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A Novel Routing Protocol for Hierarchical Software Defined Vehicular Adhoc Network 9

A Novel Routing Protocol for Hierarchical Software Defined V...

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9th international conference on computing for Sustainable Global Development, INDIACom 2022

作者： Kumar, Manish Raw, Ram Shringar Ggsipu New Delhi India Bharati Vidyapeeth's Institute of Computer Applications and Management New Delhi India Netaji Subhas University of Technology Delhi India

ISBN: (纸本)9789380544441

the nodes of a Vehicular Adhoc Network (VANET), are highly mobile in nature. Hence, it is very challenging to disseminate the message to the nodes with high reliability. the scalability and heterogeneity of these networks are also quite challenging to handle. this manuscript proposes a Hybrid Hierarchical Software-Defined VANET (SD-VANET) with Multiple Network Interface protocol with two interfaces. the SDN provides the scalability and heterogeneity feature and the second interface is used to reduce the inference and maximize the network utilization. We analyze the proposed routing protocol on parameters like link reliability, Packet Delivery Ratio and End to End Delay to assess its effectiveness over existing counterparts. © 2022 Bharati Vidyapeeth, New Delhi.

关键词： Software defined networking

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A Novel Approach for Federated Learning with Non-IID Data 9

A Novel Approach for Federated Learning with Non-IID Data

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9th international conference on Soft computing and Machine Intelligence (ISCMI)

作者： Nguyen, Hiep Warrier, Harikrishna Gupta, Yogesh HCL Technol Hanoi Vietnam HCL Technol Hyderabad Telangana India

ISBN: (纸本)9798350320886

Federated learning (FL) is an emerging technique used to collaboratively train a global machine learning model while keeping the data localized on the user devices. the main obstacle to FL's practical implementation is the Non-Independent and Identical (Non-IID) data distribution across users, which slows convergence and degrades performance. To tackle this fundamental issue, we propose a method (called ComFed) that enhances the whole training process on both the client and server sides. the key idea of ComFed is to simultaneously utilize clientvariance reduction techniques to facilitate server aggregation and global adaptive update techniques to accelerate learning. Our experiments show that ComFed can improve state-of-theart algorithms dedicated to Non-IID data.

关键词： Federated learning Machine learning distributed learning Deep learning Decentralized machine learning

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Enhancing Resilience against DDoS Attacks in SDN -based Supply Chain Networks Using Machine Learning 9

Enhancing Resilience against DDoS Attacks in SDN -based Supp...

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9th international conference on Control, Decision and Information Technologies, CoDIT 2023

作者： Sebbar, Anass Zkik, Karim International University of Rabat Esin TICLab Rabat Morocco Esaip Ecole d'Ingenieur Cerade Angers France

ISBN: (纸本)9798350311402

distributed Denial of Service (DDoS) attacks are becoming increasingly common and sophisticated, and supply chain networks are particularly vulnerable to these types of attacks due to their reliance on interconnected systems. Software-Defined networking (SDN) has the potential to enhance resilience against DDoS attacks by providing a centralized control mechanism and the ability to reroute traffic dynamically. However, traditional methods for detecting and mitigating DDoS attacks in SDN-based networks may not be sufficient to protect against these threats fully. In this paper, we propose the use of machine learning techniques to detect and mitigate DDoS attacks in SDN-based supply chain networks. We will investigate how the centralized control mechanism of SDN can be leveraged to improve the effectiveness of machine learning-based DDoS attack detection and mitigation. Additionally, we evaluated these techniques' performance and effectiveness and discussed the trade-offs and limitations of using machine learning for DDoS attack detection and mitigation in SDN-based supply chain networks. © 2023 IEEE.

关键词： Supply chains

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9th international conference on Mobility, IoT and Smart Cities, EAI Mobility IoT 2022

9th International Conference on Mobility, IoT and Smart Citi...

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9th international conference on Mobility, IoT and Smart Cities, EAI Mobility IoT 2022

ISBN: (纸本)9783031282249

the proceedings contain 12 papers. the special focus in this conference is on Mobility, IoT and Smart Cities. the topics include: A New Trend in Car Personalization Based on Augmented Reality: A Study;Management and Maintenance of Buildings in BIM Environment: Facility Management of Historic Buildings (HBIM);collaboration of an Established Company with Startups: A Funnel-Shaped Framework;digital Well-Being and Satisfaction of University Students with Online Education;digitization, Personalization, and Automation of Business Processes;smart Solutions for an Improved Experience in the Process of Buying Slovak Products;construction and Experimental Testing of Innovative Wireless Emission Monitoring System in Small Household of Smart City;optimizing the Resource’s Mobility, Transportation, and networking in the Project Construction Industry, Using a Fractal Method;smart Approaches by Online Monitoring in Transportation;possibilities and Challenges for the Sustainable Development of Air Transport.

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Incentive-based task matching with evolving preferences in distributed fog computing: A trust-aware approach 9

Incentive-based task matching with evolving preferences in d...

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9th international conference on Computer and Communications, ICCC 2023

作者： Yan, Lei Zhang, Zaigui Sun, Bin Wang, Yonghai Inspur Group Company Limited Shandong Jinan250102 China Data Technology Co. Ltd Henan Zhengzhou450047 China

Fog computing has been a promising technology for the computation-intensive Apps with the resource pool adjacent to the mobile users. In which, users9; workloads or management can be offloaded to servers with a des... 详细信息

ISBN: (纸本)9798350317251

Fog computing has been a promising technology for the computation-intensive Apps with the resource pool adjacent to the mobile users. In which, users' workloads or management can be offloaded to servers with a designed matching scheme. However, the selfish servers are reluctant to share their resources cooperatively. An efficient incentive scheme is desirable for the edge networks, especially for the decentralized fog networks. In addition, existing works mainly assume that the preferences of users and servers are static or fixed, and it is not practical for the fog networks with dynamicity caused by many uncertainties. In this paper, a trust-aware incentive scheme for task matching with evolving preferences in decentralized fog computing is proposed. We first formulate a long-term trust management scheme for the network considering the participants' behaviors, such as, service qualities and payment behavior, etc. then, the evolving preferences of both users and fog nodes are derived with their variable trust levels, and a trust-aware task matching algorithm is proposed. Finally, a trust-aware incentive scheme is designed to encourage users and fog nodes to behave positively during the offloading interaction. the simulation results demonstrate that our proposed trust-aware fog computing scheme is more efficient than existing methods regarding energy cost and delay. © 2023 IEEE.

关键词： Fog computing

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ML based Web Application Firewall for Signature and Anomaly Detection Using Feature Extraction 15

ML based Web Application Firewall for Signature and Anomaly ...

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15th international conference on computing Communication and networking Technologies, ICCCNT 2024

作者： Dhote, Sanjana Magdum, Aditya Singh, Siddharth Raigar, Dipika Pune Institute of Computer Technology Department of Computer Engineering Pune India

In today9;s digital landscape, web applications have become indispensable tools for businesses, facilitating access to vital data and services. However, this ubiquity also exposes them to a myriad of cyber threats,... 详细信息

ISBN: (纸本)9798350370249

In today's digital landscape, web applications have become indispensable tools for businesses, facilitating access to vital data and services. However, this ubiquity also exposes them to a myriad of cyber threats, ranging from SQL injection to cross-site scripting. Traditional Web Application Firewalls (WAFs), while essential, often struggle with rule-based detection methods, leading to issues like false positives and an inability to adapt swiftly to emerging threats. this paper introduces an advanced Web Application Firewall (WAF) fortified with Machine Learning (ML) techniques, specifically a Random Forest classifier. the proposed WAF achieved nearly 1 0 0% accuracy in classifying requests as normal or anomalous and 8 9. 5% accuracy in distinguishing between different attack types. Furthermore, it significantly reduces computational time compared to traditional WAFs. By harnessing ML, the proposed WAF enhances web application security, effectively identifying and mitigating attacks while minimizing false positives, showcasing a practical ML-driven solution for safeguarding online assets against evolving cyber threats. © 2024 IEEE.

关键词： Anomaly detection Cross-Site Scripting (XSS) Cybersecurity Deep Learning (DL) distributed Denial of Service (DDoS) False negatives False positives Machine Learning (ML) Rule-based detection mechanisms Signature-based filtering Structured Query Language (SQL) injection Web Application Firewall (WAF) Web Application Security

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Resource Trading Incentive Mechanism Based on Stackelberg Game and Auction theory in computing Power Network 9

Resource Trading Incentive Mechanism Based on Stackelberg Ga...

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9th international conference on Computer and Communications, ICCC 2023

作者： Li, Yinan Xie, Renchao Tang, Qinqin Huang, Tao Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing China Purple Mountain Laboratories Nanjing China

ISBN: (纸本)9798350317251

computing power network (CPN) is a new architecture proposed in recent years. It has integrated multidimensional resources, such as computing, network and storage resources in cloud, edge and end to realize more flexible resource allocation and task scheduling. Consumers in CPN want to purchase some resources to meet their service demands and gain some profits, while operators would like to obtain payments by selling their idle resources to others. However, consumers usually prefer to purchase resources from large and public cloud operators in reality, while small and private operators who lack the recognition struggle to obtain the opportunity to join in the sales. therefore, both parties may lack the passion and enthusiasm to participate in CPN transaction and there is a great need for a resource trading incentive mechanism. In this paper, we propose a three-tier joint optimization framework to increase their motivations and establish a centralized computing service platform (CSP). We use the Stackelberg game to describe the resource-purchasing process of computing service demanders (CSDs) and use the auction theory to describe the task-scheduling process of computing service operators (CSOs). In this way, both parties can gain their profits so that they will have a greater willingness to participate in the transaction. the simulation results demonstrate the feasibility and superiority of our scheme. © 2023 IEEE.

关键词： Computer games

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Blockchain Over Named Data networking Architecture: A Review 9th

Blockchain Over Named Data Networking Architecture: A Review

引用

9th international conference on computing and Informatics, ICOCI 2023

作者： Alsamman, Mohammed Hassan, Suhaidi Mohammed, Fathey Fazea, Yousef School of Computing Universiti Utara Malaysia Sintok Kedah Bukit Kayu Hitam06010 Malaysia Sunway Business School Sunway University Selangor Subang Jaya47500 Malaysia Computer and Information Technology Marshall University 1 John Marshall Drive HuntingtonWV25755 United States

ISBN: (纸本)9789819995882

With infinite apps and online services, future Internet architecture will face new challenges and consequences, such as scalability, dependability, suitable mobility, and security. Internet use has changed spectacularly from one-way communication to content distribution, as much content is generated every minute. Blockchain and Named Data networking (NDN) are two cutting-edge technologies on the verge of revolutionizing how we use the Internet. Blockchain is a decentralized ledger technology allowing users to store and share data securely. On the other hand, NDN is a new way of networking that focuses on content instead of location. Combining blockchain and NDN can create a safer, more efficient, and more decentralized internet. Blockchain can provide tamper-proof data records, and NDN can deliver content to users efficiently and securely. this paper emphasizes the importance of research in the field of blockchain over Named Data networks. It highlights the advantages of combining blockchain with NDN and discusses the difficulties and open research questions related to the use of blockchain over NDN. Also, the potential impact of blockchain over NDN on the future of the Internet as it can create a safer, more efficient, and more decentralized Internet. © 2024, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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indexPDT: A High Scalable distributed Classification Approach with Novel Cache Structure for Geo-location 25

indexPDT: A High Scalable Distributed Classification Approac...

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25th IEEE international conferences on High Performance computing and Communications, 9th international conference on Data Science and Systems, 21st IEEE international conference on Smart City and 9th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Sun, Zhijie Li, Jing Xie, Jun Zheng, Binfan Zeng, Li Zhao, Rongqian Huawei Technologies Co. Ltd. Shenzhen China

ISBN: (纸本)9798350330014

Geo-location, also known as measurement report (MR) location, is a technique to determine the geographic location of user equipment (UE) and the behaviour attribute of telephone traffic based on wireless signals measured by the mobile communication network. the geographic location information can help to support network performance monitoring and evaluation. Considering accuracy and cost, we mainly adopt a hybrid location scheme combined with feature matching location and Weighted Centroid Correction Location (WCCL). As for feature matching location, over 20 billion samples gathered from tens of thousands of cells daily updated. Due to the vast data scale, feature analysis encounters a severe performance bottleneck. To address this problem, we design the indexed parallel decision tree (indexPDT) operator and integrate it into WindTensor, a self-innovated distributed machine learning (ML) engine. indexPDT is a classifier unit of the random forest (RF) algorithm with a novel cache structure. It performs structured cache processing on the dataset's meta-information, which can accompany the splitting of nodes. the cache structure can be quickly converted into statistical information to help find the optimal splitting point, effectively reducing memory usage and improving performance. Under the public datasets testing on 5 nodes, the mean speedup ratios are 86x and 3x compared with SparkML and XGBoost, respectively. In the Geo-location scenario, for a single cell, the speedup ratios are 82x and 4x compared with SparkML and XG Boost, respectively. © 2023 IEEE.

关键词： Location

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Research on Large-scale Model System Management Technology for Joint Operations 9

Research on Large-scale Model System Management Technology f...

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9th international conference on Big Data and Information Analytics, BigDIA 2023

作者： Li, Zhenya Zhu, Yong Jiang, Kai Liu, Shanyi Zhang, Yiming Zhang, Daowei Zhang, Yan Li, Zhimeng National University of Defense Technology ChangSha China Nanjing Research Institute of Electronic Engineering ChangSha China Nanjing Research Institute of Electronic Engineering NanJing China

ISBN: (纸本)9798350330076

the paper focuses on the computational power requirements with domain-crossing models and distributed collaborative combat command systems under a joint combat environment, and developed a massive combat model system management mode and a technical framework for joint and domain multi-dimensional operations, covering support for the entire lifecycle of the model;aiming at the key requirements such as how to distribute and flexibly schedule the use of massive models in multiple domains across domains, and how to organize and apply intelligent models for changing combat scenarios, innovatively propose technology methods such as intelligent scheduling of models for multi-centers and domain knowledge based model combination application engine;based on the above key capabilities and technology exploration, the application of intelligent and actuarial capabilities in information warfare and the closure of the OODA loop can be accelerated, providing the support of critical base capability for the improvement of comprehensive computing power in command and decision-making in joint operations. © 2023 IEEE.

关键词： computing power

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