Artikel ; Online: Evaluation and Improvement of Internet Printing Protocol Based on HCPN Model Detection Method
Applied Sciences, Vol 13, Iss 3467, p
2023 Band 3467
Abstract: The Internet Printing Protocol (IPP) is a bridge between hosts and printers, and is supported by more than 98 percent of printers today. In addition to supporting local use, the IPP protocol also supports online use. Although this can expand the scope of ...
| Abstract | The Internet Printing Protocol (IPP) is a bridge between hosts and printers, and is supported by more than 98 percent of printers today. In addition to supporting local use, the IPP protocol also supports online use. Although this can expand the scope of its application, it has also introduced potential risks to user data. IPP has security components that should be able to guarantee confidentiality, integrity, and non-repudiation. In order to verify whether its security components can achieve this goal, this study modeled the 0-RTT authentication process of the IPP protocol based on Petri net theory and CPN Tools, introducing the improved Dolev–Yao adversary model to perform security evaluation on the protocol model. The result showed that the server could not resist the adversary’s replay attacks on early data. Accordingly, we proposed an improved authentication scheme that introduced a random number signature to enhance the server’s anti-replay capability. Using the same attack model to verify, the result proved that the new scheme was feasible and effective. The method used in this article could easily observe the movement of the security protocol message flow and the specific actions of each participant (including the adversary), which ensured researchers could easily locate the protocol defects and make improvements. |
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| Schlagwörter | IPP ; colored Petri nets ; formal analysis ; TLS 1.3 ; 0-RTT ; early data ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999 |
| Sprache | Englisch |
| Erscheinungsdatum | 2023-03-01T00:00:00Z |
| Verlag | MDPI AG |
| Dokumenttyp | Artikel ; Online |
| Datenquelle | BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl) |
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