Deep Learning in Security of Internet of Things

计算机科学 计算机安全 边缘计算 建筑 入侵检测系统 互联网 脆弱性(计算) 智能电网 物联网 万维网 工程类 电气工程 艺术 视觉艺术
作者
Yuxi Li,Yue Zuo,Houbing Song,Zhihan Lv
出处
期刊:IEEE Internet of Things Journal [Institute of Electrical and Electronics Engineers]
卷期号:9 (22): 22133-22146 被引量:102
标识
DOI:10.1109/jiot.2021.3106898
摘要

Internet-of-Things (IoT) technology is increasingly prominent in the current stage of social development. All walks of life have begun to implement the IoT integration technology, so as to strive to promote industrial modernization, intelligence, and digitalization. In this case, how to link high-risk network activities with entities has become the primary issue for promoting industrial development. However, at this stage, the security issues in the development of the IoT technology have contradictions that are difficult to resolve. According to this situation, how to make system defense intelligent and replace manual monitoring has become the future of the development of security architecture. This article combines existing security research to explore the possibility of deep learning (DL) in upgrading the IoT security architecture, discusses how the IoT can identify and respond to cyber attacks, and how to encrypt edge data transmission. Moreover, this article discusses security research in application fields, such as Industrial IoT, Internet of Vehicles, smart grid, smart home, and smart medical. Then, we summarized the areas that can be improved in future technological development, including sharing computing power through the edge network processing unit (NPU) central device and closely combining the environmental simulation model with the actual environment, as well as malicious code detection, intrusion detection, production safety, vulnerability detection, fault diagnosis, and blockchain technology.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
wwsbb发布了新的文献求助10
2秒前
3秒前
JJ完成签到,获得积分10
5秒前
Orange应助小安采纳,获得10
9秒前
yangling0124完成签到,获得积分10
9秒前
11秒前
香蕉觅云应助科研通管家采纳,获得10
11秒前
小马甲应助科研通管家采纳,获得10
11秒前
杨羕完成签到,获得积分10
11秒前
慕青应助科研通管家采纳,获得10
11秒前
乐乐应助科研通管家采纳,获得10
11秒前
彭于晏应助科研通管家采纳,获得10
11秒前
wanci应助科研通管家采纳,获得30
11秒前
上官若男应助科研通管家采纳,获得10
11秒前
孤独天薇完成签到 ,获得积分10
16秒前
wwyy完成签到,获得积分10
17秒前
铠甲勇士完成签到,获得积分10
17秒前
细心书蕾完成签到 ,获得积分10
18秒前
you完成签到,获得积分10
22秒前
i说晚安完成签到,获得积分10
22秒前
干净的向真完成签到,获得积分10
23秒前
CipherSage应助maliang666采纳,获得10
24秒前
大胖完成签到,获得积分10
26秒前
5High_0完成签到 ,获得积分10
28秒前
sh完成签到,获得积分10
29秒前
31秒前
33秒前
34秒前
半岛岛发布了新的文献求助10
34秒前
maliang666发布了新的文献求助10
37秒前
wwsbb完成签到,获得积分10
40秒前
于友卉完成签到,获得积分20
40秒前
党弛完成签到,获得积分10
41秒前
45秒前
chenjiaye完成签到,获得积分10
46秒前
zzz完成签到,获得积分10
49秒前
11完成签到,获得积分10
49秒前
金钰贝儿应助AJoe采纳,获得10
52秒前
chenjyuu完成签到 ,获得积分10
53秒前
冷酷晓瑶完成签到,获得积分10
55秒前
高分求助中
The Oxford Handbook of Social Cognition (Second Edition, 2024) 1050
Kinetics of the Esterification Between 2-[(4-hydroxybutoxy)carbonyl] Benzoic Acid with 1,4-Butanediol: Tetrabutyl Orthotitanate as Catalyst 1000
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
юрские динозавры восточного забайкалья 800
English Wealden Fossils 700
Handbook of Qualitative Cross-Cultural Research Methods 600
Chen Hansheng: China’s Last Romantic Revolutionary 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3140237
求助须知:如何正确求助?哪些是违规求助? 2791023
关于积分的说明 7797649
捐赠科研通 2447480
什么是DOI,文献DOI怎么找? 1301910
科研通“疑难数据库(出版商)”最低求助积分说明 626345
版权声明 601194