Intellicise Wireless Networks Meet Agentic AI: A Security and Privacy Perspective

2026-02-16

AI Summary

This work addresses the novel security and privacy risks introduced by Agentic AI in Intellicise (intelligent and lean) wireless networks. It presents the first comprehensive taxonomy tailored to the security and privacy challenges inherent in Agentic AI–driven Intellicise wireless systems, systematically identifying their unique threat landscape. Building upon this taxonomy, the study proposes an intelligent defense framework grounded in the perception–memory–reasoning–action closed-loop architecture characteristic of Agentic AI. The efficacy of the framework is demonstrated through a case study on intelligent eavesdropping attack mitigation, showing significant improvements in network security and trustworthiness. This research provides both theoretical foundations and practical pathways for securing next-generation intelligent wireless networks empowered by Agentic AI.

Technology Category

• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Philosophy and Ethics of AI: Privacy & Security
• Multiagent Systems: Agent/AI Theories and Architectures

Application Category

• Search and Retrieval-Augmented AI: Agentic search
• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

Intellicise (Intelligent and Concise) wireless network is the main direction of the evolution of future mobile communication systems, a perspective now widely acknowledged across academia and industry. As a key technology within it, Agentic AI has garnered growing attention due to its advanced cognitive capabilities, enabled through continuous perception-memory-reasoning-action cycles. This paper first analyses the unique advantages that Agentic AI introduces to intellicise wireless networks. We then propose a structured taxonomy for Agentic AI-enhanced secure intellicise wireless networks. Building on this framework, we identify emerging security and privacy challenges introduced by Agentic AI and summarize targeted strategies to address these vulnerabilities. A case study further demonstrates Agentic AI's efficacy in defending against intelligent eavesdropping attacks. Finally, we outline key open research directions to guide future exploration in this field.

Problem

• Agentic AI
• Intellicise wireless networks
• security
• privacy
• intelligent eavesdropping

Innovation

• Agentic AI
• Intellicise wireless networks
• security and privacy
• intelligent eavesdropping defense
• structured taxonomy