面向6G智能终端身份鉴别技术

doi:10.11959/j.issn.2096-3750.2020.00159

Abstract

Abstract:

The intelligent terminal will greatly expand the applications of 6G .However,it will also make 6G face with greater security threats.The reliable terminal identification technology is the premise to ensure the security of 6G networks.Firstly,based on the network architecture and terminal characteristics,the requirements and challenges of 6G intelligent terminal identification were summarized.Then,the development trend was put forward for 6G intelligent terminal identification.Finally,physical layer authentication was explored to achieve possible realization of intelligent terminal identity authentication mechanism in 6G networks.

Key words: intelligent terminal, 6G, identification, physical layer authentication

CLC Number:

TN918

Shida XIA,Jin XU,Xiaofeng TAO. Intelligent terminal identification technology toward 6G[J]. Chinese Journal on Internet of Things, 2020, 4(1): 131-138.

Figures/Tables 6

References 46

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	4G	5G	6G
网络特点	扁平化网络、全IP结构	云化、边缘化、软件化、虚拟化、切片化	智能化
网络组成	蜂窝网	地面网络、垂直行业	地面网络、太空网络、深海网络
终端类型	智能手机	智能终端	泛在、智能、轻量、共享、融合的智能终端
鉴权机制	EPS-AKA	EAP-AKA' 5G AKA	智能认证机制
	分级密钥	非对称密码体制	自适应安全需求
		保护鉴权时间有效性
特点	双向鉴权	时延无法满足要求	自适应鉴权算法选择
	明文传输身份信息	缺乏鉴权连续性管理	智能化鉴权切换
		缺乏统一鉴权管理	统一鉴权管理

	密钥鉴权	物理层认证	区块链认证
原理	密钥协商协议	物理层特征认证	非对称加密和智能合约
主要作用	终端接入保护、数据完整性保护	终端接入保护	数据完整性保护
	稳定性强	安全度高	信息无法篡改
优势		复杂度低
	可靠性高	通用性强	隐私保护
	复杂度高	可靠性差	保证节点可信度
挑战		稳健性低
	通用性差	无法保护数据完整性	大规模部署下时延高

学习类型	学习方法	特点	参考文献
	深度学习	基于攻击样本学习分类模型，实现可靠认证	34,35,36]
有参数学习	强化学习	基于攻击者样本学习判决阈值，最大化认证精度	37]
	回归学习	学习属性可靠性评估模型，增强认证可靠性	38-39]
	基于核函数学习	通过核函数将非线性可分样本映射至线性可分子空间，增强认证可靠性	40]
无参数学习	聚类学习	基于样本结构对合法样本和攻击样本自适应分类，提高认证可靠性	41,42,43]

样本类型	方式	特点	参考文献
多属性	互补双属性多独立属性	同一信号的多个物理层属性作为身份标识	34,44][40,45]
多观测节点	接收信号自身观测环境信号观测	不同感知节点对同一信号的联合感知作为身份标识	38][46]

Intelligent terminal identification technology toward 6G

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