Abstract
Intelligent dialogue systems are widely applied in smart home systems, and the security of such systems deserves concern [1, 2]. In this paper, we design a threatening scenario of dialogue systems at a smart home. A trojan robot is disguised as one part of the whole system but generates dialogue adversarial examples to attack the normal robots according to the information of users. To achieve the goal in such a scenario, the responding speed, the correctness of the grammar, and the consistency of semantic is necessary. Based on these requirements, we propose a novel method named Attention weight Probability Estimation Attack (APE) to allocate the keys words in dialogue and substitute these words with synonyms in real-time. We perform our experiments on popular classification datasets in the DNN model, and the result shows that APE effectively attacks the system with low responding time and a high success rate.
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Acknowledgement
We thank the anonymous reviewers for their insightful comments on the preliminary version of this paper. This work is supported by the Natural Science Foundation of Guangdong Province (Grant No. 2018A030313354). Any findings, opinions, or conclusions in this paper are those of the authors and do not reflect the views of the funding agency.
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Deng, E., Qin, Z., Li, M., Ding, Y., Qin, Z. (2021). Attacking the Dialogue System at Smart Home. In: Gao, H., Wang, X., Iqbal, M., Yin, Y., Yin, J., Gu, N. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 349. Springer, Cham. https://doi.org/10.1007/978-3-030-67537-0_10
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DOI: https://doi.org/10.1007/978-3-030-67537-0_10
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