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WEB high-interaction honeypot system based on artificial intelligence and anti-attack method

An artificial intelligence, high-interaction technology, applied in transmission systems, digital transmission systems, advanced technologies, etc., can solve problems such as loss of attack operations, and achieve the effect of less resource occupation, strong interaction ability, and high interaction performance

Active Publication Date: 2022-03-08
SHANGHAI JIAO TONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although this can minimize the risk of the honeypot system being completely compromised, and also collect some preliminary attack data, it makes the researchers lose the opportunity to obtain the attacker's further attack operations

Method used

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  • WEB high-interaction honeypot system based on artificial intelligence and anti-attack method
  • WEB high-interaction honeypot system based on artificial intelligence and anti-attack method
  • WEB high-interaction honeypot system based on artificial intelligence and anti-attack method

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Embodiment Construction

[0052] The following describes several preferred embodiments of the present invention with reference to the accompanying drawings, so as to make the technical content clearer and easier to understand. The present invention can be embodied in many different forms of embodiments, and the protection scope of the present invention is not limited to the embodiments mentioned herein.

[0053] A preferred embodiment of the present invention, by request collection layer 1, response acquisition layer 2, artificial intelligence layer 3, log recording layer 4 four-layer design and active port database 5, request-response database 6, artificial intelligence database 8 and access The log database consists of 7 four databases. The system of the present invention collects malicious requests from attackers by monitoring ports related to WEB services, and learns the best response message corresponding to each malicious request by forwarding received malicious requests to the public network and...

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Abstract

The invention relates to the field of computer network security, and discloses a WEB high-interaction honeypot system based on artificial intelligence and an anti-attack method. The system comprises a request collection layer, a response acquisition layer, an artificial intelligence layer, a log recording layer, a design and active port database, a request-response database, an artificial intelligence database and an access log database. According to the system, malicious requests of an attacker are collected by monitoring WEB service related ports, response messages corresponding to the malicious requests are learned by forwarding the received malicious requests to a public network and collecting the response messages, finally the response messages are replied to the attacker, and the content of the attack is recorded in an access log database. According to the method, the advantages of few occupied resources and simple deployment of the low-interaction honeypot and the advantages of high camouflage degree and high interaction capability of the high-interaction honeypot are organically combined; and an artificial intelligence technology is utilized, so that the interaction performance of the honeypot system is further improved.

Description

technical field [0001] The invention relates to the field of computer network security, in particular to an artificial intelligence-based WEB high-interaction honeypot system. Background technique [0002] Honeypot (English: honeypot) is a computer term, specifically referring to traps used to detect or defend against unauthorized operations or hacker attacks. Honeypots are usually disguised as seemingly useful networks, data, and computer systems, and deliberately set bugs to attract hackers to attack. Since honeypots do not actually provide any valuable service to the network, any attempt to use them is suspicious. There may also be monitoring software installed in the honeypot to monitor the actions of hackers after intrusion. [0003] Reinforcement learning is an important research direction of artificial intelligence - the third branch of machine learning technology except supervised learning and unsupervised learning. The main difference between reinforcement learni...

Claims

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Application Information

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IPC IPC(8): H04L9/40G06N20/00
CPCH04L63/1491G06N20/00Y02D30/50
Inventor 邹福泰郭万达任蕴东吴越李林森易平
Owner SHANGHAI JIAO TONG UNIV