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Dergiler / Istanbul University Journal of Electrical and Electronics Engineering / 2004 / Cilt: 4 - Sayı: 1

User identification at logon via keystroke dynamics

İbrahim SOĞUKPINAR
Levent YALÇIN
Sayfa
995–1005
Yayın Tarihi
2022-10-18
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Also this system makes difficult to system logon even if the password is known by the hypothesis of distinguishing users according to their typing rhythms is possible.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Main goal of information system security is to protect the information by preventing unauthorized users to log on system and provide to log on system only authorized users.
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Temel Bulgular & Veri:For this goal, it is necessary to distinguish the authorized and unauthorized users.
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Sonuç & Katkı:Also this system makes difficult to system logon even if the password is known by the hypothesis of distinguishing users according to their typing rhythms is possible.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

Abstract

Main goal of information system security is to protect the information by preventing unauthorized users to log on system and provide to log on system only authorized users. For this goal, it is necessary to distinguish the authorized and unauthorized users. In this study, a security method, which doesn't require an extra hardware, was designed according to this goal. Also this system makes difficult to system logon even if the password is known by the hypothesis of distinguishing users according to their typing rhythms is possible.

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Bu Makaleye Atıf Yap

SOĞUKPINAR, İ., YALÇIN, L. (2022). User identification at logon via keystroke dynamics. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 4 - Sayı: 1, 995–1005. https://ajindex.com/articles/543884

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Kaynakça (13)

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  10. CHO, S. & HAN, C. & HAN, D. H. & KIM, H., “Web Based Keystroke Dynamics Identity Verification using Neural Network”, Journal of Organizational Computing and Electronic Commerce, Vol. 10, No. 4, pp. 295-307, 2000
  11. PEACOCK, A., “Learning User Keystroke Latency Patterns”, (Preliminary Report), http:/ /pel.cs.byu.edu/~alen/personal/ CourseWork/cs572/KeystrokePaper.ps, 2000
  12. GUVEN,A. & SOĞUKPINAR, İ. “Computer and Network Security System Design via Keystroke Dynamics”,. BAS2000, Ankara., 2000
  13. MONROSE, F. & RUBIN, A. D., “Keystroke Dynamics as a Biometric for Authentication”, Future Generation Computing Systems (FGCS) Journal: Security on the Web (special issue). March 2000 [14] SONG, D. & VENABLE, P. & PERRIG, A. “User Recognition by Keystroke Latency Pattern Analysis”, http://paris.cs.berkeley.edu /~perrig/projects/keystroke,1997.