Breaking the Bot Barrier: Evaluating Adversarial AI Techniques Against Multi-Modal Defense Models | Companion Proceedings of the ACM on Web Conference 2024 (2024)

Breaking the Bot Barrier: Evaluating Adversarial AI Techniques Against Multi-Modal Defense Models | Companion Proceedings of the ACM on Web Conference 2024 (2)

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Breaking the Bot Barrier: Evaluating Adversarial AI Techniques Against Multi-Modal Defense Models | Companion Proceedings of the ACM on Web Conference 2024 (3)

  • Authors:
  • Behzad Ousat Florida International University, Miami, USA

    Florida International University, Miami, USA

    Breaking the Bot Barrier: Evaluating Adversarial AI Techniques Against Multi-Modal Defense Models | Companion Proceedings of the ACM on Web Conference 2024 (4)0000-0002-2328-6895

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  • Dongsheng Luo Florida International University, Miami, USA

    Florida International University, Miami, USA

    Breaking the Bot Barrier: Evaluating Adversarial AI Techniques Against Multi-Modal Defense Models | Companion Proceedings of the ACM on Web Conference 2024 (5)0000-0003-4192-0826

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  • Amin Kharraz Florida International University, Miami, USA

    Florida International University, Miami, USA

    Breaking the Bot Barrier: Evaluating Adversarial AI Techniques Against Multi-Modal Defense Models | Companion Proceedings of the ACM on Web Conference 2024 (6)0000-0002-7841-3409

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WWW '24: Companion Proceedings of the ACM on Web Conference 2024May 2024Pages 646–649https://doi.org/10.1145/3589335.3651474

Published:13 May 2024Publication HistoryBreaking the Bot Barrier: Evaluating Adversarial AI Techniques Against Multi-Modal Defense Models | Companion Proceedings of the ACM on Web Conference 2024 (7)

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WWW '24: Companion Proceedings of the ACM on Web Conference 2024

Breaking the Bot Barrier: Evaluating Adversarial AI Techniques Against Multi-Modal Defense Models

Pages 646–649

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Breaking the Bot Barrier: Evaluating Adversarial AI Techniques Against Multi-Modal Defense Models | Companion Proceedings of the ACM on Web Conference 2024 (8)

ABSTRACT

Breaking the Bot Barrier: Evaluating Adversarial AI Techniques Against Multi-Modal Defense Models | Companion Proceedings of the ACM on Web Conference 2024 (9)

Websites utilize several approaches to detect automated agents. The agents are deployed either for beneficial purposes such as search engine crawlers, or to perform tasks on behalf of the adversary such as scanning for vulnerabilities. Recent methods in detecting such agents include the analysis of the behavior that the agents show when visiting the website. In this paper, I) we describe a deep learning framework that analyzes the triggered browser events to classify the visitor. II) We develop two adversarial attacks in order to bypass the defense by generating adversarial vectors that are misclassified by the model. III) We discuss how applicable the attacks are by reviewing the limitations of the popular tools (i.e., Selenium and Puppeteer) used for the development of automated agents based on full-fledged browsers.

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References

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Breaking the Bot Barrier: Evaluating Adversarial AI Techniques Against Multi-Modal Defense Models | Companion Proceedings of the ACM on Web Conference 2024 (31)

    Index Terms

    1. Breaking the Bot Barrier: Evaluating Adversarial AI Techniques Against Multi-Modal Defense Models

      1. Security and privacy

        1. Security services

          1. Authentication

          2. Software and application security

            1. Web application security

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          Breaking the Bot Barrier: Evaluating Adversarial AI Techniques Against Multi-Modal Defense Models | Companion Proceedings of the ACM on Web Conference 2024 (32)

          WWW '24: Companion Proceedings of the ACM on Web Conference 2024

          May 2024

          1928 pages

          ISBN:9798400701726

          DOI:10.1145/3589335

          • General Chairs:
          • Tat-Seng Chua

            National University of Singapore

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          • Chong-Wah Ngo

            Singapore Management University

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          • Proceedings Chair:
          • Roy Ka-Wei Lee

            Singapore University of Technology and Design

            ,
          • Program Chairs:
          • Ravi Kumar

            Google

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          • Hady W. Lauw

            Singapore Management University

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              • Published: 13 May 2024

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              Breaking the Bot Barrier: Evaluating Adversarial AI Techniques Against Multi-Modal Defense Models | Companion Proceedings of the ACM on Web Conference 2024 (33)

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              • bot detection
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