Work in Progress: Network Attack Detection Towards Smart Factory

With the continuous development of network communication and Internet of Things technology, the smart factory of new energy vehicles is increasingly dependent on network communication technology. Due to its increasing openness, which leads to increasing security risks, the attackers' system vulnerability discovery ability and attack techniques are also improving, making the security threats of smart factories escalating. To improve the autonomous sensing and defence capability of smart production lines for security vulnerabilities in the collaborative manufacturing environment, we put forward an adaptive LDoS attack detection scheme based on RF-GMM algorithm in an SDN environment. The method distinguishes normal and abnormal states of networks in smart factories by establishing a multi-feature selection model and profiling network anomalies to achieve the detection for external intrusions.