Feng, X., Zhang, Y., Meng, M. H., & Teo, S. G. (2022). Detecting Contradictions from CoAP RFC Based on Knowledge Graph. Lecture Notes in Computer Science, 170–189. https://doi.org/10.1007/978-3-031-23020-2_10
Abstract:
Due to the boom of Internet of Things (IoT) in recent years, various IoT devices are connected to the internet and communicate with each other through web protocols such as the Constrained Application Protocol (CoAP). These web protocols are typically defined and described in the Request for Comments (RFC) documents, which are written in natural or semi-formal languages. Since developers largely follow the RFCs when implementing web protocols, the RFCs have become the de facto protocol specifications. Therefore, it is desirable to ensure that the technical details being described in the RFC are consistent, to avoid technological issues, incompatibility, security risks or even legal concerns. In this work, we propose RFCKG, a knowledge graph based contradictions detection tool for CoAP RFC. Our approach can automatically parse the RFC documents and construct knowledge graphs from them through entity extraction, relation extraction, and rule extraction. It then conducts an intra-entity and inter-entity consistency checking over the generated knowledge graph. We implement RFCKG and apply it to the main RFC (RFC7252) of CoAP, one of the most extensively used messaging protocols in IoT. Our evaluation shows that RFCKG manages to detect both direct contradiction and conditional contradictions from the RFC.
License type:
Publisher Copyright
Funding Info:
There was no specific funding for the research done
Description:
This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-031-23020-2_10