Mohd Noorulfakhri Yaacob
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Mohd Noorulfakhri Yaacob
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Mohd Noorulfakhri, Yaacob
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57218118259

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  • Publication
    Soft Biometrics and Its Implementation in Keystroke Dynamics
    ( 2020-06-17)
    Mohd Noorulfakhri Yaacob
    ;
    Syed Zulkarnain Syed Idrus
    ;
    Wan Nor Ashiqin Wan Ali
    ;
    Wan Azani Wan Mustafa
    ;
    Mohd Aminudin Jamlos
    ;
    Wahab M.H.A.
    Biometrics is a unique art that exists within a person and allows it to be used to differentiate between one another. These biometrics can be divided into two categories namely behaviour and physical such as face, fingerprint, hand, voice and gait. There are previous studies which examine the personal's characteristic or personality as gender, age, cultural, weight, height, colour of hair etc. This personal's characteristic or personality also known as soft biometric. Several previous studies have shown that the use of soft biometric element (one or combination of elements) in the process of identifying individuals can improve the performance of individual recognition. This paper will elaborate and concludes past studies related to the use of soft biometric elements in KD. Several soft biometric elements applied in various methods of recognition on previous studies have been listed and the results of the studies are compared.
  • Publication
    Multiple Fusions Approach for Keystroke Dynamics Verification System with Soft Biometrics
    ( 2020-09-21)
    Mohd Noorulfakhri Yaacob
    ;
    Syed Zulkarnain Syed Idrus
    ;
    Wan Azani Wan Mustafa
    ;
    Mohd Aminudin Jamlos
    ;
    Helmy Abd Wahab M.
    Computer security is a process that controls the entire information system, including network, system and hardware. Important information that must be controlled in a system is the data or information contained in a system. Various methods have been used to ensure that only users with legitimate access to data can use a system. Usernames and passwords have been a common practice by many systems as the first requirement to be fulfilled to access the system, but some systems use the secondary verification for additional confirmation. In this article, Keystroke Dynamics has been used as the user's second level authentication for the systems that use the keyboard to login into a system. A common problem of system intrusions is that the system fails to identify the user who signs in using the keyboard when the login is correct. There is a possibility that someone else tries to break into the system. To ensure and improve users' recognition who use the keyboard to enter their logins into the system, Keystroke Dynamics is used as a next-level verification if the login is correct. Soft biometrics is used in the user authentication process using KD method in this study. The soft biometric elements used in this study are culture, gender, educational level (CGPA - Cumulative Grade Point Average) and region of birth (ROB). All of these four soft biometric elements are expected to enhance capabilities in the user authentication process.
      2  32
  • Publication
    Weighted-KNN Based Analysis of Typing Patterns Across Different Age Groups
    ( 2024-05-10)
    Mohd Noorulfakhri Yaacob
    ;
    Syed Zulkarnain Syed Idrus
    ;
    Abdul Hapes Mohammed
    The use of behavioural biometrics, such as movement patterns and keystroke dynamics, in human identity recognition research to strengthen smartphone security is growing. Users usually secure their phones with a PIN or pattern. This paper uses a smartphone keystroke dynamic open dataset with user age information. This Open Dataset is known as the RHU-Keystroke Dynamics dataset. A dataset classification study was conducted utilising the Weighted K-nearest neighbour (W-KNN) method in order to identify the three age categories with the highest accuracy. The four keystroke features that have been collected in this open dataset are used for this classification. The highest average accuracy obtained from this W-KNN method is 83%. The results of the study are explained with a Confusion Matrix diagram and a Receiver Operating Characteristic (ROC) graph. A classification study using this method has successfully increased accuracy and can be utilized in the use of software, as demonstrated in the results of the study. It is expected that future studies will apply other classification methods to keystroke dynamics.
      27  5
  • Publication
    A Review on Feature Extraction in Keystroke Dynamics
    ( 2020-06-17)
    Mohd Noorulfakhri Yaacob
    ;
    Syed Zulkarnain Syed Idrus
    ;
    Wan Nor Ashiqin Wan Ali
    ;
    Wan Azani Wan Mustafa
    ;
    Mohd Aminudin Jamlos
    ;
    Wahab M.H.A.
    Feature extraction is an important process before an analysis of a data is carry out. Different behaviour of a user while using the keyboard is a feature that need to be identified in the Keystroke Dynamics (KD) study. Example are the difference between typing time between letters, typing speed and the force of a person pressing the keyboard. Past studies related to feature extraction for KD have been described in this paper. Various features that have been used are listed and the results of the study are compared. The results of this writing are expected to help new researchers in the process of evaluating KD.
      31  1