找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Security, Trust and Privacy Models, and Architectures in IoT Environments; Lidia Fotia,Fabrizio Messina,Giuseppe M.L. Sarné Book 2023 The

[复制链接]
楼主: 杂技演员
发表于 2025-3-23 12:45:33 | 显示全部楼层
发表于 2025-3-23 14:32:58 | 显示全部楼层
发表于 2025-3-23 20:30:27 | 显示全部楼层
发表于 2025-3-24 02:07:46 | 显示全部楼层
Digital Twin Through Physical Assets Tokenization in Blockchain,analyze some relevant aspects of the main available tokenization approaches, such as the IoT-based, and then we propose a new concept architecture that aim to combine the best side of each approach into a new hybrid solution that use both on-chain and off-chain transactions to being suitable for any kind of physical asset.
发表于 2025-3-24 02:31:44 | 显示全部楼层
IoT Network Administration by Intelligent Decision Support Based on Combined Neural Networks,also have a fairly developed and branched structure. However, the high dynamics of the behavior of IoT networks, coupled with the large volumes of information processed in them and the transmitted traffic, cause certain difficulties in solving the problems of administration of computer networks. It
发表于 2025-3-24 10:30:48 | 显示全部楼层
A Novel Privacy-Preserving Framework Based on Blockchain Technology to Secure Industrial IoT Data,h such kinds of data. In order to avoid such kinds of security problems, the design of a distributed model to provide resistant to security breached and vulnerabilities. This provides a trust-less solution to the healthcare practitioner and their patients. One of the proposed solutions for adopting
发表于 2025-3-24 14:17:43 | 显示全部楼层
Detecting Collusive Agents by Trust Measures in Social IoT Environments: A Novel Reputation Model,ons. Smart objects can be associated with software agents to boost social interactions and realizing complex and sophisticated forms of collaboration of objects with both other objects and people. In such a scenario, there exists the possibility to interact with unreliable partners exposing agents t
发表于 2025-3-24 15:01:33 | 显示全部楼层
发表于 2025-3-24 22:51:57 | 显示全部楼层
发表于 2025-3-24 23:34:38 | 显示全部楼层
Machine Learning Methodologies for Preventing Malware Obfuscation,n rely on an attack surface that grows together with the number of new devices coming to the market. There is a constant competition between malware detection systems that have to adapt their knowledge base and heuristics day by day and malware writers that have to find new techniques to evade these
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-19 01:53
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表