The global energy Internet standard support system plays a vital role in global energy interconnection. However, the system brings convenience to the global energy interconnection and introduces new security issues. Due to the diversity of users, the complexity of the environment and the internationalization, there will be more and more malicious network intrusions from outside and inside. The security system of the global energy Internet standard support system faces great challenges. To this end, this paper proposes a security architecture that combines active and passive, establishing a chain of trust between the active security architecture and the passive security architecture, ensuring a new security architecture, a security organization framework, a security policy framework, a security operation framework, and a closed-loop system that integrates the security technology framework. A deep learning algorithm was introduced for network intrusion learning to achieve sustainable management of the information security life cycle. The combination of active and passive security systems and continuous monitoring strategies based on deep learning fully ensure the security of the global energy Internet standard support system.
ECG diagnostic support system (EDSS): A deep learning neural network based classification system for detecting ECG abnormal rhythms from a low-powered wearable biosensors
