aCAPTCHA: Verifying That an Entity Is a Capable Agent via Asymmetric Hardness
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Abstract (arXiv)
As autonomous AI agents increasingly populate the Internet, a novel security challenge arises: "Is this entity an AI agent?" It is a new entity-type verification problem with no established solution. We formalize the problem through a three-class entity taxonomy (Human, Script, Agent) based on a verifiable agentic capability vector <x, r, s> (action, reasoning, and memory). A timing threshold t exploits the asymmetric hardness between human cognition and AI processing to separate the three classes. We define the Agentic Capability Verification Problem (ACVP) through three necessity primitives, each testing one capability dimension. Building on this foundation, we introduce aCAPTCHA (Agent CAPTCHA), a time-constrained security game for agent admission whose security rests on ACVP hardness under t. We instantiate aCAPTCHA through time-bounded natural-language understanding as a multi-round HTTP verification protocol, and evaluate it with preliminary agent trials that validate the protocol's soundness and completeness. aCAPTCHA provides a composable, infrastructure-free admission gate for any service where entity-type verification is required.
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References · 8
- 2017Attention Is All You Needcited by 59,932
- 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
- 2023The Rise and Potential of Large Language Model Based Agents: A Surveycited by 1,422
- 2020Beyond Accuracy: Behavioral Testing of NLP models with CheckListcited by 979
- 2023ChatDev: Communicative Agents for Software Developmentcited by 893
- 2017Adversarial Examples for Evaluating Reading Comprehension Systemscited by 568
- 2015Towards AI-Complete Question Answering: A Set of Prerequisite Toy Taskscited by 309
- 2024Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligencecited by 80
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