Research And Implementation Of Secure Communication Technology For Embedded Operating System

With the continuous rise and development of Internet of Things(IoT)technology,devices based on embedded real-time operating systems play a key role in the Internet of Things.While embedded system devices play key nodes in the IoT system,frequent communication between these devices is also possible.With the frequent occurrence of communication security incidents,the problem of secure communication between embedded systems has attracted more and more attention.How to make communication between embedded systems become safe and reliable,this problem and goal has become the present An important topic in computer engineering and computer science.With the improvement and innovation of machine learning theory in recent years,various computer fields have gradually begun to apply machine learning technology to solve problems.The article will also apply machine learning techniques to solve security communication problems.The article is based on the embedded operating system,using security communication,cryptography,machine learning and other related technologies and theories.The research,design and implementation of secure communication technologies on the system are carried out.The main contents of these tasks include:Implementing cryptographic service based on embedded systems,improving encryption algorithms and providing basic support for secure communication technologies;using trusted computing environment and independently designing a trusted computing environment that is transparent to developers to ensure secure communication security of technology-related data storage;developing secure communication protocols based on embedded system communication protocol stack,such as development of IPSec protocol at IP layer,development of SSL/TLS protocol at transport layer;developing secure communication applications based on embedded systems,collecting,counting,monitoring,and detecting the communication traffic in the system;using the collected data and machine learning technology to establish services in the cloud to help the embedded system intelligently intrusion detection of communication traffic;using homomorphic encryption to guarantee the data security in the communication process between the embedded system and the cloud machine learning service;transplanting the cloud machine learning model into the embedded system and computing the model based on the embedded system to perform traffic intrusion detection.The unit test,integration test,performance test and other methods were used to verify the feasibility,stability and effectiveness of the secure communication technology that is implemented in the article.