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  • 标题:Combined scaled manhattan distance and mean of horner’s rules for keystroke dynamic authentication
  • 本地全文:下载
  • 作者:Didih Rizki Chandranegara ; Hardianto Wibowo ; Agus Eko Minarno
  • 期刊名称:TELKOMNIKA (Telecommunication Computing Electronics and Control)
  • 印刷版ISSN:2302-9293
  • 出版年度:2020
  • 卷号:18
  • 期号:2
  • 页码:770-775
  • DOI:10.12928/telkomnika.v18i2.14815
  • 出版社:Universitas Ahmad Dahlan
  • 摘要:Account security was determined by how well the security techniques applied by the system were used. There had been many security methods that guaranteed the security of their accounts, one of which was Keystroke Dynamic Authentication. Keystroke Dynamic Authentication was an authentication technique that utilized the typing habits of a person as a security measurement tool for the user account. From several research, the average use in the Keystroke Dynamic Authentication classification is not suitable, because a user's typing speed will change over time, maybe faster or slower depending on certain conditions. So, in this research, we proposed a combination of the Scaled Manhattan Distance method and the Mean of Horner's Rules as a classification method between the user and attacker against the Keystroke Dynamic Authentication. The reason for using Mean of Horner’s Rules can adapt to changes in values over time and based on the results can improve the accuracy of the previous method.
  • 关键词:authentication; biometric authentication; keystroke dynamic authentication; mean of horner’s rules; scaled manhattan distance;
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