Adversarial Text-Based CAPTCHA Generation Method Utilizing Spatial Smoothing

Yuichiro Matsuura, Hiroya Kato, Iwao Sasase

研究成果: Conference contribution

抄録

The development of deep learning (DL) techniques has enabled to crack traditional text-based CAPTCHA (Com-pletely Automated Public Turing test to tell Computers and Humans Apart), which results in new security issues. As a coun-termeasure against DL based attacks, the adversarial CAPTCHA is well suited since it can increase the difficulty of machine recognition while ensuring human readability. However, spatial smoothing can negate the effectiveness of adversarial CAPTCHAs because adversarial noises in them are subject to averaging pixels. As far as we know, there are no effective counters against spatial smoothing, whereas it is the critical problem which facilitates spreading automated attacks. Therefore, to address the unsolved problem, in this paper, we propose an adversarial text-based CAPTCHA generation method utilizing spatial smoothing. We focus on the fact that when spatial smoothing is applied to an image, the amount of information it carries decreases, making the whole image blurred. Spatial smoothing is only viable as an attack when the mitigation of the adversarial noise has a larger impact than the whole image getting blurred. Thus, when the degree of spatial smoothing exceeds a certain threshold, the impact of the two aspects reverses, and the difficulty of the recognition increase. By utilizing this phenomenon in the generation of CAPTCHAs, the proposed method can indirectly neutralize the intended effect of spatial smoothing by attackers, preventing the recognition rate from increasing. Our evaluation shows the proposed method can reduce the recognition rate by up to 34%, compared to the conventional method. Besides, an experiment on human recognition rates marked 73.67%, showing that human recognition is maintained at an acceptable level.

本文言語English
ホスト出版物のタイトル2021 IEEE Global Communications Conference, GLOBECOM 2021 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781728181042
DOI
出版ステータスPublished - 2021
イベント2021 IEEE Global Communications Conference, GLOBECOM 2021 - Madrid, Spain
継続期間: 2021 12月 72021 12月 11

出版物シリーズ

名前2021 IEEE Global Communications Conference, GLOBECOM 2021 - Proceedings

Conference

Conference2021 IEEE Global Communications Conference, GLOBECOM 2021
国/地域Spain
CityMadrid
Period21/12/721/12/11

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ ネットワークおよび通信
  • コンピュータ サイエンスの応用
  • ハードウェアとアーキテクチャ
  • 情報システムおよび情報管理
  • 安全性、リスク、信頼性、品質管理
  • 健康情報学

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