Distributing Intelligence in 6G Programmable Data Planes for Effective In-Network Intrusion Prevention
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2024
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866908362780704768 |
|---|---|
| author | Spina, Mattia G. De Rango, Floriano Scalzo, Edoardo Guerriero, Francesca Iera, Antonio |
| author_facet | Spina, Mattia G. De Rango, Floriano Scalzo, Edoardo Guerriero, Francesca Iera, Antonio |
| contents | The problem of attacks on new generation network infrastructures is becoming increasingly relevant, given the widening of the attack surface of these networks resulting from the greater number of devices that will access them in the future (sensors, actuators, vehicles, household appliances, etc.). Approaches to the design of intrusion detection systems must evolve and go beyond the traditional concept of perimeter control to build on new paradigms that exploit the typical characteristics of future 5G and 6G networks, such as in-network computing and intelligent programmable data planes. The aim of this research is to propose a disruptive paradigm in which devices in a typical data plane of a future programmable network have anomaly detection capabilities and cooperate in a fully distributed fashion to act as an ML-enabled Intrusion Prevention System ``embedded" into the network. The reported proof-of-concept experiments demonstrate that the proposed paradigm allows working effectively and with a good level of precision while occupying overall less CPU and RAM resources of the devices involved. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_24013 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Distributing Intelligence in 6G Programmable Data Planes for Effective In-Network Intrusion Prevention Spina, Mattia G. De Rango, Floriano Scalzo, Edoardo Guerriero, Francesca Iera, Antonio Networking and Internet Architecture Cryptography and Security Optimization and Control The problem of attacks on new generation network infrastructures is becoming increasingly relevant, given the widening of the attack surface of these networks resulting from the greater number of devices that will access them in the future (sensors, actuators, vehicles, household appliances, etc.). Approaches to the design of intrusion detection systems must evolve and go beyond the traditional concept of perimeter control to build on new paradigms that exploit the typical characteristics of future 5G and 6G networks, such as in-network computing and intelligent programmable data planes. The aim of this research is to propose a disruptive paradigm in which devices in a typical data plane of a future programmable network have anomaly detection capabilities and cooperate in a fully distributed fashion to act as an ML-enabled Intrusion Prevention System ``embedded" into the network. The reported proof-of-concept experiments demonstrate that the proposed paradigm allows working effectively and with a good level of precision while occupying overall less CPU and RAM resources of the devices involved. |
| title | Distributing Intelligence in 6G Programmable Data Planes for Effective In-Network Intrusion Prevention |
| topic | Networking and Internet Architecture Cryptography and Security Optimization and Control |
| url | https://arxiv.org/abs/2410.24013 |