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A New Approach of TPM Construction Based on J2810

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Wuhan University Journal of Natural Sciences 2007年第1期12卷 21-24页

作者： ZHAO Bo ZHANG Huanguo HUANG Rui School of computer Wuhan University Wuhan 430072Hubei China

Trusted platform model （TPM） is special-purpose integrated circuits （ICs） built into a variety of platforms to enable strong user authentication and machine attestation-essential to prevent inappropriate access to confidential and sensitive information and to protect against compromised networks. Existing TPM products have some limitations. This paper adopts J2810TPM Single Chip cryptogram MCU produced by Jetway company to construct typical TPM after comparing existing TPM products. Finally, an improved construction approach of TPM based on J2810 is proposed.

关键词： trusted platform model(TPM) trusted computing J2810

Security Monitoring and Management for the Network Services in the Orchestration of SDN-NFV Environment Using Machine Learning Techniques

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computer systems Science & Engineering 2024年第2期48卷 363-394页

作者： Nasser Alshammari Shumaila Shahzadi Saad Awadh Alanazi Shahid Naseem Muhammad Anwar Madallah Alruwaili Muhammad Rizwan Abid Omar Alruwaili Ahmed Alsayat Fahad Ahmad Department of computer Science College of Computer and Information SciencesJouf UniversitySakakaAl Jouf72341Saudi Arabia Department of computer Sciences Kinnaird College forWomenLahorePunjab54700Pakistan Department of Information Sciences Division of Sciences and TechnologyUniversity of EducationLahore54770Pakistan Department of computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakaka72341Saudi Arabia computer Science Florida Polytechnic UniversityLakelandFlorida33805USA Delta3T LahorePunjab54700Pakistan Department of Basic Sciences Common First YearJouf UniversitySakaka72341Saudi Arabia

Software Defined Network(SDN)and Network Function Virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified network lifecycle,and policies *** vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration(NFV MANO),and malicious attacks in different scenarios disrupt the NFV Orchestrator(NFVO)and Virtualized Infrastructure Manager(VIM)lifecycle management related to network services or individual Virtualized Network Function(VNF).This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order to enhance the quality of experience for end *** anomaly detector investigates these identified risks and provides secure network *** enables virtual network security functions and identifies anomalies in Kubernetes(a cloud-based platform).For training and testing purpose of the proposed approach,an intrusion-containing dataset is used that hold multiple malicious activities like a Smurf,Neptune,Teardrop,Pod,Land,IPsweep,etc.,categorized as Probing(Prob),Denial of Service(DoS),User to Root(U2R),and Remote to User(R2L)*** anomaly detector is anticipated with the capabilities of a Machine Learning(ML)technique,making use of supervised learning techniques like Logistic Regression(LR),Support Vector Machine(SVM),Random Forest(RF),Naïve Bayes(NB),and Extreme Gradient Boosting(XGBoost).The proposed framework has been evaluated by deploying the identified ML algorithm on a Jupyter notebook in Kubeflow to simulate Kubernetes for validation *** classifier has shown better outcomes(99.90%accuracy)than other classifiers in detecting anomalies/intrusions in the containerized environment.

关键词： Software defined network network function virtualization network function virtualization management and orchestration virtual infrastructure manager virtual network function Kubernetes Kubectl artificial intelligence machine learning

Automated knowledge graphs for complex systems (AutoGraCS): Applications to management of bridge networks

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Resilient Cities and Structures 2024年第4期3卷 95-106页

作者： Minghui Cheng Syed M.H.Shah Antonio Nanni H.Oliver Gao Department of Civil&Architectural Engineering University of MiamiCoral GablesFL 33146USA School of Architecture University of MiamiCoral GablesFL 33126USA Department of computer Science University of MiamiCoral GablesFL 33146USA systems Engineering Cornell UniversityIthacaNY 14853USA School of Civil and Environmental Engineering Cornell UniversityIthacaNY 14853USA

With the ability to harness the power of big data,the digital twin(DT)technology has been increasingly applied to the modeling and management of structures and infrastructure systems,such as buildings,bridges,and power distribution *** these applications,an important family of methods are based on *** DT applications in modeling and managing smart cities,large-scale knowledge graphs(KGs)are necessary to represent the complex interdependencies and model the urban infrastructure as a system of *** this end,this paper develops a conceptual framework:Automated knowledge Graphs for Complex systems(AutoGraCS).In contrast to existing KGs developed for DTs,AutoGraCS can support KGs to account for interdependencies and statistical correlations across complex *** established KGs from AutoGraCS can then be easily turned into Bayesian networks for probabilistic modeling,Bayesian analysis,and adaptive decision ***,AutoGraCS provides flexibility in support of users’need to implement the ontology and rules when constructing the *** the user-defined ontology and rules,AutoGraCS can automatically generate a KG to represent a complex system consisting of multiple *** bridge network in Miami-Dade County,FL is used as an illustrative example to generate a KG that integrates multiple layers of data from the bridge network,traffic monitoring facilities,and flood water watch stations.

关键词： System digital twin Bayesian network Infrastructure systems Knowledge Graph

Bayesian Deep Learning Enabled Sentiment Analysis on Web Intelligence Applications

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computers, Materials & Continua 2023年第5期75卷 3399-3412页

作者： Abeer D.Algarni Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

In recent times,web intelligence(WI)has become a hot research topic,which utilizes Artificial Intelligence(AI)and advanced information technologies on theWeb and *** users post reviews on social media and are employed for sentiment analysis(SA),which acts as feedback to business people and *** SA on the reviews helps to enhance the quality of the services and products,however,web intelligence techniques are needed to raise the company profit and user *** this motivation,this article introduces a new modified pigeon inspired optimization based feature selection(MPIO-FS)with Bayesian deep learning(BDL),named MPIOBDL model for SA on WI *** presented MPIO-BDL model initially involved preprocessing and feature extraction take place using Term Frequency—Inverse Document Frequency(TF-IDF)technique to derive a useful set of information from the user ***,the MPIO-FS model is applied for the selection of optimal feature subsets,which helps to enhance classification accuracy and reduce computation ***,the BDL model is employed to allocate the proper class labels of the applied user review data.A comprehensive experimental results analysis highlighted the improved classification efficiency of the presented model.

关键词： Social media data classification Bayesian deep learning artificial intelligence web intelligence feature selection

Blockchain and Machine Learning for Intelligent Multiple Factor-Based Ride-Hailing Services

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computers, Materials & Continua 2022年第3期70卷 4429-4446页

作者： Zeinab Shahbazi Yung-Cheol Byun IIST Department of Computer EngineeringJeju National UniversityJeju-siJeju Special Self-Governing Province63243Kore

One of the common transportation systems in Korea is calling taxis through online applications,which is more convenient for passengers and drivers in the modern ***,the driver’s passenger taxi request can be rejected based on the driver’s location and ***,there is a need to specify driver’s acceptance and rejection of the received *** security of this systemis anothermain core to save the transaction information and safety of passengers and *** this study,the origin and destination of the Jeju island SouthKorea were captured from T-map and processed based on machine learning decision tree and XGBoost *** blockchain framework is implemented in the Hyperledger Fabric *** experimental results represent the features of *** cross-validation was *** is another factor for the taxi trip,which in total trip in midnight is quite *** process presents the successful matching of ride-hailing taxi services with the specialty of distance,the trip request,and safety based on the total city measurement.

关键词： Taxi trip blockchain machine learning ride-hailing prediction trip distance

Progressive events in supervisory control and compositional verification

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Control Theory and Technology 2014年第3期12卷 317-329页

作者： Simon Ware Robi Malik School of Electronic and Electrical Engineering Nanyang Technological UniversitySingapore Department of computer Science University of WaikatoHamilton New Zealand

This paper investigates some limitations of the nonblocking property when used for supervisor synthesis in discrete event systems. It is shown that there are cases where synthesis with the nonblocking property gives undesired results. To address such cases, the paper introduces progressive events as a means to specify more precisely how a synthesised supervisor should complete its tasks. The nonblocking property is modified to take progressive events into account, and appropriate methods for verification and synthesis are proposed. Experiments show that progressive events can be used in the analysis of industrial-scale systems, and can expose issues that remain undetected by standard nonblocking verification.

关键词： Model validation in design methods Controller constraints and structure Computational issues

Joint On-Demand Pruning and Online Distillation in Automatic Speech Recognition Language Model Optimization

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computers, Materials & Continua 2023年第12期77卷 2833-2856页

作者： Soonshin Seo Ji-Hwan Kim Clova Speech Naver CorporationSeongnam13561Korea Department of computer Science and Engineering Sogang UniversitySeoul04107Korea

Automatic speech recognition(ASR)systems have emerged as indispensable tools across a wide spectrum of applications,ranging from transcription services to voice-activated *** enhance the performance of these systems,it is important to deploy efficient models capable of adapting to diverse deployment *** recent years,on-demand pruning methods have obtained significant attention within the ASR domain due to their adaptability in various deployment ***,these methods often confront substantial trade-offs,particularly in terms of unstable accuracy when reducing the model *** address challenges,this study introduces two crucial empirical ***,it proposes the incorporation of an online distillation mechanism during on-demand pruning training,which holds the promise of maintaining more consistent accuracy ***,it proposes the utilization of the Mogrifier long short-term memory(LSTM)language model(LM),an advanced iteration of the conventional LSTM LM,as an effective alternative for pruning targets within the ASR *** rigorous experimentation on the ASR system,employing the Mogrifier LSTM LM and training it using the suggested joint on-demand pruning and online distillation method,this study provides compelling *** results exhibit that the proposed methods significantly outperform a benchmark model trained solely with on-demand pruning ***,the proposed strategic configuration successfully reduces the parameter count by approximately 39%,all the while minimizing trade-offs.

关键词： Automatic speech recognition neural language model Mogrifier long short-term memory pruning distillation efficient deployment optimization joint training

A Survey on Graph Processing Accelerators:Challenges and Opportunities

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Journal of computer Science & Technology 2019年第2期34卷 339-371页

作者： Chuang-Yi Gui Long Zheng Bingsheng He Cheng Liu Xin-Yu Chen Xiao-Fei Liao Hai Jin National Engineering Research Center for Big Data Technology and System School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China Services Computing Technology and System Laboratory School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China Cluster and Grid Computing Laboratory School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China School of Computing National University of Singapore Singapore 117418 Singapore Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

Graph is a well known data structure to represent the associated relationships in a variety of applications,e.g.,data science and machine *** a wealth of existing efforts on developing graph processing systems for improving the performance and/or energy efficiency on traditional architectures,dedicated hardware solutions,also referred to as graph processing accelerators,are essential and emerging to provide the benefits significantly beyond what those pure software solutions can *** this paper,we conduct a systematical survey regarding the design and implementation of graph processing ***,we review the relevant techniques in three core components toward a graph processing accelerator:preprocessing,parallel graph computation,and runtime *** also examine the benchmarks and results in existing studies for evaluating a graph processing ***,we find that there is not an absolute winner for all three aspects in graph acceleration due to the diverse characteristics of graph processing and the complexity of hardware *** finally present and discuss several challenges in details,and further explore the opportunities for the future research.

关键词： graph processing accelerator domain-specific architecture performance energy efficiency

Wireless Sensor Security Issues on Data Link Layer:A Survey

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computers, Materials & Continua 2023年第5期75卷 4065-4084页

作者： Muhammad Zulkifl Hasan Zurina Mohd Hanapi Muhammad Zunnurain Hussain Department of Communication Technology and Network Faculty of Computer Science and Information TechnologyUniversiti Putra MalaysiaSerdangSelangor43400Malaysia

A computer network can be defined as many computing devices connected via a communication medium like the *** network development has proposed how humans and devices communicate *** networks have improved,facilitated,and made conventional forms of communication ***,it has also led to uptick in-network threats and *** 2022,the global market for information technology is expected to reach$170.4 ***,in contrast,95%of cyber security threats globally are caused by human *** networks may be utilized in several control systems,such as home-automation,chemical and physical assault detection,intrusion detection,and environmental *** proposed literature review presents a wide range of information on Wireless Social Networks(WSNs)and Internet of Things(IoT)*** aim is first to be aware of the existing issues(issues with traditional methods)and network attacks on WSN and IoT systems and how to defend *** second is to review the novel work in the domain and find its *** goal is to identify the area’s primary gray field or current research divide to enable others to address the ***,we concluded that *** Rapid Spanning Tree Protocol(RSTP)messages have higher efficiency in network performance degradation than alternative Bridge Data Unit Protocol(BPDU)*** research divides our future research into solutions and newly developed techniques that can assist in completing the lacking *** this research,we have selected articles from 2015 to 2021 to provide users with a comprehensive literature overview.

关键词： Wireless sensor networks(WSN) internet of things(IoT) industrial revolution 4.0(IR4.0) computer networks network security