5G物联网环境下的信息安全人工智能技术

I. Petrov, T. Janevski
{"title":"5G物联网环境下的信息安全人工智能技术","authors":"I. Petrov, T. Janevski","doi":"10.24018/ejers.2020.5.11.2210","DOIUrl":null,"url":null,"abstract":"The development of the telecommunication networks observed in present and future time is impressive. Today we witness rapid implementation of 5G networks. We can say that this actually is the moment when (artificial intelligence) AI enters at small door but in the beyond 5G world it is expected to have the prime role in smart operation, management and maintenance of non-software defined networking (SDN), network function virtualization (NFV) and especially at SDN and NFV aware networks. Number of standardization body’s and work groups are focused in a way to create a framework that will define the future use of AI and security standards necessary to exist in order to create health environment for the next generation telecommunication infrastructure. In the wireless world AI/Machine learning (ML) has great potential to shake the way we operate and to become foundation of the transformation that leads to the next industrial revolution. Network virtualization gives flexibility and freedom of the telco operators to choose the hardware and network topology they need for AI/ML platforms and big data sets. 5G and IoT create positive environment for AI and ML development and usage. As the network requirements are developed and the number of the users raises, gains are expected to grow with the number of variables and the interactions among them so it becomes impossible to relay on humans to control the network for increased number of variables and this is why AI with ML and automation become beneficial and necessity to run the future networks. AI generally is defined as capacity of mind or ability to acquire and apply knowledge and skills while ML is defined as learning that does not require explicit programming. Combined usage of AI and ML can optimize almost any component of the wireless network, this does not mean that it should be used everywhere mainly because at the end of the day the cost benefit analysis of its usage must be positive. Smart operation, management and infrastructure maintenance (SOMM) networks are defined as: Intelligent, data driven, integrated and agile. Today AI is introduced but in future it will represent the network engine. It is interesting to mention that network security must be upgraded because the network will provide services for massive number of IoT devices that will have variety of functions and requests. AI/ML can improve the security services and to be used in order to elevate them at advanced level. In this text we focus our attention at AI/ML and security scenarios defined for IoT in 5G environment.","PeriodicalId":12029,"journal":{"name":"European Journal of Engineering Research and Science","volume":"46 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence Techniques for Information Security in 5G IoT Environments\",\"authors\":\"I. Petrov, T. Janevski\",\"doi\":\"10.24018/ejers.2020.5.11.2210\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The development of the telecommunication networks observed in present and future time is impressive. Today we witness rapid implementation of 5G networks. We can say that this actually is the moment when (artificial intelligence) AI enters at small door but in the beyond 5G world it is expected to have the prime role in smart operation, management and maintenance of non-software defined networking (SDN), network function virtualization (NFV) and especially at SDN and NFV aware networks. Number of standardization body’s and work groups are focused in a way to create a framework that will define the future use of AI and security standards necessary to exist in order to create health environment for the next generation telecommunication infrastructure. In the wireless world AI/Machine learning (ML) has great potential to shake the way we operate and to become foundation of the transformation that leads to the next industrial revolution. Network virtualization gives flexibility and freedom of the telco operators to choose the hardware and network topology they need for AI/ML platforms and big data sets. 5G and IoT create positive environment for AI and ML development and usage. As the network requirements are developed and the number of the users raises, gains are expected to grow with the number of variables and the interactions among them so it becomes impossible to relay on humans to control the network for increased number of variables and this is why AI with ML and automation become beneficial and necessity to run the future networks. AI generally is defined as capacity of mind or ability to acquire and apply knowledge and skills while ML is defined as learning that does not require explicit programming. Combined usage of AI and ML can optimize almost any component of the wireless network, this does not mean that it should be used everywhere mainly because at the end of the day the cost benefit analysis of its usage must be positive. Smart operation, management and infrastructure maintenance (SOMM) networks are defined as: Intelligent, data driven, integrated and agile. Today AI is introduced but in future it will represent the network engine. It is interesting to mention that network security must be upgraded because the network will provide services for massive number of IoT devices that will have variety of functions and requests. AI/ML can improve the security services and to be used in order to elevate them at advanced level. In this text we focus our attention at AI/ML and security scenarios defined for IoT in 5G environment.\",\"PeriodicalId\":12029,\"journal\":{\"name\":\"European Journal of Engineering Research and Science\",\"volume\":\"46 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Engineering Research and Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24018/ejers.2020.5.11.2210\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Engineering Research and Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24018/ejers.2020.5.11.2210","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

电信网络在现在和将来的发展是令人印象深刻的。今天,我们见证了5G网络的快速实施。我们可以说,这实际上是人工智能进入小门的时刻,但在超越5G的世界中,它有望在非软件定义网络(SDN),网络功能虚拟化(NFV),特别是SDN和NFV感知网络的智能运营,管理和维护中发挥主要作用。若干标准化机构和工作组的工作重点是创建一个框架,该框架将确定人工智能的未来使用以及为下一代电信基础设施创造卫生环境所必需的安全标准。在无线世界中,人工智能/机器学习(ML)具有巨大的潜力,可以改变我们的运营方式,并成为导致下一次工业革命的转型基础。网络虚拟化为电信运营商选择AI/ML平台和大数据集所需的硬件和网络拓扑提供了灵活性和自由度。5G和物联网为AI和ML的开发和使用创造了积极的环境。随着网络需求的发展和用户数量的增加,预计收益将随着变量数量和它们之间的交互而增长,因此不可能依靠人类来控制网络以增加变量数量,这就是为什么具有ML和自动化的人工智能对运行未来网络是有益的和必要的。AI通常被定义为思维能力或获取和应用知识和技能的能力,而ML被定义为不需要明确编程的学习。人工智能和机器学习的结合使用可以优化无线网络的几乎任何组件,这并不意味着它应该在任何地方使用,主要是因为在一天结束时,其使用的成本效益分析必须是积极的。智能运营、管理和基础设施维护(SOMM)网络的定义是:智能、数据驱动、集成和敏捷。今天人工智能被引入,但未来它将代表网络引擎。有趣的是,网络安全必须升级,因为网络将为大量具有各种功能和请求的物联网设备提供服务。AI/ML可以改善安全服务,并被用于将其提升到高级水平。在本文中,我们将重点关注5G环境中为物联网定义的AI/ML和安全场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Artificial Intelligence Techniques for Information Security in 5G IoT Environments
The development of the telecommunication networks observed in present and future time is impressive. Today we witness rapid implementation of 5G networks. We can say that this actually is the moment when (artificial intelligence) AI enters at small door but in the beyond 5G world it is expected to have the prime role in smart operation, management and maintenance of non-software defined networking (SDN), network function virtualization (NFV) and especially at SDN and NFV aware networks. Number of standardization body’s and work groups are focused in a way to create a framework that will define the future use of AI and security standards necessary to exist in order to create health environment for the next generation telecommunication infrastructure. In the wireless world AI/Machine learning (ML) has great potential to shake the way we operate and to become foundation of the transformation that leads to the next industrial revolution. Network virtualization gives flexibility and freedom of the telco operators to choose the hardware and network topology they need for AI/ML platforms and big data sets. 5G and IoT create positive environment for AI and ML development and usage. As the network requirements are developed and the number of the users raises, gains are expected to grow with the number of variables and the interactions among them so it becomes impossible to relay on humans to control the network for increased number of variables and this is why AI with ML and automation become beneficial and necessity to run the future networks. AI generally is defined as capacity of mind or ability to acquire and apply knowledge and skills while ML is defined as learning that does not require explicit programming. Combined usage of AI and ML can optimize almost any component of the wireless network, this does not mean that it should be used everywhere mainly because at the end of the day the cost benefit analysis of its usage must be positive. Smart operation, management and infrastructure maintenance (SOMM) networks are defined as: Intelligent, data driven, integrated and agile. Today AI is introduced but in future it will represent the network engine. It is interesting to mention that network security must be upgraded because the network will provide services for massive number of IoT devices that will have variety of functions and requests. AI/ML can improve the security services and to be used in order to elevate them at advanced level. In this text we focus our attention at AI/ML and security scenarios defined for IoT in 5G environment.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
相关文献
二甲双胍通过HDAC6和FoxO3a转录调控肌肉生长抑制素诱导肌肉萎缩
IF 8.9 1区 医学Journal of Cachexia, Sarcopenia and MusclePub Date : 2021-11-02 DOI: 10.1002/jcsm.12833
Min Ju Kang, Ji Wook Moon, Jung Ok Lee, Ji Hae Kim, Eun Jeong Jung, Su Jin Kim, Joo Yeon Oh, Sang Woo Wu, Pu Reum Lee, Sun Hwa Park, Hyeon Soo Kim
具有疾病敏感单倍型的非亲属供体脐带血移植后的1型糖尿病
IF 3.2 3区 医学Journal of Diabetes InvestigationPub Date : 2022-11-02 DOI: 10.1111/jdi.13939
Kensuke Matsumoto, Taisuke Matsuyama, Ritsu Sumiyoshi, Matsuo Takuji, Tadashi Yamamoto, Ryosuke Shirasaki, Haruko Tashiro
封面:蛋白质组学分析确定IRSp53和fastin是PRV输出和直接细胞-细胞传播的关键
IF 3.4 4区 生物学ProteomicsPub Date : 2019-12-02 DOI: 10.1002/pmic.201970201
Fei-Long Yu, Huan Miao, Jinjin Xia, Fan Jia, Huadong Wang, Fuqiang Xu, Lin Guo
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Introducing Secondary Education Students to Programming through Sound Alerts Optimal Sizing of a PV System in Golpayegan, Iran Using Thermal Modeling-based Load Demand Experimental Study of Twin Connected Pipe Jets Development and Assessment of Cracking and Sorting Processes of Palm Kernel Nut Machine Chemical Characterization of Nine Locally Made Cement Products for Quality Assurance in Nigeria Cement Industry
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1