2014
DOI: 10.5120/15541-4274
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Keystroke Dynamic Authentication in Mobile Cloud Computing

Abstract: One of the important challenges in Mobile Cloud Computing (MCC) is related to the authentication of users. There is increasing demand for suitable authentication method for accessing to the shared information via the Internet through Cloud Service Provider (CSP). Personal identification number is the most common mechanism for authentication in mobile devices; however it is not secure way for authenticating users. This work presents a method of authentication which able to identify users based on Keystroke Dyna… Show more

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Cited by 14 publications
(2 citation statements)
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References 58 publications
(42 reference statements)
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“…An important mechanism category is biometric authentication that examines users by identifying individual features , such as physical characteristics and behaviors . This approach is a complementary support for password‐based verifications, which can provide a secure end users access.…”
Section: Intrusion Detection Systemsmentioning
confidence: 99%
“…An important mechanism category is biometric authentication that examines users by identifying individual features , such as physical characteristics and behaviors . This approach is a complementary support for password‐based verifications, which can provide a secure end users access.…”
Section: Intrusion Detection Systemsmentioning
confidence: 99%
“…• Keystroke Static authentication (KSA): The user is asked to type several times a fixed text, like a password in order to build his profile or template. During the identification stage, the user is supposed to provide the same string captured during his enrollment to verify if this way of typing matches the model stored or not (Babaeizadeh et al, 2014;Bours & Mondal, 2015) • Keystroke Dynamic authentication (KDA): The user is required to provide a free text to create his templates. It isn't important what he is typing, but how he is typing it, so the user didn't need to remember his password every time when access to the system (Babaeizadeh et al, 2014;Bours & Mondal, 2015) Multimodal Biometric Systems…”
Section: Keystroke Recognitionmentioning
confidence: 99%