Code recovery system and recovery method based on generator and extended rainbow table

Abstract

A code recovery system and a recovery method based on a generator and an extended rainbow table belong to the technical field of computer safety and comprise an extended rainbow table generating module, a plurality of clients of an extended rainbow table recovering module and a server, wherein the server is connected with a plurality of network nodes and comprises a data mining module, a memorizer and a system initialization module. A user manages the work of the data mining module and the system initialization module of the server through managing the work of terminal networks. The data mining module of the server generates a generator dictionary; the system initialization module of the server generates a distributed initialized configuration file; the distributed initialized configuration file comprises generator dictionary information and is connected with the extended rainbow table generating module and the extended rainbow table recovering module of the network nodes and is used for transmitting system initialization configuration information. The code recovery system and the recovery method based on the generator and the extended rainbow table achieve the purpose that a long instruction rainbow table is generated within a receptible time range by reducing plaintext space and reduces the recovery time of an artificial instruction.

Description

technical field [0001] The invention relates to an encryption system and method in the field of computer security, in particular to a password recovery system and a recovery method based on generator extended rainbow tables. Background technique [0002] The rainbow table is an important method and tool in the field of cryptography. It was originally proposed by Hellman in the article "A cryptanalytic time-memory trade off based on time-space compromise algorithm". Its core idea is A compromise between space and time, the time spent on password recovery is reduced through pre-computation. Essentially, the generation of the rainbow table needs to exhaustively traverse the entire plaintext space. The generation time is related to the length and number of rainbow chains, and the recovery success rate is related to the plaintext space and the size of the rainbow table. That is to say, for a fixed plaintext space, if you want to generate a rainbow table with a high recovery succ...

AI Technical Summary

Problems solved by technology

But the defect of this prior art is: there is no effective method for the generating element of table expansion, and the present invention is mainly based on the method of data mining to mine and formulate the generating element for the real password database.

In addition, due to environmental constraints, the generation and use of Hadoop-based cloud computing-based expansion tables have relatively large limitations, which is not conducive to the application of expansion tables in actual environments.

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