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相关概念视频

Rapid Identification of Pathogens01:25

Rapid Identification of Pathogens

MALDI-TOF MS has transformed clinical microbiology by offering a rapid and reliable method for pathogen identification. The traditional approach to microbial identification typically involves time-consuming culture techniques and biochemical tests, which can delay the initiation of appropriate antimicrobial therapy. MALDI-TOF MS avoids these delays by using characteristic ribosomal protein mass patterns of microbial cells, enabling accurate species-level identification within minutes.Principle...

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Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
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ROSIDS23:用于机器人操作系统的网络入侵检测数据集

Elif Değirmenci1, Yunus Sabri Kırca1, İlker Özçelik2

  • 1Department of Computer Engineering, Eskisehir Osmangazi University, Eskisehir, 26048, Turkey.

Data in brief
|November 29, 2023
PubMed
概括

ROSIDS23数据集提供了关于机器人操作系统 (ROS) 网络攻击的高保真数据,这对于推进机器人系统安全研究和开发有效的对策至关重要.

关键词:
入侵检测系统的入侵检测系统网络监控 网络监控 网络监控网络流量 网络流量这就是ROSOS ROS.安全的安全的安全的安全的安全.交通分类的交通分类.

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科学领域:

  • 机器人系统安全 机器人系统安全
  • 网络安全 网络安全
  • 网络法医学 网络法医学

背景情况:

  • 机器人系统的日益集成需要强有力的安全措施.
  • 缺乏高可靠性数据集阻碍了机器人系统安全研究.
  • 现有的研究往往缺乏针对机器人中间件的网络攻击的全面数据.

研究的目的:

  • 介绍ROSIDS23数据集,这是一个针对机器人系统的网络攻击数据的新集合.
  • 详细介绍数据集创建和特征提取背后的方法.
  • 为提高机器人基础设施安全提供宝贵的资源.

主要方法:

  • 在IFARLab-DIH机器人和工厂级实验室环境中收集数据.
  • 使用tcpdump从机器人操作系统 (ROS) 中间软件捕获网络流量.
  • 使用CICFlowMeter从pcap文件中提取82个流量特征并将其转换为CSV格式.

主要成果:

  • ROSIDS23数据集包括来自基于ROS的网络的良性和多样化的攻击流量.
  • 功能被提取和格式化,以便在安全研究中更容易使用.
  • 该数据集为分析和减轻机器人系统中的网络威胁提供了基础.

结论:

  • ROSIDS23数据集对机器人系统安全研究做出了重大贡献.
  • 它可以开发和验证先进的安全对策.
  • 促进向更具弹性和安全的机器人基础设施的进化.