Method and device for protecting neural network model security
A neural network model and network model technology, applied in biological neural network models, neural learning methods, neural architectures, etc., can solve problems such as attackers or gray-produced attacks, stealing model sensitive information, etc., to achieve privacy protection and guarantee prediction. performance, the effect of reducing resource consumption
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[0020] Multiple embodiments disclosed in this specification will be described below in conjunction with the accompanying drawings.
[0021] As mentioned earlier, if all the trained neural network models are exposed, it is easy for attackers or gray products to attack through the model and steal sensitive information in the model. For example, after obtaining the neural network model, the attacker can infer the statistical characteristics remembered in the network layer by visualizing it. For example, suppose the neural network model is used to decide whether to provide a certain service to the user, where The feature remembered by a certain network layer may be: if the user’s age is older than 52, no loan service will be provided. At this time, the attacker can modify the user’s age (such as changing 54 to 48), so that illegal users can use loan service. For another example, after obtaining the neural network model, the attacker can observe the data distribution of the output...
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