An overview of cybersecurity based on Network Security Situational Awareness and Machine learning

Network security refers to a series of measures to protect computer systems, network systems and network data from unauthorized access, theft, damage, tampering and interference on the Internet. With the popularity and application of the Internet, the issue of network security has become more and more important, especially in the financial, transportation, medical, government and other industries, security issues cannot be ignored. In this context, it is important to deal with the security issues in a more complex network environment. Network security situational awareness refers to the analysis and monitoring of network data, events and behaviors to keep abreast of security threats and dog overreaching in the network environment so that timely defensive measures can be taken. Machine learning techniques use algorithms and models to allow computers to learn and improve on their own. Machine learning has a wide range of applications, including image recognition, speech recognition, natural language processing, and other fields. Based on these two important technical concepts, this paper provides an overview of both and their applications in cyberspace security, and concludes with a summary and outlook on their future development.