快速、精确的变压器认证

Gregory Bonaert, Dimitar I. Dimitrov, Maximilian Baader, Martin T. Vechev
{"title":"快速、精确的变压器认证","authors":"Gregory Bonaert, Dimitar I. Dimitrov, Maximilian Baader, Martin T. Vechev","doi":"10.1145/3453483.3454056","DOIUrl":null,"url":null,"abstract":"We present DeepT, a novel method for certifying Transformer networks based on abstract interpretation. The key idea behind DeepT is our new Multi-norm Zonotope abstract domain, an extension of the classical Zonotope designed to handle ℓ1 and ℓ2-norm bound perturbations. We introduce all Multi-norm Zonotope abstract transformers necessary to handle these complex networks, including the challenging softmax function and dot product. Our evaluation shows that DeepT can certify average robustness radii that are 28× larger than the state-of-the-art, while scaling favorably. Further, for the first time, we certify Transformers against synonym attacks on long sequences of words, where each word can be replaced by any synonym. DeepT achieves a high certification success rate on sequences of words where enumeration-based verification would take 2 to 3 orders of magnitude more time.","PeriodicalId":20557,"journal":{"name":"Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Fast and precise certification of transformers\",\"authors\":\"Gregory Bonaert, Dimitar I. Dimitrov, Maximilian Baader, Martin T. Vechev\",\"doi\":\"10.1145/3453483.3454056\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present DeepT, a novel method for certifying Transformer networks based on abstract interpretation. The key idea behind DeepT is our new Multi-norm Zonotope abstract domain, an extension of the classical Zonotope designed to handle ℓ1 and ℓ2-norm bound perturbations. We introduce all Multi-norm Zonotope abstract transformers necessary to handle these complex networks, including the challenging softmax function and dot product. Our evaluation shows that DeepT can certify average robustness radii that are 28× larger than the state-of-the-art, while scaling favorably. Further, for the first time, we certify Transformers against synonym attacks on long sequences of words, where each word can be replaced by any synonym. DeepT achieves a high certification success rate on sequences of words where enumeration-based verification would take 2 to 3 orders of magnitude more time.\",\"PeriodicalId\":20557,\"journal\":{\"name\":\"Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3453483.3454056\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3453483.3454056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20

摘要

提出了一种基于抽象解释的变压器网络认证新方法deep。deep背后的关键思想是我们新的多范数zone otope抽象域,这是经典zone otope的扩展,用于处理1,2范数界摄动。我们介绍了处理这些复杂网络所需的所有多范数分区抽象变压器,包括具有挑战性的softmax函数和点积。我们的评估表明,deep可以证明比最先进的平均鲁棒性半径大28倍,同时扩展有利。此外,我们首次验证了transformer在长单词序列(其中每个单词都可以被任何同义词替换)上不受同义词攻击。deep在单词序列上实现了很高的认证成功率,而基于枚举的验证将花费2到3个数量级的时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast and precise certification of transformers
We present DeepT, a novel method for certifying Transformer networks based on abstract interpretation. The key idea behind DeepT is our new Multi-norm Zonotope abstract domain, an extension of the classical Zonotope designed to handle ℓ1 and ℓ2-norm bound perturbations. We introduce all Multi-norm Zonotope abstract transformers necessary to handle these complex networks, including the challenging softmax function and dot product. Our evaluation shows that DeepT can certify average robustness radii that are 28× larger than the state-of-the-art, while scaling favorably. Further, for the first time, we certify Transformers against synonym attacks on long sequences of words, where each word can be replaced by any synonym. DeepT achieves a high certification success rate on sequences of words where enumeration-based verification would take 2 to 3 orders of magnitude more time.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信