The capacity of machine objects to communicate autonomously is seen as the future of the Internet of Things (IoT), but machine-to-machine communication (M2M) is also gaining traction. In everyday life, security, transportation, industry, and healthcare all employ this paradigm. Smart devices have the ability to detect, handle, store, and analyze data, resulting in major network issues such as security and reliability. There are numerous vulnerabilities linked with IoT devices, according to security experts. Prior to performing any activities, it is necessary to identify and classify the device. Device identification and classification in M2M for secure telerobotic surgery are presented in this study. Telerobotics is an important aspect of the telemedicine industry. The major purpose is to provide remote medical care, which eliminates the requirement for both doctors and patients to be in the same location. This paper aims to propose a security and energy-efficient protocol for telerobotic surgeries, which is the primary concern at present. For secure telerobotic surgery, the author presents an Efficient Device type Detection and Classification (EDDC) protocol for device identification and classification in M2M communication. The periodic trust score is calculated using three factors from each sensor node. It demonstrates that the EDDC protocol is more effective and secure in detecting and categorizing rogue devices.

中文翻译：

---

用于安全远程机器人手术中设备识别和分类的机器对机器通信

机器对象自主通信的能力被视为物联网 (IoT) 的未来，但机器对机器通信 (M2M) 也越来越受到关注。在日常生活中，安全、交通、工业和医疗保健都采用这种范式。智能设备具有检测、处理、存储和分析数据的能力，从而导致安全性和可靠性等重大网络问题。据安全专家称，有许多与物联网设备相关的漏洞。在执行任何活动之前，有必要对设备进行识别和分类。本研究介绍了 M2M 中用于安全远程机器人手术的设备识别和分类。远程机器人是远程医疗行业的一个重要方面。主要目的是提供远程医疗服务，这消除了医生和患者在同一地点的要求。本文旨在为远程机器人手术提出一种安全且节能的协议，这是目前主要关注的问题。对于安全的远程机器人手术，作者提出了一种高效的设备类型检测和分类 (EDDC) 协议，用于 M2M 通信中的设备识别和分类。使用来自每个传感器节点的三个因素计算周期性信任分数。它表明 EDDC 协议在检测和分类流氓设备方面更加有效和安全。作者提出了一种有效的设备类型检测和分类 (EDDC) 协议，用于 M2M 通信中的设备识别和分类。使用来自每个传感器节点的三个因素计算周期性信任分数。它表明 EDDC 协议在检测和分类流氓设备方面更加有效和安全。作者提出了一种有效的设备类型检测和分类 (EDDC) 协议，用于 M2M 通信中的设备识别和分类。使用来自每个传感器节点的三个因素计算周期性信任分数。它表明 EDDC 协议在检测和分类流氓设备方面更加有效和安全。