Stylometry as a Reliable Method for Fallback Authentication
| Autor: | Ariful Haque, Nafiz Sadman, Subash Poudyal, Kishor Datta Gupta, Sajib Sen |
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| Rok vydání: | 2020 |
| Předmět: |
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Stop words business.industry Computer science media_common.quotation_subject 02 engineering and technology 010501 environmental sciences computer.software_genre 01 natural sciences Punctuation Authentication (law) Writing style Identification (information) 020204 information systems 0202 electrical engineering electronic engineering information engineering Stylometry Artificial intelligence Set (psychology) business computer Natural language processing 0105 earth and related environmental sciences media_common |
| Zdroj: | 2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON). |
| DOI: | 10.1109/ecti-con49241.2020.9158216 |
| Popis: | Over the decades with advancement in artificial intelligent systems, stylometry has proven to be crucial in authorship attribution. It is an evident that by natural development, writing styles between individuals are unique and cannot be fabricated. Stylometric analysis research has been done for author identification and there is significant progress to recognize an author based on their written texts. This paper aims to evaluate the efficiency o f u sing s tylometry a s a fall back authentication method. We proposed to detect differences between writings on the same topic provided by a set of users and tested whether these differences are enough to use for an authentication system. We observed 74% accuracy in detecting the actual authors and concluded that with additional features the accuracy can be pushed to above 90%. Moreover, we deviced a threshold for authentication of a particular user. We observed that the combination of textual features can support authenticity of the user. We also analyzed the impact of some data cleaning systems like removing stop words and punctuation marks, and how they affected the overall detection outcome. |
| Databáze: | OpenAIRE |
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