The invention provides a hidden
attack sample
data labeling method, and belongs to the field of
artificial intelligence and
data security. The method comprises the following steps: firstly, carrying out an
attack data labeling process: executing by an attacker, presetting an
immune agent by the attacker, effectively interfering a target agent by wrongly written characters generated by the
immune agent on the premise of keeping the overall fluency and
readability of a text, and meanwhile, ensuring that the target agent is harmless to the own agent; and then carrying out an
immune agent detection process. According to the method, interference information such as wrongly written characters and similar characters can be accurately inserted on the basis of ensuring the
readability of a text through an intelligent
algorithm, so that the purpose of directional
attack on a target agent is achieved, and meanwhile, adverse effects on an own agent are effectively avoided; according to the method, hidden labeling of the attack sample can be realized,
pollution attack on the target
intelligent agent is realized, the influence on the own
intelligent agent is avoided, and the method is widely applied to the aspects of poisoning training data, attacking the
intelligent agent and the like.