Self-defending 6G networks through AI-driven adaptive decoy generation at the edge
Ranil Mukesh M J, Pandiya Rajan G, Prabhu Gopal, Malathy Sathyamoorthy, Aniket S. Nagane, Rakesh Keshava · 2026
Read Self-defending 6G networks through AI-driven adaptive decoy generation at the edge by Ranil Mukesh M J, Pandiya Rajan G, Prabhu Gopal, Malathy Sathyamoorthy, Aniket S. Nagane, Rakesh Keshava (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13434419.txt.
Description
Ranil Mukesh M J and colleagues propose self-defending 6G networks that generate adaptive decoys at the network edge. Next-generation networks promise vast connectivity but also a far larger attack surface, where traditional security models fall short.
Their adaptive decoy framework combines a conditional generative adversarial network, a reinforcement-learning agent based on proximal policy optimisation, and an adversarial feedback loop that learns from new attacks. Simulations on the CIC-IoT-2023 dataset achieved a 97.9 percent detection rate with a 1.3 percent false-positive rate. Network defenders get a proactive, learning decoy system that lures and studies attackers at the edge instead of merely blocking them.
Catalog record
| CREATOR | Ranil Mukesh M J, Pandiya Rajan G, Prabhu Gopal, Malathy Sathyamoorthy, Aniket S. Nagane, Rakesh Keshava |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 77 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |