中文标题#
Aura-CAPTCHA：一種強化學習和 GAN 增強的多模態 CAPTCHA 系統
英文标题#
Aura-CAPTCHA: A Reinforcement Learning and GAN-Enhanced Multi-Modal CAPTCHA System
中文摘要#
Aura-CAPTCHA 作為一種多模態 CAPTCHA 系統被開發出來，以解決傳統方法在人工智慧技術（如光學字符識別 OCR 和對抗性圖像處理）日益突破時出現的漏洞。 設計中集成了生成對抗網絡 GANs 用於生成動態圖像挑戰，強化學習 RL 用於自適應難度調整，以及大語言模型 LLMs 用於創建文本和音頻提示。 視覺挑戰包括至少包含三個正確圖像的 3x3 網格選擇，而音頻挑戰則將隨機數字和單詞組合成一個任務。 強化學習根據錯誤嘗試次數、響應時間和可疑用戶行為來調整難度。 在真實流量上的評估顯示，人類成功率為 92%，機器人繞過率為 10%，顯著優於現有的 CAPTCHA 系統。 該系統為保護在線應用提供了一種強大且可擴展的方法，同時保持對用戶的可訪問性，解決了之前研究中提到的空白。
英文摘要#
Aura-CAPTCHA was developed as a multi-modal CAPTCHA system to address vulnerabilities in traditional methods that are increasingly bypassed by AI technologies, such as Optical Character Recognition (OCR) and adversarial image processing. The design integrated Generative Adversarial Networks (GANs) for generating dynamic image challenges, Reinforcement Learning (RL) for adaptive difficulty tuning, and Large Language Models (LLMs) for creating text and audio prompts. Visual challenges included 3x3 grid selections with at least three correct images, while audio challenges combined randomized numbers and words into a single task. RL adjusted difficulty based on incorrect attempts, response time, and suspicious user behavior. Evaluations on real-world traffic demonstrated a 92% human success rate and a 10% bot bypass rate, significantly outperforming existing CAPTCHA systems. The system provided a robust and scalable approach for securing online applications while remaining accessible to users, addressing gaps highlighted in previous research.
文章页面#
Aura-CAPTCHA：一種強化學習和 GAN 增強的多模態 CAPTCHA 系統
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