Network security dynamic defense system and method based on big data

Abstract

The invention discloses a network security dynamic defense system and method based on big data. The system comprises a big data module, a dynamic defense module, a backup module and a monitoring module, the big data module and the dynamic defense module are both bidirectionally connected with the monitoring module; and the backup module is used for all data and attack behavior data in the data module, the dynamic defense module and the monitoring module. Abnormal behaviors in a data packet are positioned and analyzed through a big data module, active defense and passive defense are matched, a dynamic defense model with attacking and defending view angles is established, an attacker is actively spoofed, the sight of the attacker is disturbed, and the attacker is decoy to carry out attack by setting a honeypot, so that the attack time is prolonged and the attack efficiency is improved. The opportunity is provided for the defense model to implement the defense scheme, the dynamic, real-time and active defense of the defense system is finally realized, and the defense effect is good.

Description

technical field

[0001] The invention relates to the field, in particular to a big data-based network security dynamic defense system and method. Background technique

[0002] In recent years, cyberspace has rapidly risen to a new battlefield among major powers. APT attacks, DDoS, and industrial Internet attacks represented by government enterprises and scientific research institutions have become increasingly serious, leading to the theft of important intelligence data of government enterprises and institutions, and industrial interconnection systems. The financial infrastructure was destroyed and the financial infrastructure suffered heavy economic losses, seriously endangering my country's national security and social and economic interests. In the face of new attack methods such as targeted APT attacks, ransomware, and mining viruses, traditional technical means based on feature detection have great limitations in dealing with dynamic, changeable, and high-intensity aspect...

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