Computer User Profiling Based on Keystroke Analysis

The article concerns the issues related to a computer user verification based on the analysis of a keyboard activity in a computer system. The research focuses on the analysis of a user’s continuous work in a computer system, which constitutes a type of a free-text analysis. To ensure a high level of a users’ data protection, an encryption of keystrokes was implemented. A new method of a computer user profiling based on encrypted keystrokes is introduced. Additionally, an attempt to an intrusion detection based on the \( k \)-NN classifier is performed.

[1]  Kevin Warwick,et al.  Keystroke Dynamics Authentication: A Survey of Free-text Methods , 2013 .

[2]  Przemyslaw Kudlacik,et al.  A new approach to signature recognition using the fuzzy method , 2014, Pattern Analysis and Applications.

[3]  Giancarlo Ruffo,et al.  Keystroke Analysis of Different Languages: A Case Study , 2005, IDA.

[4]  Rafal Doroz,et al.  On-Line Signature Recognition Based on an Analysis of Dynamic Feature , 2013, 2013 International Conference on Biometrics and Kansei Engineering.

[5]  Jiankun Hu,et al.  A k-Nearest Neighbor Approach for User Authentication through Biometric Keystroke Dynamics , 2008, 2008 IEEE International Conference on Communications.

[6]  Camilo Romero Núñez,et al.  Prevalence and risk factors associated with Toxocara canis infection in children. , 2013 .

[7]  Roy A. Maxion,et al.  Comparing anomaly-detection algorithms for keystroke dynamics , 2009, 2009 IEEE/IFIP International Conference on Dependable Systems & Networks.

[8]  Robert Koprowski,et al.  Machine learning, medical diagnosis, and biomedical engineering research - commentary , 2014, BioMedical Engineering OnLine.

[9]  Anil K. Jain,et al.  Keystroke dynamics for user authentication , 2012, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[10]  Jamal Raiyn,et al.  A survey of Cyber Attack Detection Strategies , 2014 .

[11]  Lee Luan Ling,et al.  User authentication through typing biometrics features , 2005 .

[12]  Jugurta R. Montalvão Filho,et al.  On the equalization of keystroke timing histograms , 2006, Pattern Recognit. Lett..

[13]  Przemyslaw Kudlacik,et al.  Computer User Verification Based on Mouse Activity Analysis , 2015, New Trends in Intelligent Information and Database Systems.

[14]  Przemyslaw Kudlacik,et al.  Fuzzy approach for intrusion detection based on user’s commands , 2016, Soft Comput..

[15]  Andrew Beng Jin Teoh,et al.  A Survey of Keystroke Dynamics Biometrics , 2013, TheScientificWorldJournal.

[16]  Khalid Saeed,et al.  An Exploration of Keystroke Dynamics Authentication Using Non-fixed Text of Various Length , 2013, 2013 International Conference on Biometrics and Kansei Engineering.

[17]  Damon L. Woodard,et al.  Biometric Authentication and Identification using Keystroke Dynamics: A Survey , 2012 .

[18]  M. van Zaanen,et al.  Vibration Sensitive Keystroke Analysis , 2009 .

[19]  Rafal Doroz,et al.  The k-NN classifier and self-adaptive Hotelling data reduction technique in handwritten signatures recognition , 2014, Pattern Analysis and Applications.

[20]  Rituparna Chaki,et al.  An approach to classify keystroke patterns for remote user authentication , 2014 .

[21]  Sung-Hyuk Cha,et al.  Keystroke Biometric Identification and Authentication on Long-Text Input , 2010 .

[22]  Malek Ben Salem,et al.  A Survey of Insider Attack Detection Research , 2008, Insider Attack and Cyber Security.