The Art of Deception: Robust Backdoor Attack using Dynamic Stacking of Triggers

Fuente: arXiv
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Auteur principal: Mengara, Orson
Format: Preprint
Publié: 2024
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author Mengara, Orson
author_facet Mengara, Orson
contents The area of Machine Learning as a Service (MLaaS) is experiencing increased implementation due to recent advancements in the AI (Artificial Intelligence) industry. However, this spike has prompted concerns regarding AI defense mechanisms, specifically regarding potential covert attacks from third-party providers that cannot be entirely trusted. Recent research has uncovered that auditory backdoors may use certain modifications as their initiating mechanism. DynamicTrigger is introduced as a methodology for carrying out dynamic backdoor attacks that use cleverly designed tweaks to ensure that corrupted samples are indistinguishable from clean. By utilizing fluctuating signal sampling rates and masking speaker identities through dynamic sound triggers (such as the clapping of hands), it is possible to deceive speech recognition systems (ASR). Our empirical testing demonstrates that DynamicTrigger is both potent and stealthy, achieving impressive success rates during covert attacks while maintaining exceptional accuracy with non-poisoned datasets.
format Preprint
id arxiv_https___arxiv_org_abs_2401_01537
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle The Art of Deception: Robust Backdoor Attack using Dynamic Stacking of Triggers
Mengara, Orson
Cryptography and Security
Artificial Intelligence
Machine Learning
The area of Machine Learning as a Service (MLaaS) is experiencing increased implementation due to recent advancements in the AI (Artificial Intelligence) industry. However, this spike has prompted concerns regarding AI defense mechanisms, specifically regarding potential covert attacks from third-party providers that cannot be entirely trusted. Recent research has uncovered that auditory backdoors may use certain modifications as their initiating mechanism. DynamicTrigger is introduced as a methodology for carrying out dynamic backdoor attacks that use cleverly designed tweaks to ensure that corrupted samples are indistinguishable from clean. By utilizing fluctuating signal sampling rates and masking speaker identities through dynamic sound triggers (such as the clapping of hands), it is possible to deceive speech recognition systems (ASR). Our empirical testing demonstrates that DynamicTrigger is both potent and stealthy, achieving impressive success rates during covert attacks while maintaining exceptional accuracy with non-poisoned datasets.
title The Art of Deception: Robust Backdoor Attack using Dynamic Stacking of Triggers
topic Cryptography and Security
Artificial Intelligence
Machine Learning
url https://arxiv.org/abs/2401.01537