Doctor's name here
- Bachelor Degree in Computer Science - King Abdulaziz University 2003 - 2007
-Master Degree in IT Security - University of Ontario Institute of Technology 2009 - 2010
-Doctorate Degree in Computer Science - University of Ontario Institute of Technology 2012 - 2015
Publications in Conference and Symposiums :
A. Almehmadi, and K. El-Khatib, "On the Possibility of Insider Threat Prevention Using Intent-Based Access Control (IBAC)," IEEE Systems Journal, vol., no.99, pp.1-12, May 2015
A. Almehmadi, M. Bourque, K. El-Khatib, "A Tweet of the Mind: Automated Emotion Detection for Social Media Using Brain Wave Pattern Analysis," In Proceedings of the International Conference on Social Computing (SocialCom), 2013, vol., no., pp.987-991
A. Almehmadi, and K. El-Khatib, "The state of the art in electroencephalogram and access control," In Proceedings of the Third International Conference on Communications and Information Technology (ICCIT), 2013, pp.49-54, 2013 doi: 10.1109/ICCITechnology.2013.6579521
A. Almehmadi and K. El-Khatib, “Authorized! Access denied, Unauthorized! Access granted,” In Proceedings of the 6th International Conference on Security of Information and Networks (SIN '13), 2013.
A. Almehmadi and K. El-Khatib, “On the possibility of insider threat detection using physiological signal monitoring,” In Proceedings of the 7th International Conference on Security of Information and Networks (SIN '14), ACM, New York, NY, USA, pp. 223-230, 2014.
On the potential of intent-based access control (IBAC) in preventing insider threats
Existing access control mechanisms are based on the concepts of identity enrollment and recognition, and assume that recognized identity is synonymous with ethical actions. However, statistics over the years show that the most severe security breaches have been the results of trusted, authorized, and identified users who turned into malicious insiders. Therefore, demand exists for designing prevention mechanisms. A non-identity-based authentication measure that is based on the intent of the access request might serve that demand. In this thesis, we test the possibility of detecting intention of access using involuntary electroencephalogram (EEG) reactions to visual stimuli. This method takes advantage of the robustness of the Concealed Information Test to detect intentions. Next, we test the possibility of detecting motivation of access, as motivation level corresponds directly to the likelihood of intent execution level. Subsequently, we propose and design Intent-based Access Control (IBAC), a non-identity-based access control system that assesses the risk associated with the detected intentions and motivation levels. We then study the potential of IBAC in denying access to authorized individuals who have malicious plans to commit maleficent acts. Based on the access risk and the accepted threshold established by the asset owners, the system decides whether to grant or deny access requests. We assessed the intent detection component of the IBAC system using experiments on 30 participants and achieved accuracy of 100% using Nearest Neighbor and SVM classifiers. Further, we assessed the motivation detection component of the IBAC system. Results show different levels of motivation between hesitation-based vs. motivation-based intentions. Finally, the potential of IBAC in preventing insider threats by calculating the risk of access using intentions and motivation levels as per the experiments shows access risk that is different between unmotivated and motivated groups. These results demonstrate the potential of IBAC in detecting and preventing malicious insiders.
A Tweet of the Mind: Automated Emotion Detection for Social Media Using Brain Wave Pattern Analysis
While millions of individuals around the globe use social media every second to disseminate, in some form, their emotions and experiences, there are still some situational challenges these individuals face while trying to share experience over social media. This work introduces the idea of using a Brain Computer Interface device to detect human emotion, which is then paired with geo-location information and automatically posted to a popular social media service. A complete architecture of a system that implements this idea is proposed and implemented, where Brain Pattern Analysis is performed using an Electroencephalogram device and a mobile computing device.
|عنوان المرجع||وصف المرجع||رابط المرجع|
On the Possibility of Insider Threat Prevention Using Intent-Based Access Control (IBAC)
|Authorized! access denied, unauthorized! access granted|
|On the Possibility of Insider Threat Detection Using Physiological Signal Monitoring|
|The state of the art in electroencephalogram and access control|