Test for Detection of Weak Graphic Passwords in Passpoint Based on the Mean Distance between Points
| Autor: | Lisset Suárez-Plasencia, Carlos Miguel Legón-Pérez, Joaquín A. Herrera-Macías, Omar Rojas, Guillermo Sosa-Gómez, Luis R. Piñeiro-Díaz |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
K-function
Physics and Astronomy (miscellaneous) Computer science mean distance Passpoint weak graphical passwords authentication access control General Mathematics Access control 02 engineering and technology 01 natural sciences k-nearest neighbors algorithm 010104 statistics & probability QA1-939 0202 electrical engineering electronic engineering information engineering Computer Science (miscellaneous) 0101 mathematics Password Authentication business.industry Pattern recognition Small sample Function (mathematics) Test (assessment) Chemistry (miscellaneous) 020201 artificial intelligence & image processing Artificial intelligence business Mathematics |
| Zdroj: | Symmetry; Volume 13; Issue 5; Pages: 777 Symmetry, Vol 13, Iss 777, p 777 (2021) |
| ISSN: | 2073-8994 |
| DOI: | 10.3390/sym13050777 |
| Popis: | This work demonstrates the ineffectiveness of the Ripley’s K function tests, the distance to the nearest neighbor, and the empty space function in the Graphical Authentication scenario with Passpoint for the detection of non-random graphical passwords. The results obtained show that none of these tests effectively detect non-random graphical passwords; the reason for their failure is attributed to the small sample of the spatial pattern in question, where only the five points of the graphical password are analyzed. Consequently, a test based on mean distances is proposed, whose experiments show that it detects with good efficiency non-random graphical passwords in Passpoint. The test was designed to be included in the Graphical Authentication systems with Passpoint to warn the user about a possibly weak password during the registration phase, and in this way, the security of the system is increased. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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