu Cui Zhanhui Jia Wensheng Tian Chao Wu Chengxin Peng Chengyong Shu Kang Yang Wei Tang School of Chemical Engineering and technology Xi'an Jiaotong University Center for Advancing Materials Performance from the Nanoscale(CAMP-Nano) State Key Laboratory for Mechanical Behavior of Materials Xi'an Jiaotong University State Key Laboratory of space Power-sources technology Shanghai Institute of Space Power-Sources School of Materials science and Engineering University of Shanghai for Science and Technology Top-Energy Digital Manufacturing Technologies(Xi'an) co. Ltd.

The insurmountable charge transfer impedance at the Li metal/solid polymer electrolytes（SPEs） interface at room temperature as well as the ascending risk of short circuits at the operating temperature higher than the melting point,dominantly limits their applications in solid-state batteries（SSBs）.Although the inorganic filler such as CeO2nanoparticle co.tent of co.posite solid polymer electrolytes（CSPEs） can significantly reduce the enormous charge transfer impedance at the Li metal/SPEs interface,we found that the required co.tent of CeO2nanoparticles in SPEs varies for achieving a decent interfacial charge transfer impedance and the bulk ionic co.ductivity in CSPEs.In this regard,a sandwich-type co.posited solid polymer electrolyte with a 10% CeO2CSPEs interlayer sandwiched between two 50% CeO2CSPEs thin layers（sandwiched CSPEs） is co.structed to simultaneously achieve low charge transfer impedance and superior ionic co.ductivity at 30℃.The sandwiched CSPEs allow for stable cycling of Li plating and stripping for 1000 h with 129 mV polarized voltage at 0.1 mA cm-2and 30℃.In addition,the LiFePO4/Sandwiched CSPEs/Li cell also exhibits exceptional cycle performance at 30℃ and even elevated120℃ without short circuits.co.structing multi-layered CSPEs with optimized co.tents of the inorganic fillers can be an efficient method for developing all solid-state PEO-based batteries with high performance at a wide range of temperatures.

关键词： All-solid-state Li metal batteries CeO2 nanoparticles Charge transfer impedance PEO-based solid electrolytes Sandwich-type co.posite electrolytes

Properties and microstructure of co.per–titanium alloys with magnesium additions

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Rare Metals 2024年第5期43卷 2290-2299页

作者： Lue Huang Li-Jun Peng Jiang Li Xu-Jun Mi Gang Zhao Guo-Jie Huang Hao-Feng Xie Yi-Cheng Cao Wen-Jing Zhang Zhen Yang State Key Laboratory of Nonferrous Metals and Processes GRINM Group Co. Ltd. GRIMAT Engineering Institute co. Ltd. School of Materials science and Engineering Northeastern University General Research Institute for Nonferrous Metals China Academy of space technology China Nonferrous Metals Mining Group (Tianjin) co.Ltd

The volume fractions and morphology of precipitates in precipitation-strengthened Cu-Ti alloys,which precipitate mainly as co.tinuous and disco.tinuous precipitates,are important for the application of the alloy.This study employed hardness and electrical co.ductivity tests transmission electron microsco.y （TEM）,atom probe tomography （APT）,and first-principles calculations to demonstrate that the addition of Mg is effective for accelerating nanosized co.tinuous β'-Cu4Ti precipitation as well as for suppressing the precipitation of co.rse lamellar disco.tinuous β-Cu4Ti precipitates along the grain boundaries,resulting in Cu-Ti alloys with high yield strength and good electrical co.ductivity.The results showed that the co.tinuous precipitation of β'-Cu4Ti was accelerated by the Mg additions,which reduced the supersaturation of the matrix,thereby reducing the chemical driving force for the disco.tinuous precipitates.On the other hand,Mg additions increased the mismatch between the disco.tinuous β-Cu4Ti precipitates and matrix decreased the nucleation rate of the disco.tinuous precipitates,and increased the spacing of the disco.tinuous precipitation layer,resulting in a lower growth rate of the disco.tinuous precipitates.Therefore,the addition of Mg to Cu-Ti alloys enhances the strength and improves the resistance to over-ageing.

关键词： Cu-Ti-Mg alloy Precipitation hardening Disco.tinuous precipitation co.tinuous precipitation Microstructure formation mechanism

MCWOA Scheduler:Modified Chimp-Whale Optimization Algorithm for Task Scheduling in Cloud co.puting

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co.puters, Materials & co.tinua 2024年第2期78卷 2593-2616页

作者： Chirag Chandrashekar Pradeep Krishnadoss Vijayakumar Kedalu Poornachary Balasundaram Ananthakrishnan School of co.puter science and Engineering Vellore Institute of TechnologyChennai600127India Center for cyber Physical Systems School of Computer Science and EngineeringVellore Institute of TechnologyChennai600127India

Cloud co.puting provides a diverse and adaptable resource pool over the internet,allowing users to tap into various resources as needed.It has been seen as a robust solution to relevant challenges.A significant delay can hamper the performance of IoT-enabled cloud platforms.However,efficient task scheduling can lower the cloud infrastructure’s energy co.sumption,thus maximizing the service provider’s revenue by decreasing user job processing times.The proposed Modified Chimp-Whale Optimization Algorithm called Modified Chimp-Whale Optimization Algorithm(MCWOA),co.bines elements of the Chimp Optimization Algorithm(co.)and the Whale Optimization Algorithm(WOA).To enhance MCWOA’s identification precision,the Sobol sequence is used in the population initialization phase,ensuring an even distribution of the population across the solution space.Moreover,the traditional MCWOA’s local search capabilities are augmented by inco.porating the whale optimization algorithm’s bubble-net hunting and random search mechanisms into MCWOA’s position-updating process.This study demonstrates the effectiveness of the proposed approach using a two-story rigid frame and a simply supported beam model.Simulated outco.es reveal that the new method outperforms the original MCWOA,especially in multi-damage detection scenarios.MCWOA excels in avoiding false positives and enhancing co.putational speed,making it an optimal choice for structural damage detection.The efficiency of the proposed MCWOA is assessed against metrics such as energy usage,co.putational expense,task duration,and delay.The simulated data indicates that the new MCWOA outpaces other methods across all metrics.The study also references the Whale Optimization Algorithm(WOA),Chimp Algorithm(CA),Ant Lion Optimizer(ALO),Genetic Algorithm(GA)and Grey Wolf Optimizer(GWO).

关键词： Cloud co.puting scheduling chimp optimization algorithm whale optimization algorithm

Deep Learning and Tensor-Based Multiple Clustering Approaches for cyber-Physical-Social Applications

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co.puters, Materials & co.tinua 2024年第3期78卷 4109-4128页

作者： Hongjun Zhang Hao Zhang Yu Lei Hao Ye Peng Li Desheng Shi School of co.puter science Nanjing University of Posts and TelecommunicationsNanjing210023China China co.munications Services co. Ltd.Beijing100071China China co.munications Services Hexin science&technology co. Ltd.Hefei230031China

The study delves into the expanding role of network platforms in our daily lives, enco.passing various mediums like blogs, forums, online chats, and prominent social media platforms such as Facebook, Twitter, and Instagram. While these platforms offer avenues for self-expression and co.munity support, they co.currently harbor negative impacts, fostering antisocial behaviors like phishing, impersonation, hate speech, cyberbullying, cyberstalking, cyberterrorism, fake news propagation, spamming, and fraud. Notably, individuals also leverage these platforms to co.nect with authorities and seek aid during disasters. The overarching objective of this research is to address the dual nature of network platforms by proposing innovative methodologies aimed at enhancing their positive aspects and mitigating their negative repercussions. To achieve this, the study introduces a weight learning method grounded in multi-linear attribute ranking. This approach serves to evaluate the significance of attribute co.binations across all feature spaces. Additionally, a novel clustering method based on tensors is proposed to elevate the quality of clustering while effectively distinguishing selected features. The methodology inco.porates a weighted average similarity matrix and optionally integrates weighted Euclidean distance, co.tributing to a more nuanced understanding of attribute importance. The analysis of the proposed methods yields significant findings. The weight learning method proves instrumental in discerning the importance of attribute co.binations, shedding light on key aspects within feature spaces. Simultaneously, the clustering method based on tensors exhibits improved efficacy in enhancing clustering quality and feature distinction. This not only advances our understanding of attribute importance but also paves the way for more nuanced data analysis methodologies. In co.clusion, this research undersco.es the pivotal role of network platforms in co.temporary society, emphasizing their potential for both positive co.tr

关键词： Network platform tensor-based clustering weight learning multi-linear euclidean