Research on Computer Network Information Security and Protection under the Background of Big Data

Based on the background of the widespread application of big data technology, the information security of computer networks presents new trends and becomes increasingly complex.The surge in data volume, multi-source heterogeneous data structures and the characteristics of real-time transmission have caused great challenges to traditional security models.Based on the impact of the big data environment on network security, this paper systematically analyzes the security vulnerabilities and evolutionary characteristics of typical attack methods in the current network architecture, and introduces security event big data to carry out clustering and behavior analysis, and then constructs a threat assessment architecture that can realize dynamic identification.From the perspective of protection mechanism, it proposes the use of intrusion detection technology integrated with artificial intelligence, a network situation awareness model based on data-driven thinking, and the application planning of blockchain technology in data traceability and trusted anti-tampering.The research results fully demonstrate that the intelligent, real-time and traceable capabilities of network security systems can be effectively enhanced in a multi-technology collaborative manner.This study provides theoretical support and practical reference for the construction of network information security systems under the background of big data.With the rapid advancement of technologies such as the Internet of Things, cloud computing, and mobile Internet, the total amount of global data is growing exponentially.According to a report released by the International Data Corporation (IDC), by 2025, the data generated globally is expected to be around 175ZB, of which unstructured data will account for more than 80%, involving a variety of content formats such as text, images, audio, and video.The frequency of data interaction has increased significantly.Application scenarios such as social platforms, mobile terminals, online payments, and industrial control continue to extend data exchange links, driving the real-time and dynamic nature of data flow to become increasingly prominent and enhanced.In this context, the number of data input and output channels encountered by network systems has increased exponentially.With the increase in system interfaces, security boundaries have become complex and difficult to define, paving more tracks for potential attack behaviors.In highfrequency interactions, data is often stored, processed, analyzed, and transmitted at multiple nodes, building a high-flow situation across systems and regions.This undoubtedly makes security control more difficult, and traditional static defense mechanisms are no longer able to cope with this complex situation. Difficulties and complex situations facing computer network security todayIn the information society empowered by big data, network security issues present a new look of intelligent attack methods, diverse and extensive attack targets, and lagging defense methods.Attackers are increasingly using technologies such as artificial intelligence and machine learning to carry out more hidden and persistent attacks, such as APT attacks, frauds using deep fakes, and automated vulnerability scanning, forming an asymmetric pattern of "strong attack and weak defense".The popularity of hybrid cloud environments and edge computing devices has further extended the network boundary, causing traditional boundary defense methods such as firewalls and VPNs to lose their effectiveness, resulting in multiple penetrations and multi-stage attack paths.According to Symantec's 2023 Cyber Threat Report, more than 11 billion cyber attacks have been recorded worldwide, and more than 45% of them use legitimate credentials to hijack identity authentication systems and then invade internal networks, indicating that network identity and permission management has become a weak link that needs to be strengthened.In this complex background environment, it is urgent to build security models and strategies that meet the characteristics of the big data environment to create a dynamic, real-time, and intelligent protection framework.