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检索条件"任意字段=2023 International Conference on Computer Network Security and Software Engineering, CNSSE 2023"

共 6804 条记录，以下是151-160 订阅

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Algae Object Detection Algorithm Based on Improved YOLOv5 6

Algae Object Detection Algorithm Based on Improved YOLOv5

引用

6th international conference on software engineering and computer Science, CSECS 2023

作者： Lin, Ke Tang, Yang Tang, Jianheng Huang, Huiqing Qin, Zhisong School of Computer and Information Security Guilin University of Electronic Technology Guilin China

ISBN: (纸本)9798350306378

Algae are sensitive to changes in water quality, and the substances produced by algae also have a direct impact on the aquatic environment, so the detection and analysis of algae can provide important information on changes in water quality. In this paper, we propose an improved deep learning network for algae object detection, YOLO-MultiAlgae, which is capable of fast object detection of algae images. The method uses GhostNet as the backbone network and employs the SimAM attention mechanism to improve the detection accuracy. Experiments on the detection of eight species of algae show that the proposed network has higher labeling speed and accuracy compared to other classical object detection networks, with the detection accuracy reaching up to 98.8%, as well as better results in comparison experiments with two lightweight networks, shuffleNetV2 and MobileNetV3. Algae detection can be performed faster and better with this network. © 2023 IEEE.

关键词： Object detection

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security Evaluation in software-Defined networks 12th

Security Evaluation in Software-Defined Networks

引用

13th international conference on Cloud Computing and Services Science (CLOSER)

作者： Ivkic, Igor Thiede, Dominik Race, Nicholas Broadbent, Matthew Gouglidis, Antonios Univ Lancaster Lancaster England Univ Appl Sci Burgenland Eisenstadt Austria Edinburgh Napier Univ Edinburgh Midlothian Scotland

ISBN: (纸本)9783031681646;9783031681653

Cloud computing has grown in importance in recent years which has led to a significant increase in Data Centre (DC) network requirements. A major driver of this change is virtualisation, which allows computing resources to be deployed on a large scale. However, traditional DCs, with their network topology and proliferation of network endpoints, are struggling to meet the flexible, centrally managed requirements of cloud computing applications. software-Defined networks (SDN) promise to offer a solution to these growing networking requirements by separating control functions from data routing. This shift adds more flexibility to networks but also introduces new security issues. This article presents a framework for evaluating security of SDN architectures. In addition, through an experimental study, we demonstrate how this framework can identify the threats and vulnerabilities, calculate their risks and severity, and provide the necessary measures to mitigate them. The proposed framework helps administrators to evaluate SDN security, address identified threats and meet network security requirements.

关键词： software-defined networks security evaluation framework Threat analysis Risk assessment Attack modelling Threat mitigation

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network security, trust & privacy in a wiredwireless Environments-An Overview 1

Network security, trust & privacy in a wiredwireless Environ...

引用

1st international conference on Computational Intelligence, Communication Technology and networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Bhatla, Shruti Gautam, Devendra Ai and Robotics Institute Research Center for Ai and IoT Near East University Nicosia Department of Computer Engineering Mersin10 Turkey Ai and Robotics Institute Near East University Artificial Intelligence Engineering Dept. Mersin Nicosia10 Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Mersin10 Turkey Graphic Era Hill University Department of Computer Science and Engineering Dehradun India Abes Engineering College Ghaziabad India

ISBN: (纸本)9798350338027

In this report, we explore the key challenges and threats facing network security in wired and wireless environments, as well as the technologies and best practices for addressing these challenges. We provide an overview of the key concepts and terminology related to network security, trust, and privacy, and discuss the role of encryption in maintaining trust and privacy in these environments. We also examine common attack vectors and countermeasures and offer some recommendations for best practices in the realm of network security. © 2023 IEEE.

关键词： network security

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Evaluation of the Effectiveness Mitigation of Distributed Denial of Service in software-Defined networking Using the Nearest Centroid Classification 6

Evaluation of the Effectiveness Mitigation of Distributed De...

引用

6th international conference on computer and Informatics engineering, IC2IE 2023

作者： Grananta, Rahma Syndu Data, Mahendra Basuki, Achmad Brawijaya University Faculty of Computer Science Malang Indonesia

ISBN: (纸本)9798350345162

software-defined networking (SDN) is a modern approach in computer networking where the control plane and data plane layers are decoupled. The advantage of this separation is that it allows computer networks to be programmed dynamically and facilitates network management. SDN uses the OpenFlow Protocol (OFP), developed by the Open networking Foundation, to manage the communication between the control and data planes. Like other networks, OFP-based networks pose similar security challenges, such as a Distributed Denial of Service (DDoS) attack. These challenges affect the controller, data plane, and network users in the SDN network. Therefore, an OFP-based network requires a mechanism to identify network traffic. This study implements and evaluates security mechanisms on OFP networks using the Intrusion Detection System (IDS) application running on the SDN controller that leverages traffic flow classification. The machine learning approach is employed to categorize data flows, after which the detected DDoS (Distributed Denial of Service) flows are blocked and obstructed within the data-plane flow table. In classifying the DDoS traffic flow, three extracted features were used based on flow entries arrival, source of IP address changes, and the ratio of pair-flow entries. The experiments were conducted using generated DDoS and normal traffic with exciting results. We centered the experiments using the Nearest Centroid classification method compared to several classification methods. The result shows an accuracy of 85.48% and an F1-Score value of 0.87 on the Nearest Centroid classification. The implemented IDS application on the Ryu-based SDN controller shows the effectiveness of DDoS detection and successful mitigation by being blocked in the data plane. © 2023 IEEE.

关键词： DDoS nearest centroid openflow software-defined networking

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Automatic summarization of medical conversations based on episodic memory network hierarchical labels

Automatic summarization of medical conversations based on ep...

引用

2022 international conference on computer network security and software engineering, cnsse 2022

作者： Zheng, Peng Liu, Yongbin Wu, Lin University of South China Hunan Hengyang421000 China

ISBN: (纸本)9781510655980

Summarizations to the patients' problems and the doctors' treatments in the medical conversations can be highly useful, in terms of helping other patients with similar problems have a precise reference for potential medical solutions. The patient's first question in the medical conversation often contains critical information that determines the diagnosis. The previous simple weight division for the role of dialogue determines that doctors and patients' discourses do not affect each other, which makes it incomplete for the model to obtain the important discourses in the dialogue. Therefore, it is proposed to use episodic memory network to enhance the influence of the patient's first sentence on the model's acquisition of important words, and re-divide the sentence role weight according to the first sentence vector. The experiment proves that using episodic memory network can be more sensitive to the information between utterances, acquire important utterances more accurately, and generate high-quality abstracts. © 2022 SPIE.

关键词： Diagnosis

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computer network information security monitoring system 2

Computer network information security monitoring system

引用

2nd international conference on Big Data, Computational Intelligence, and Applications, BDCIA 2024

作者： Lin, Hongkai Wuhan Business University Hubei Wuhan430056 China

ISBN: (纸本)9781510689053

Although traditional protection methods can improve the security of the network to a certain extent, its effect is often limited in the face of complex network environment and various attacks. Therefore, it is an important problem to be solved in the field of communication network security to find a more efficient and intelligent communication network link data security protection method. This paper proposes a computer network information security monitoring system combined with knowledge mapping technology, which aims to improve the data security protection effect of computer communication network. this paper designs and implements an information security situation awareness system, which can find and deal with network security threats in time by monitoring and analyzing network data traffic and security event information in real time, and improves the efficiency and level of information security protection. The results show that the information security situational awareness system based on artificial intelligence technology has high detection accuracy and strong real-time response capability, and can effectively deal with various network security threats. It has a good application prospect in data security protection of communication network link. © 2025 SPIE.

关键词： network security Data communications computer security Defense and security Information security Data modeling Machine learning computer networks Evolutionary algorithms Education and training

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Based on WOA-BP neural network power the behavior detection

Based on WOA-BP neural network power the behavior detection

引用

2023 international conference on computer Application and Information security, ICCAIS 2023

作者： Kong, Lingji Wang, Xinmeng Li, Haiqi Zhao, Chengnan Tian, Junqiang State Grid Shandong Electric Power Company Heze Power Supply Company Shandong Heze274000 China

ISBN: (纸本)9781510675032

In view of the current situation that the phenomenon of power pilferage is common and the difficulty of anti-theft, a BP (Back Propagation) neural network steal detection method optimized by whale algorithm is proposed. This method detects the power theft behavior through the power trend decline index, line missing index, and problem index, and optimizes it with the whale algorithm since BP neural network algorithm to raise its accuracy. The experimental results show that the whale algorithm capable of optimizing the BP neural network well. Among them, the MAE and MSE were reduced by 0.02, and the RMSE error was reduced from 0.215 to 0.16. Therefore, the model can detect the theft behavior well, which provides a certain reference value for the research of anti-theft. © 2024 SPIE.

关键词： Crime

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CBAM-DnCNN: An Improved Method For Image Denoising 3

CBAM-DnCNN: An Improved Method For Image Denoising

引用

3rd international conference on Electronic Information engineering and computer Science, EIECS 2023

作者： Cai, Guofeng Sichuan University School of Software Engineering Chengdu China

ISBN: (纸本)9798350316674

In modern society, with the wide application of digital images in the fields of social media, medical diagnosis, security monitoring, and automatic driving, the quality of images has become particularly critical for information transfer and decision-making. With the continuous development of artificial intelligence and computer vision, Image denoising techniques are gradually applied to improve image quality. In this paper, an Image denoising method based on a modified DnCNN network (CBAM-DnCNN) is proposed. Our method first convolves the noisy image to extract features, then captures the spatial structure of the image through the Convolutional Block Attention Module, and then feeds it to this DnCNN network for residual learning. In addition, the combination of BCEWithLogitsLoss and MSELoss is used as a loss function during training and the introduction of these methods can improve the quality of the results. This work provides a new method for image noise reduction and proves the effectiveness of the method in experiments. © 2023 IEEE.

关键词： Attention mechanism component DnCNN Image denoising Residual learning

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A Review of Methods to Prevent DDOS Attacks Using NFV and SDN 9

A Review of Methods to Prevent DDOS Attacks Using NFV and SD...

引用

9th international conference on Web Research, ICWR 2023

作者： Shayegan, Mohammad Javad Damghanian, Amirreza University of Science and Culture Department of Computer Engineering Tehran Iran

ISBN: (纸本)9798350399691

Denial-of-service attacks are always one of the most widespread security attacks at the enterprise network level. In DDOS attacks, a large amount of false demand is intentionally sent to the target network to disable the service. In DDoS attacks, the target server faces many demands, not from a specific source, but from different locations of the attack, which makes detection and defense more difficult. With the introduction of network functions virtualization and software-defined networking , a new route, for network design and management, has been created. The purpose of this research is to investigate and compare DDoS attack defense methods using NFV and SDN. The details provided will help researchers in this field familiarize themselves with DDoS attack defense methods and choose the appropriate design for their actual implementations.. © 2023 IEEE.

关键词： network security

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Role of DDoS in Smart Grid networks

Role of DDoS in Smart Grid Networks

引用

2023 international conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Pandey, Vijay Kumar Singh, Yaduvir Manivasagam Vivekananda Global University Department of Mechanical Engineering Jaipur India Uttar Pradesh Greater Noida India Computer Science Engineering Department Bangalore India

ISBN: (纸本)9798350357769

This paper tackles the essential problem of distributed denial- of-service (DDoS) assaults on smart grid networks (SG) and presents a novel approach based on network software defined (SDN). The rising energy needs of web-connected devices underline the need for efficient and trustworthy solutions. The development of smart grids enables a two-way interaction inside power networks, giving flexibility and scalability. However, increased complexity also brings up technical obstacles, notably in the field of security. Current security solutions fail to deal with the convoluted and linked structure of smart grids, putting them susceptible to DDoS assaults. In the setting of SGs servicing millions of customers and playing a critical role in delivering important services, any gap in its components may have rapid and far-reaching implications. DDoS assaults offer a substantial hazard, with the ability to interrupt energy production infrastructure. The report underscores the inadequacy of present safety protocols and underlines the critical need for innovative alternatives. © 2023 IEEE.

关键词： Anomaly Detection Entropy network security Smart Grids software-Defined networking

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