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New CLIC system secures LLMs in Open RAN against injection attacks

Researchers have developed CLIC, a closed-loop intent consistency layer designed to secure Large Language Models (LLMs) integrated into Open Radio Access Networks (O-RAN). This system addresses runtime prompt injection and residual virtual prompt injection (VPI) attacks by introducing a formal consistency score. Implemented on the OpenAI Cellular platform, CLIC significantly reduces attack success rates while introducing a minor increase in latency. AI

IMPACT Enhances the security of LLM integrations in critical network infrastructure, potentially enabling wider adoption in telecommunications.

RANK_REASON The cluster describes a new research paper detailing a novel system for securing LLMs in a specific technical domain. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New CLIC system secures LLMs in Open RAN against injection attacks

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The cluster describes a new research paper detailing a novel system for securing LLMs in a specific technical domain. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Sunder Ali Khowaja, Kapal Dev, Joongheon Kim, Angelos Antonopoulos, Nikolaos Bartzoudis ·

    CLIC: Closed-Loop Intent Consistency for Securing LLM-Driven Control in Open RAN

    arXiv:2610.40744v1 Announce Type: cross Abstract: With the progressive capabilities of large language models (LLMs), researchers are finding ways to integrate them into the control loops of Open Radio Access Network (O-RAN) to enable slicing and resource management through user i…