KNN—based 6LoWPAN network intrusion detection method
US12069481B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 5, 2019 |
| Grant date | Aug 20, 2024 |
| Priority date | — |
| Expiry date | May 31, 2041 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04W84/18
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
The present invention relates to an improved KNN-based 6LoWPAN network intrusion detection method. The present invention selects quantifiable security features which can reflect a self-security state of network elements of a 6LoWPAN network for training, and establishes a 6LoWPAN network feature space. The present invention assigns the weights to the features and transfers zero points, to alleviate the bias caused by large and small impact factors and simplify calculation; realizes construction and update of a state data table of network elements by extracting the feature data of network elements in real time, thus forming a normal contour updated according to the real-time state of the network in the feature space of the 6LoWPAN network based on the clustering effect of a KNN algorithm; and the present invention improves the KNN algorithm and redefines a basis for judging the invasion, to meet the requirements for 6LoWPAN network intrusion detection.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.