PoTrojan: powerful neural-level trojan designs in deep learning modelsPoTrojan: powerful neural-level trojan designs in deep learning modelsMinhui Zou and Yang Shi and Chengliang Wang and Fangyu Li and WenZhan Song and Yu Wang2018
Paper summarynizTo keep it simple, this figure shows the basic idea.
PoTrojan: powerful neural-level trojan designs in deep learning models
arXiv e-Print archive - 2018 via arXiv
First published: 2018/02/08 (1 month ago) Abstract: 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.