A network protection technology is primarily designed for detecting vulnerabilities against the target device through an intrusion detection system (IDS). Unattended locations need detection of malicious attack. The IDS challenge is to achieve a high level of attack prevention by tracking and reviewing incidents at the computer network device to identify potential impacts with low false alarm rates. Furthermore, in this paper, IoT assisted intelligent monitoring approach has been proposed to monitor camera location and senses video frame-based evaluation interference constructively. The proposed method interfaces a digital video camera on a computer with wireless communication. The proposed approach uses a support vector machine classification algorithm for intrusion detection, and its position in the scene is automatically communicated through the wireless cellular network adapter that saves energy. The experimental result shows that the classification accuracy is achieved to 98.97%, and the false-positive rate of classification of the modell is checked.

网络保护技术主要用于通过入侵检测系统 (IDS) 检测针对目标设备的漏洞。无人值守位置需要检测恶意攻击。IDS 面临的挑战是通过跟踪和审查计算机网络设备上的事件以识别低误报率的潜在影响来实现高水平的攻击预防。此外，在本文中，提出了物联网辅助智能监控方法来监控摄像机位置并建设性地感知基于视频帧的评估干扰。所提出的方法将计算机上的数码摄像机与无线通信连接起来。所提出的方法使用支持向量机分类算法进行入侵检测，并且它在场景中的位置通过节省能源的无线蜂窝网络适配器自动通信。实验结果表明，分类准确率达到了98.97%，并检验了模型的分类误报率。