PoTrojan：深度学习模型中强大的神经级木马设计
PoTrojan: powerful neural-level trojan designs in deep learning models
摘要：
随着深度学习（DL）的普及，人工智能（AI）已经应用到人类生活的许多领域。神经网络或人工神经网络（NN），DL背后的主要技术，已被广泛研究，以促进计算机视觉和自然语言识别。然而，我们越依赖信息技术，我们就越脆弱。也就是说，恶意NN可能在所谓即将到来的AI时代带来巨大威胁。在本文中，我们首次在文献中提出了一种新的方法来设计和插入强大的神经级木马或PoTrojan在预训练的NN模型。大多数时候，PoTrojans保持不活动状态，不会影响其宿主NN模型的正常功能。PoTrojans只能在非常罕见的情况下触发。然而，一旦被激活，PoTrojans可能会导致宿主NN模型发生故障，错误地预测或分类，这对人工智能时代的人类社会构成重大威胁。我们将解释PoTrojans的原理，以及设计和将它们插入预先训练好的深度学习模型的容易性。PoTrojans不会修改预训练模型的现有架构或参数，而无需重新训练。因此，该方法是非常有效的。
英文摘要：
With the popularity of deep learning (DL), artificial intelligence (AI) has been applied in many areas of human life. Neural network or artificial neural network (NN), the main technique behind DL, has been extensively studied to facilitate computer vision and natural language recognition. However, the more we rely on information technology, the more vulnerable we are. That is, malicious NNs could bring huge threat in the so-called coming AI era. In this paper, for the first time in the literature, we propose a novel approach to design and insert powerful neural-level trojans or PoTrojan in pre-trained NN models. Most of the time, PoTrojans remain inactive, not affecting the normal functions of their host NN models. PoTrojans could only be triggered in very rare conditions. Once activated, however, the PoTrojans could cause the host NN models to malfunction, either falsely predicting or classifying, which is a significant threat to human society of the AI era. We would explain the principles of PoTrojans and the easiness of designing and inserting them in pre-trained deep learning models. PoTrojans doesn't modify the existing architecture or parameters of the pre-trained models, without re-training. Hence, the proposed method is very efficient.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
