Multiple countermeasure sample attack-based intelligent defense algorithm recommendation method and intelligent defense algorithm recommendation system

Abstract

The invention discloses a multiple countermeasure sample attack-based intelligent defense algorithm recommendation method. The method comprises the following steps: cleaning an original data set to obtain a training set; training a target recognition model by utilizing the training set, and obtaining a target attack model; selecting different countermeasure sample attack algorithms, and attackingthe target attack model; quantitatively evaluating the attack success rate of each countermeasure sample attack algorithm, and selecting a target attack algorithm according to the attack success rate;aiming at each target attack algorithm, applying a countermeasure attack defense algorithm one by one for defense purpose; and recommending a corresponding countermeasure attack defense algorithm toa user according to the defense result. The invention further discloses an intelligent defense algorithm recommendation system, wherein the system is adopted by the above intelligent defense algorithmrecommendation method. According to a specific target model, the intelligent defense algorithm recommendation system can intelligently recommend an effective defense algorithm, so that the loss caused by the attack of a defense sample case to the target model is reduced.

Description

technical field [0001] The invention relates to the technical field of anti-example attacks and defenses in machine learning model security and privacy issues, and in particular to an intelligent defense algorithm recommendation method and system based on various anti-example attacks. Background technique [0002] Machine learning is the core of artificial intelligence. In recent years, machine learning has achieved unprecedented development, and its application has spread across various fields of artificial intelligence. Especially in the fields of data mining, computer vision, natural language processing, speech and handwriting recognition, driverless driving, etc., the application of machine learning has achieved great success. Nowadays, machine learning has received extensive attention and in-depth research, both in academia and industry. The development of machine learning has entered a new stage. Various machine learning algorithms and models emerge in an endless stre...

AI Technical Summary

Problems solved by technology

At present, most of the defense algorithms are a static defense method that only targets specific examples of attacks, and there is no unified defense algorithm recommendation and evaluation system

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