自然语言处理中的标记修改对抗攻击:调查

IF 1.4 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE AI Communications Pub Date : 2024-04-02 DOI:10.3233/aic-230279
Tom Roth, Yansong Gao, Alsharif Abuadbba, Surya Nepal, Wei Liu
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引用次数: 0

摘要

许多对抗性攻击都以自然语言处理系统为目标,其中大多数攻击都是通过修改文档中的单个标记而得逞的。尽管这些攻击表面上各具特色,但从根本上说,它们不过是由目标函数、允许的转换、搜索方法和限制条件这四个部分组成的独特配置。在本调查报告中,我们系统地介绍了文献中使用的不同组件,并使用了与攻击无关的框架,以便于对组件进行比较和分类。我们的工作旨在为该领域的新手提供全面的指导,并激发有针对性的研究,以完善各个攻击组件。
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Token-modification adversarial attacks for natural language processing: A survey
Many adversarial attacks target natural language processing systems, most of which succeed through modifying the individual tokens of a document. Despite the apparent uniqueness of each of these attacks, fundamentally they are simply a distinct configuration of four components: a goal function, allowable transformations, a search method, and constraints. In this survey, we systematically present the different components used throughout the literature, using an attack-independent framework which allows for easy comparison and categorisation of components. Our work aims to serve as a comprehensive guide for newcomers to the field and to spark targeted research into refining the individual attack components.
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来源期刊
AI Communications
AI Communications 工程技术-计算机:人工智能
CiteScore
2.30
自引率
12.50%
发文量
34
审稿时长
4.5 months
期刊介绍: AI Communications is a journal on artificial intelligence (AI) which has a close relationship to EurAI (European Association for Artificial Intelligence, formerly ECCAI). It covers the whole AI community: Scientific institutions as well as commercial and industrial companies. AI Communications aims to enhance contacts and information exchange between AI researchers and developers, and to provide supranational information to those concerned with AI and advanced information processing. AI Communications publishes refereed articles concerning scientific and technical AI procedures, provided they are of sufficient interest to a large readership of both scientific and practical background. In addition it contains high-level background material, both at the technical level as well as the level of opinions, policies and news.
期刊最新文献
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