Dormant Neural Trojans

• URL: http://arxiv.org/abs/2211.01808v1
• Date: Wed, 2 Nov 2022 16:06:46 GMT
• Title: Dormant Neural Trojans
• Authors: Feisi Fu, Panagiota Kiourti, Wenchao Li
• Abstract summary: We present a novel methodology for neural network backdoor attacks. Unlike existing training-time attacks where the Trojaned network would respond to the Trojan trigger after training, our approach inserts a Trojan that will remain dormant until it is activated.
• Score: 6.8722427980580445
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a novel methodology for neural network backdoor attacks. Unlike existing training-time attacks where the Trojaned network would respond to the Trojan trigger after training, our approach inserts a Trojan that will remain dormant until it is activated. The activation is realized through a specific perturbation to the network's weight parameters only known to the attacker. Our analysis and the experimental results demonstrate that dormant Trojaned networks can effectively evade detection by state-of-the-art backdoor detection methods.

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