Intent-Based Network Policy to Solution Architecting Recommendations

Abstract

The semantic diversity of policies written by people with different IT literacy to achieve certain network security or performance goals created ambiguity to otherwise straightforward solution implementations. In this project, an intent-aware solution recommender is designed to decode semantic cues in network policies written by various demographics for robust solution recommendations. A novel policy analyzer is designed to extract the intrinsic networking intents from ICT policies to provide context-specific solution recommendations. A custom network-aware intent recognizer is trained on a small keywords-to-intents dataset annotated by domain experts using NLP algorithms in AWS comprehend. The bin-of-words model is then used to classify sentences in the policies into predicted ‘intent' class. A collaborative filtering recommendation system using crowd-sourced ground-truth is designed to suggest optimal architecting solutions to achieve the requirements outlined in ICT policies.

Toward Intent-Based Network Automation for Smart Environments: A Healthcare 4.0 Use Case

“…Thus, lately, a natural language approach started to emerge as a means to express intent. For example, the authors, in [21], utilized Amazon voice-assisted technologies and a Latent Dirichlet Allocation (LDA) NLP approach to perform the intent refinement. The framework includes intents related to five network scenarios, namely authentication, network security, performance, access control, and self-healing.…”