الفهرس 
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Abstract
Securing the process of accessing cloud computing environment is one of the
most important and sensitive fields in scientific research. Cloud Computing
security faces daily new drawbacks and intruders. This thesis aims to enhance
the presented performance from authentication systems based on keystroke
dynamics (KD) that is used for accessing cloud environment. Between the
different physiological and behavioral biometric techniques that is used for
securing the cloud computing, keystrokes dynamics is the appropriate choice to
be presented. It is the most user-friendly technique between other biometric
techniques as users can’t know that they have been tested from the system, and
it doesn’t need any external hardware. Different types of authentication
techniques will be described in detail in additional to the drawbacks and the
threaten attacks which faces them. The thesis targets the using of a multi factor
mechanism based on biometric keystroke technique for higher level of security.
Systems access decision is taken based on the predefined matching thresholds
between the new access sample from the user and the referenced stored
template. The proposed method mainly centers on the usage way of datasets for
creating the user’s referenced template and how this way can totally affect the
decision of the system. The thesis explains the processes of using a published
dataset and the way of collecting a personal dataset from various users. A
publicly shared keystroke dataset named CMU is used for implementing the
proposed methodology. This dataset is analyzed for removing the typing outliers