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TRACE-Bot: Detecting Emerging LLM-Driven Social Bots via Implicit Semantic Representations and AIGC-Enhanced Behavioral Patterns

research note

TRACE-Bot: Detecting Emerging LLM-Driven Social Bots via Implicit Semantic Representations and AIGC-Enhanced Behavioral Patterns

·7 min read·Zhongbo Wang, Zhiyu Lin, Zhu Wang et al.

The paper addresses the emerging threat of social bots driven by large language models (LLMs), which generate highly human-like content that evades traditional bot detection methods

researchllm-driven-social-botsmultimodal-detectionaigc-detectionsemantic-representations

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Uncovering Relationships between Android Developers, User Privacy, and Developer Willingness to Reduce Fingerprinting Risks

research note

Uncovering Relationships between Android Developers, User Privacy, and Developer Willingness to Reduce Fingerprinting Risks

·7 min read·Alex Berke, Güliz Seray Tuncay, Michael Specter et al.

This paper investigates how Android developers perceive platform efforts to reduce user tracking via device fingerprinting, a stealthy method that circumvents user controls and privacy protections

researchandroid-developer-privacymobile-fingerprintingplatform-privacy-interventiondeveloper-survey

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