Comparing anomaly-detection algorithms for keystroke dynamics
By Kevin S. Killourhy, Roy A. Maxion. 2009 IEEE/IFIP International Conference on Dependable Systems & Networks, 2009
580 citations recorded by the source corpus.
Subfields: Information Systems, Human-Computer Interaction, Signal Processing
View Paper: https://www.semanticscholar.org/paper/8549c708f1b408ffaeb93f9e8114a7f413665f31
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems
- Shigang Yue
- Romit Roy Choudhury
- Damon L. Woodard
- Pin Shen Teh
- Salil Banerjee
- Haining Wang
- Andrew Beng Jin Teoh
In Human-Computer Interaction
In Signal Processing
- Shigang Yue
- Romit Roy Choudhury
- Damon L. Woodard
- Pin Shen Teh
- Wenyuan Xu
- Salil Banerjee
- Haining Wang
- Suhrid Balakrishnan
Citations in the corpus
- You Are How You Touch: User Verification on Smartphones via Tapping Behaviors (2014, background): “Keystroke dynamics, as one of the behavioral biometrics, has been extensively studied in distinguishing users by the way they type on a computer keyboard [3, 15, 24, 28].”
- A Survey of Keystroke Dynamics Biometrics (2013, methodology): “Common measure used to compute distance score introduced in the literature included but is not limited to Euclidean [77, 120, 121], Manhattan [99, 122, 123], Bhattacharyya [81, 124], Mahalanobis [125], degree of disorder [43, 76, 126], and direction similarity measure [3]. to identify and classify p”
- Biometric Authentication and Identification using Keystroke Dynamics: A Survey (2012, background): “Killourhy & Maxion [91] 1,3 Manhattan() S C 51 20400 - 9.”
- AccelPrint: Imperfections of Accelerometers Make Smartphones Trackable (2014, methodology): “Electromagnetic waves [65], acoustic signals [71], timing events [38], and specialized software [36] were exploited to intercept the keystrokes with high accuracy.”
- Tapprints: your finger taps have fingerprints (2012, background): “Researchers exploit electromagnetic waves [18], acoustic signals [27], timing events [14], and specialized software [28] to intercept the typed content with high accuracy.”
- HMOG: New Behavioral Biometric Features for Continuous Authentication of Smartphone Users (2015, unknown): “For instance, SM and SVM were top performers in a study on keystroke authentication of desktop users by Killourhy and Maxion [20].”