检索结果-南通市图书馆

维普期刊数据库

FADSF:A Data Sharing Model for Intelligent Connected Vehicles Based on Blockchain Technology

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第8期80卷 2351-2362页

作者： Yan Sun Caiyun Liu Jun Li Yitong Liu Data security institute China Industrial Control Systems Cyber Emergency Response TeamBeijing100040China

With the development of technology,the connected vehicle has been upgraded from a traditional transport vehicle to an information terminal and energy storage *** data of ICV(intelligent connected vehicles)is the key to organically maximizing their ***,in the context of increasingly strict global data security supervision and compliance,numerous problems,including complex types of connected vehicle data,poor data collaboration between the IT(information technology)domain and OT(operation technology)domain,different data format standards,lack of shared trust sources,difficulty in ensuring the quality of shared data,lack of data control rights,as well as difficulty in defining data ownership,make vehicle data sharing face a lot of problems,and data islands are *** study proposes FADSF(Fuzzy Anonymous Data Share Frame),an automobile data sharing scheme based on *** data holder publishes the shared data information and forms the corresponding label storage on the *** data demander browses the data directory information to select and purchase data assets and verify *** data demander selects and purchases data assets and verifies them by browsing the data directory ***,this paper designs a data structure Data Discrimination Bloom Filter(DDBF),making complaints about illegal *** the number of data complaints reaches the threshold,the audit traceability contract is triggered to punish the illegal data publisher,aiming to improve the data quality and maintain a good data sharing *** this paper,based on Ethereum,the above scheme is tested to demonstrate its feasibility,efficiency and security.

关键词： Blockchain connected vehicles data sharing smart contracts credible traceability

XA-GANomaly: An Explainable Adaptive Semi-Supervised Learning Method for Intrusion Detection Using GANomaly

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2023年第7期76卷 221-237页

作者： Yuna Han Hangbae Chang Department of security Convergence Graduate SchoolChung-Ang UniversitySeoul06974Korea Department of industrial security Chung-Ang UniversitySeoul06974Korea

Intrusion detection involves identifying unauthorized network activity and recognizing whether the data constitute an abnormal network *** research has focused on using semi-supervised learning mechanisms to identify abnormal network traffic to deal with labeled and unlabeled data in the ***,real-time training and classifying network traffic pose challenges,as they can lead to the degradation of the overall dataset and difficulties preventing ***,existing semi-supervised learning research might need to analyze the experimental results *** paper proposes XA-GANomaly,a novel technique for explainable adaptive semi-supervised learning using GANomaly,an image anomalous detection model that dynamically trains small subsets to these ***,this research introduces a deep neural network(DNN)-based GANomaly for semi-supervised ***,this paper presents the proposed adaptive algorithm for the DNN-based GANomaly,which is validated with four subsets of the adaptive ***,this study demonstrates a monitoring system that incorporates three explainable techniques—Shapley additive explanations,reconstruction error visualization,and t-distributed stochastic neighbor embedding—to respond effectively to attacks on traffic data at each feature engineering stage,semi-supervised learning,and adaptive *** to other single-class classification techniques,the proposed DNN-based GANomaly achieves higher scores for Network security Laboratory-Knowledge Discovery in Databases and UNSW-NB15 datasets at 13%and 8%of F1 scores and 4.17%and 11.51%for accuracy,***,experiments of the proposed adaptive learning reveal mostly improved results over the initial *** analysis and monitoring system based on the combination of the three explainable methodologies is also ***,the proposed method has the potential advantages to be applied in practical industry,and future r

关键词： Intrusion detection system(IDS) adaptive learning semi-supervised learning explainable artificial intelligence(XAI) monitoring system

Blockchain Technology Based Information Classification Management Service

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第5期67卷 1489-1501页

作者： Gi-Wan Hong Jeong-Wook Kim Hangbae Chang Department of security Convergence Graduate SchoolChung-Ang UniversitySeoul06974Korea Department of industrial security Chung-Ang UniversitySeoul06974Korea

Hyper-connectivity in Industry 4.0 has resulted in not only a rapid increase in the amount of information,but also the expansion of areas and assets to be *** terms of information security,it has led to an enormous economic cost due to the various and numerous security solutions used in protecting the increased ***,it has caused difficulties in managing those issues due to reasons such as mutual interference,countless security events and logs’data,*** this security environment,an organization should identify and classify assets based on the value of data and their security perspective,and then apply appropriate protection measures according to the assets’security classification for effective security *** there are still difficulties stemming from the need to manage numerous security solutions in order to protect the classified *** this paper,we propose an information classification management service based on blockchain,which presents and uses a model of the value of data and the security *** records transactions of classifying assets and managing assets by each class in a distributed ledger of *** proposed service reduces assets to be protected and security solutions to be applied,and provides security measures at the platform level rather than individual security solutions,by using *** the rapidly changing security environment of Industry 4.0,this proposed service enables economic security,provides a new integrated security platform,and demonstrates service value.

关键词： Information classification data integrity document security blockchain CIA

Experimental study and Shannon entropy analysis of pressure fluctuations and flow mode transition in fluidized dense phase pneumatic conveying of fly ash

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Particuology 2020年第2期18卷 169-178页

作者： Yassin Alkassar Vijay KAgarwal RKPandey Niranjana Behera industrial Tribology Machine Dynamic and Maintenance Engineering CentreIndian Institute of Technology DelhiNew Delhi 110016India Department of Mechanical Engineering Indian Institute of Technology DelhiNew Delhi 110016India School of Mechanical Engineering Vellore Institute of Technology UniversityVellore 632014India

The objective of this study was to relate experimental pressure fluctuation behavior to the transition in mode of flow observed in fluidized dense phase pneumatic conveying of fly *** entropy and wavelet analysis were utilized to extract features of the flow *** db4 wavelet analysis of pulsating air pressure revealed that the flow mechanism of fly ash in a fluidized dense phase possessed non-steady characteristics associated with gradual aeration of dunes along the direction of *** of Shannon entropy values along the length of the pipeline were assessed to determine the location at which the flow converted from dense to dilute phase *** effects of conveying parameters and specific power consumption on Shannon entropy and variations of the local power consumption coefficient are discussed.

关键词： Fluidized dense phase Mode transition Wavelet Shannon entropy

New health-state assessment model based on belief rule base with interpretability

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2021年第7期64卷 209-223页

作者： Zhijie ZHOU You CAO Guanyu HU Youmin ZHANG Shuaiwen TANG Yuan CHEN High-Tech institute of Xi'an Department of Information and Control Engineering Xi'an University of Technology School of Computer Science and Information security Guilin University of Electronic Technology Department of Mechanical Industrial and Aerospace Engineering Concordia University

Health-state assessment is the foundation of optimal-maintenance decision-making for complex systems to maintain reliability and safety. Generating the assessment results in a convincing and interpretable way to avoid potential risks is of great importance. Belief rule base(BRB) as an interpretable model performs well in health-state assessment. However, the interpretability of a BRB-based model may be lost during the optimization process, which is expressed mainly as three problems: expert knowledge is not effectively used in the optimization process; the optimized rules of BRB may be in conflict with real systems; and some parameters get over-optimized, which may affect experts’ initial judgment. Three concepts — "searching intensity", "interpretability constraint of belief distribution", and "rule-activation factor" — are defined to address these problems. Using these concepts, we propose a new health-state assessment model based on the interpretable BRB and a new optimization method to improve the accuracy and preserve the interpretability of the new model. To demonstrate the effectiveness of the proposed model, we conducted an aero-engine case study.

关键词： health-state assessment belief rule base interpretability complex systems

A Stacking-Based Deep Neural Network Approach for Effective Network Anomaly Detection

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第2期66卷 2217-2227页

作者： Lewis Nkenyereye Bayu Adhi Tama Sunghoon Lim Department of Computer and Information security Sejong UniversitySeoul05006Korea Data Science Group Institute for Basic Science(IBS)Daejeon34126Korea Department of industrial Engineering Ulsan National Institute of Science and TechnologyUlsan44919Korea

An anomaly-based intrusion detection system(A-IDS)provides a critical aspect in a modern computing infrastructure since new types of attacks can be *** prevalently utilizes several machine learning algorithms(ML)for detecting and classifying network *** date,lots of algorithms have been proposed to improve the detection performance of A-IDS,either using individual or ensemble *** particular,ensemble learners have shown remarkable performance over individual learners in many applications,including in cybersecurity ***,most existing works still suffer from unsatisfactory results due to improper ensemble *** aim of this study is to emphasize the effectiveness of stacking ensemble-based model for A-IDS,where deep learning(e.g.,deep neural network[DNN])is used as base learner *** effectiveness of the proposed model and base DNN model are benchmarked empirically in terms of several performance metrics,i.e.,Matthew’s correlation coefficient,accuracy,and false alarm *** results indicate that the proposed model is superior to the base DNN model as well as other existing ML algorithms found in the literature.

关键词： Anomaly detection deep neural network intrusion detection system stacking ensemble

Construction of even-variable rotation symmetric Boolean functions with maximum algebraic immunity

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2013年第3期56卷 60-68页

作者： FU ShaoJing LI Chao MATSUURA Kanta QU LongJiang Department of Mathematics and System Science National University of Defense Technology institute of industrial Science University of TokyoTokyo 153-8505Japan State Key Laboratory of Information security Graduate University of Chinese Academy of Sciences

Rotation symmetric Boolean functions(RSBFs) have been used as components of different *** this paper,we investigate n-variable(n even and n≥12) RSBFs to achieve maximum algebraic immunity(AI),and provide a construction of RSBFs with maximum AI and *** functions have higher nonlinearity than the previously known nonlinearity of RSBFs with maximum *** also prove that our construction provides high algebraic degree in some case.

关键词： Boolean function rotation symmetry algebraic immunity nonlinearity

Assessment of the Contribution of Road Traffic to Greenhouse Emissions: A Case of an Algerian City

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Environmental Protection 2014年第13期5卷 1364-1372页

作者： Aouragh Leila Bourmada Noureddine LRNAT Laboratory Institute of Hygiene and Industrial Security University of Batna Batna Algeria LARPI Laboratory Institute of Hygiene and Industrial Security University of Batna Batna Algeria

Rapid urbanisation brings about increase in air pollution. These emissions are generally linked to the production of energy, to industrial activities and to transport in the densely inhabited areas. Estimating the pollutants quantities released in the air is an important stage in the evaluation of air quality. However, the problem of air pollution in urban areas is a problem in all Algerian cities. Similar to all Algerian big cities, the city of Batna has become a major urban area with an ever increasing fleet of motor vehicles most of which are practically old ones. This state of affairs increases the demand in fuel consumption and undeniably intensifies polluting emissions. As the situation goes, it has become the utmost urgency to wonder about a possible support that may be given to this sector in order to evaluate how air quality is managed in a durable way. The main objective of this study is to assess the quantity of CO2 pollutant known as the most significant greenhouse gas emission from traffic. The approach used is mainly based on a number of assumptions, which allows us to find the amount of 192 g/km/day CO2 released into the urban atmosphere of the city of Batna.

关键词： Air Pollution Road Transport Greenhouse Gas Emission Factors Impact

Heuristics for the Identical Machine Scheduling Problem with Preventive maintenances

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Shanghai Jiaotong university(Science) 2016年第1期21卷 112-120页

作者：江才林陆志强崔维伟 institute of industrial Engineering Tongji University Department of industrial Engineering and Logistics Management Shanghai Jiaotong University

In this paper, two mixed integer programming models integrating production scheduling and preventive maintenances are proposed to derive the optimal solutions for the identical machine scheduling problem with unavailability constraints. In the first model, the maintenance activities are performed periodically and the objective is to minimize the makespan. In the second model, the maintenance activities are flexible and the machines' continuous working time cannot exceed a maximum allowed time T; the objective is to minimize the total completion time of jobs. For the first problem, we propose a heuristic longest batch time(LBT) and prove that the worst case error bound of LBT is 2. For the second problem, we develop a heuristic modified smallest processing time(MSPT) based on some properties of the optimal solutions. Computational experiments show that both of the heuristics are effective and efficient compared with the results obtained by CPLEX and the other algorithms.

关键词： identical machine scheduling unavailability constraints heuristic

维普期刊数据库