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Gao et al., 2021 - Google Patents

Design and evaluation of a multi-domain trojan detection method on deep neural networks

Gao et al., 2021

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Document ID
2392223242473854430
Author
Gao Y
Kim Y
Doan B
Zhang Z
Zhang G
Nepal S
Ranasinghe D
Kim H
Publication year
Publication venue
IEEE Transactions on Dependable and Secure Computing

External Links

Snippet

Trojan attacks on deep neural networks (DNNs) exploit a backdoor embedded in a DNN model that can hijack any input with an attacker's chosen signature trigger. Emerging defence mechanisms are mainly designed and validated on vision domain tasks (eg, image …
Continue reading at arxiv.org (PDF) (other versions)

Classifications

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    • G06N3/0472—Architectures, e.g. interconnection topology using probabilistic elements, e.g. p-rams, stochastic processors
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06F21/554—Detecting local intrusion or implementing counter-measures involving event detection and direct action
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    • G06F21/55—Detecting local intrusion or implementing counter-measures
    • G06F21/56—Computer malware detection or handling, e.g. anti-virus arrangements
    • G06F21/562—Static detection
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    • G06F21/57—Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
    • G06F21/577—Assessing vulnerabilities and evaluating computer system security
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06N99/00—Subject matter not provided for in other groups of this subclass
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