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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111-120 订阅

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Research on a lightweight real-time anomaly traffic detection method

Research on a lightweight real-time anomaly traffic detectio...

引用

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

作者： Geng, Haijun Ren, Min Wang, Qingsheng Liang, Shuanglong Zhou, Manlan School of Automation and Software Engineering Shanxi University Shanxi Taiyuan030006 China Shanxi Qingzhong Technology Co. Ltd. Shanxi Taiyuan030000 China School of Safety and Emergency Management Shanxi Vocational University of Engineering Science and Technology Shanxi Jinzhong China

ISBN: (纸本)9781510675032

Anomalous traffic detection in the network is one of the essential components of network security protection. Neural networks are widely used in intrusion detection systems, which can learn the ability to distinguish between regular and attack traffic in the network through training. However, most of the existing methods do unimodal anomaly detection on temporal features. Based on this, our paper proposes a hybrid anomaly detection model based on Auto-Encoder, which uses Damped Incremental Statistics to extract features from the data to obtain Time-domain features, then uses Discrete Wavelet Transform to obtain Frequency-domain features of corresponding dimensions using two sets of Auto-Encoders to generate the RMSE in two modules and weighted sum to get the final RMSE value. The anomaly detection problem is transformed into a refactoring problem of the time series in two spaces. The classification algorithm compares the anomaly with the threshold value, thus determining whether it is an attacking traffic. The experimental results in UNSW-NB15, IDS2017, and IDS2018 datasets show that the method in paper is better than the traditional unimodal anomaly detection method, which improves 8.11% and 7.31% in Precision and Recall, respectively, and the Precision can be up to 99.99%, which proves the validity of the method in our paper. © 2024 SPIE.

关键词： Time series

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security challenges of IoT with its applications and architecture

Security challenges of IoT with its applications and archite...

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international conference on Artificial Intelligence, Blockchain, Computing and security, ICABCS 2023

作者： Bathla, Neha Kaur, Amanpreet Department of Computer Science and Engineering Chitkara University Institute of Engineering & Technology Chitkara University Punjab India

ISBN: (纸本)9781032669663

IoT (Internet of Things) is the network of physical objects("things") in which embedded devices are used like sensors and software that are used for connecting the devices and objects over the internet. Currently, seven billion connected IoT devices today, by 2025 experts is expecting this number to grow to twenty-two billion. In this article we provide an introduction or overview of the IoT (Internet of Things), IoT architecture and functionality of each layer, its applications and security issues. The IoT are enabled by the newest developments in smart sensors and RFID. The basic principle of IoT is that it has smart sensors that work together directly without human participation to deliver the new applications. In the upcoming years, with the intelligent decision making IoT expected as bridge diverse technologies to enable new applications by connecting physical objects together. In this survey we also describe the importance of security and its challenges. © 2024, CRC Press/Balkema. All rights reserved.

关键词： Internet of things

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Survivability Model of networks using Attack Graphs and Markov Chains 47

Survivability Model of Networks using Attack Graphs and Mark...

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47th IEEE-computer-Society Annual international conference on computers, software, and Applications (COMPSAC)

作者： Bardhan, Shuvo Georgetown Univ Sch Continuing Studies Cybersecur Risk Management Program Georgetown Guyana

ISBN: (纸本)9798350326970

The most difficult task that a networks administrator faces today is to save a network from an ongoing cyber attack. Modern networks have the capability of detecting ongoing cyber attacks (i.e., using Intrusion Detection Systems (Ids)). Having said that, the number of false alarms tend to be high and acting upon every alarm does not necessarily make the network effective. In this paper, the contributions are-(a) established the credibility of an alarm using poisson distribution;and (b) presented a novel survivability model using the concepts of markov chains and attack graphs. The overall objective in this paper is to help network administrators to decide on whether to terminate a computer system in order to save the network (i.e., when an alarm is raised by an Ids).

关键词： Attack Graphs Intrusion Detection Systems security Metric Markov Chains Poisson Distribution

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Research Directions in Formal Verification of network Configurations Toward Verification of Mobile networks 7th

Research Directions in Formal Verification of Network Config...

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7th international conference on Mobile Internet security (MobiSec)

作者： Sakurada, Hideki Sakurai, Kouichi NTT Corp Tokyo Japan Kyushu Univ Fukuoka Japan Adv Telecommun Res Inst Int Kyoto Japan

ISBN: (纸本)9789819744640;9789819744657

This paper reviews current research trends in the formal verification of computer network configurations, specifically focusing on formal verification for software-defined networking (SDN). We explore the challenges encountered when applying formal verification, comparing its application to pre-SDN network verification efforts. Additionally, we discuss the potential application of formal verification in mobile networks. We first provide an overview of research on the formal verification of virtual LAN (VLAN) configurations, which predates the emergence of SDN. We next illustrate SDN and existing research applying formal verification to SDN. Finally, we briefly examine potential scenarios for applying formal verification to mobile networks.

关键词： formal verification network configuration software-defined networking

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Research on computer network Intrusion Detection Algorithm Based on Deep Learning

Research on Computer Network Intrusion Detection Algorithm B...

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2023 IEEE international conference on Electrical, Automation and computer engineering, ICEACE 2023

作者： Huang, Xiaoyang Tianjin University of Technology Tianjin China

ISBN: (纸本)9798350309614

With the continuous popularization and deepening of the network, the problem of network security is becoming increasingly prominent. How to detect the network intrusion behavior timely and accurately plays a very important role in maintaining network security and improving information security. Traditional methods can not accurately judge the abnormal situation in computer network intrusion detection, and its detection speed is relatively slow, so this paper proposes a computer network intrusion detection method based on deep learning algorithm. Experiments show that the detection accuracy and false positive rate of computer network intrusion detection method based on deep learning algorithm are better than the traditional machine learning algorithm, and can be well applied to real-time network intrusion detection. © 2023 IEEE.

关键词： Artificial intelligence computer network Deep learning algorithm network intrusion detection

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Simulation of computer network Information security Assessment Model Based on Data Mining 2

Simulation of Computer Network Information Security Assessme...

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2nd international conference on Artificial Intelligence and Autonomous Robot Systems, AIARS 2023

作者： Liu, Yanjia Yong, Xi Hua, Baojian Yang, Jianhua Institute of Computing Technology Chinese Academy of Sciences Beijing100086 China Ministry of Water Resources Information Centre Beijing100053 China University of Science and Technology of China School of Software Engineering Jiangsu Suzhou215123 China Beijing Sinohonour Computing Technology Beijing100029 China

ISBN: (纸本)9798350324358

With the continuous growth of scie & tech, network technology has been widely used, which has brought great convenience to people's life and work. However, the rapid improvement of network technology has also given network viruses an opportunity, which has caused harm to the information security of computer users. In order to improve the adaptability to the network environment, it is more effective to use data mining (DM) to prevent and control viruses. Through the use of this technology, the control effect of network security management can be improved, and the effective support for the later network security development can be realized. This article will discuss the related modes of DM, study the practical application of DM to computer network virus defense, and build a computer network information security assessment model based on DM. The simulation results show that the proposed model can achieve a recall rate of 94.8% and an accuracy rate of 95.5%, both of which are better than the random forest model. DM has been effectively applied in the stage of protecting computer network virus, which greatly improves the security of computer network system, and then ensures the stability of computer system operation. © 2023 IEEE.

关键词： Data mining

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Incorporating of security Methods into the software Development Lifecycle Process (SDLC)

Incorporating of Security Methods into the Software Developm...

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2023 international conference on computer Communication and Informatics, ICCCI 2023

作者： Aishwarya, Vakkalagadda Pediredla, Saivishal Radhika, Batchu Vasanthi, Bhumula Padmanaban, K. Velmurugan, A.K. Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram India

ISBN: (纸本)9798350348217

As software usage increases and updates, software development requires several essential elements, including industry security. As vulnerabilities are exploited, we've witnessed an upsurge in the demand for securities. There are many various reasons why security is not effectively maintained in software development processes, thuswe have seen some approaches like traditional security, CllCD, and robust security to make sure security is implemented right from the start rather than after process development. The various tools in this study were used to discuss various security implementation methods, and this discussion may be useful for examining various software © 2023 IEEE.

关键词： Life cycle

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Temporal-Gated Graph Neural network with Graph Sampling for Multi-step Attack Detection 22

Temporal-Gated Graph Neural Network with Graph Sampling for ...

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IEEE 22nd international conference on Trust, security and Privacy in Computing and Communications (TrustCom) / BigDataSE conference / CSE conference / EUC conference / ISCI conference

作者： Chen, Shuyu Lin, Dawei Xie, Zhenping Wang, Hongbo Jiangnan Univ Sch Artificial Intelligence & Comp Sci Wuxi Jiangsu Peoples R China Jiangnan Univ Jiangsu Key Lab Media Design & Software Technol Wuxi Jiangsu Peoples R China Inspur Software Co Ltd Tai An Shandong Peoples R China TRS Topwalk Informat Technol Co Ltd Beijing Peoples R China

ISBN: (纸本)9798350381993;9798350382006

The emergence of new network attacks, especially multi-step attacks which exhibit complex patterns, presents challenges to network security. Intrusion detection in network traffic is one of the core means to ensure network operation security. Traditional intrusion detection methods identify abnormal traffic by modeling the patterns of normal traffic. This strategy focuses on the spatial characteristics of data, ignoring the temporal characteristics of traffic evolution, and may not fully capture the patterns of multi-step network attacks. To address this problem, we propose a Temporal-Gated Graph Neural network (TGGNN) framework based on graph clustering sampling. Firstly, each network traffic data is viewed as a graph node. We use hierarchical graph clustering methods to sample representative points and further construct local evolutionary structures with their temporally adjacent nodes. Then, we design a novel way of constructing graph data that balances both local and global aspects of network traffic data. Based on the GGNN (Gated Graph Neural network), we designed a Temporal-Gated Mechanism in the information propagation part, emphasizing the learning of the local evolutionary structure of the graph. Furthermore, a bidirectional LSTM network is used to further enhance the learning of dynamic patterns in network traffic data. Experimental results based on the UNSW-NB15 dataset demonstrate that our approach not only surpasses the performance of four recent baselines but also eliminates the need for feature engineering by adopting an end-to-end approach.

关键词： Intrusion detection Multi-step attack graph sampling Gate Graph neural network network security

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Research on the Application of computer network security in Cloud computer Intelligent System

Research on the Application of Computer Network Security in ...

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2023 IEEE international conference on Image Processing and computer Applications, ICIPCA 2023

作者： Zhang, Jianqin Jiangsu Union Technical Institute Nanjing Engineering Branch Nanjing China

ISBN: (纸本)9798350314670

This paper proposes a new firewall model to solve the problem of computer network security threats. Firstly, this paper gives the division of function modules and the working algorithm of firewall model system. Then the design and implementation of command dynamic configuration tree are introduced in detail. Finally, the performance of the algorithm used in the system is analyzed. Experimental study shows that this method is cost-effective. It's easy to implement. The system has the advantages of robustness, security and manageability. © 2023 IEEE.

关键词： network security

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computer networkS CYBER security VIA AN INTRUSION DETECTION SYSTEM

COMPUTER NETWORKS CYBER SECURITY VIA AN INTRUSION DETECTION ...

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2023 IEEE international conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Latha, J. KarthickMurugan, S. Logalakshmi, A. Department of Computer Science and Engineering R.M.K. Engineering College India Department of Computer Science and Engineering R.M.D. Engineering College India Department of Computer Science and Engineering Thiruthangal Nadar College India

ISBN: (纸本)9798350305708

Effectively identifying computer network attacks is still a challenge. This is due to recent attempts by cybercriminals to spoof intrusion detection systems (IDS) by altering packet contents. Additionally, the computer networks constantly add a large number of additional devices. Additionally posing a security risk to computer networks are these novel gadgets. To regulate computer network flows and offer security beforehand, you must do a thorough examination of the elements of your network, including the IDSs, the methodologies and devices used, particular kinds of attacks, and the tools that are used. This essay discusses intrusion detection methods, methodology, and tactics in addition to exploring innovative attack types, defenses, and current scientific study in the subject. © 2023 IEEE.

关键词： IDS methodologies IDS technologies IDS tools Intrusion detection system

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