Artificial intelligence optimization system and method adopting adversarial resistance training

An artificial intelligence and optimization method technology, applied in the field of machine learning, can solve the problems of resistance training, such as large amount of calculation, passive defense, poor robustness, etc., to enhance robustness and security, easy parameter optimization, and easy control. Effect

Inactive Publication Date: 2019-05-17
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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AI Technical Summary

Problems solved by technology

[0007] In view of the problems of the above research, the purpose of the present invention is to provide an artificial intelligence optimization system and method that adopts confrontational training. In th...

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  • Artificial intelligence optimization system and method adopting adversarial resistance training
  • Artificial intelligence optimization system and method adopting adversarial resistance training

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Embodiment

[0090] Adversarial training for the handwritten character set MNIST model.

[0091] The MNIST dataset comes from the National Institute of Standards and Technology (NIST).

[0092] The training set consisted of digits handwritten by 250 different people, 50% of them were high school students, 50% were from the Census Bureau staff, and the test set was also handwritten by the same proportion Digital data, the training data set (ie original data set) is 50,000, the verification set is 10,000, and the test data set is 10,000.

[0093] 1. Data preprocessing: the original MNIST data is a 28×28 black-and-white lattice image, and the 28×28 two-dimensional matrix can be converted into a single-row vector of 784, so that for a piece of data (that is, samples in the original data set) Say, there are 784 0, 1 features;

[0094] 2. Data feature extraction, because MNIST is image data, so all 784 features can be retained as all features of the data for processing;

[0095] 3. Pre-training...

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Abstract

The invention discloses an artificial intelligence optimization system and method adopting adversarial training, and belongs to the field of machine learning. The method comprises the following steps:carrying out feature extraction on acquired data in an original data set, and training a neural network model which is not subjected to adversarial training to obtain an identification model; Takingthe identification model as a parameter for calculating the fitness, and generating confrontation samples by a genetic algorithm based on the calculated parameter and the extracted characteristics toobtain all the generated confrontation samples; Mixing all generated adversarial samples with the samples subjected to feature extraction, and performing supervised training of the identification model again as a new data set to obtain an identification model subjected to supervised training; Testing the supervised and trained recognition model, if the supervised and trained recognition model meets a given requirement, obtaining a finally trained recognition model, and if not, adjusting parameters of a genetic algorithm, and then generating a confrontation sample again for training. The methodis used for training the neural network model against resistance, and the model security is improved.

Description

technical field [0001] An artificial intelligence optimization system and method using confrontational training, used for confrontational training of neural network models, belongs to the field of machine learning. Background technique [0002] In recent years, machine learning has been widely used and has achieved good application results in many fields, such as malicious email detection, malicious program detection, image recognition, face recognition, image classification, unmanned driving, etc., which are closely related to people's daily life There are examples of machine learning in every field. Therefore, machine learning gradually penetrates into people's daily life and becomes a key technology to improve people's living standards. However, while machine learning has brought great help to people's learning and life, there are still many security problems in machine learning algorithms. In early spam detection systems and intrusion detection systems, attackers target...

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Application Information

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IPC IPC(8): G06N3/00G06N3/12
Inventor 张小松牛伟纳任仲蔚谢鑫将天宇
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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