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Firas A. Abdulatif

Bio: Firas A. Abdulatif is an academic researcher. The author has contributed to research in topics: Password. The author has an hindex of 1, co-authored 1 publications receiving 1 citations.
Topics: Password

Papers
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Journal ArticleDOI
01 Feb 2021
TL;DR: The proposed technique allows the user to keep the ease-of-use in the mouse motion, while minimizing the risk of password guessing, in a new password generation technique on the basis of mouse motion and a special case location recognized by the number of clicks.
Abstract: This paper proposes a new password generation technique on the basis of mouse motion and a special case location recognized by the number of clicks to protect sensitive data for different companies. Two, three special locations click points for the users has been proposed to increase password complexity. Unlike other currently available random password generators, the path and number of clicks will be added by admin, and authorized users have to be training on it. This method aims to increase combinations for the graphical password generation using mouse motion for a limited number of users. A mathematical model is developed to calculate the performance of the password. The proposed technique in this paper allows the user to keep the ease-of-use in the mouse motion, while minimizing the risk of password guessing. A comparative evaluation has been conducted against a traditional password. The results show that the proposed approach improves the complexity 200% for fix position technique and two variants technique but more than 200% for three variants technique.

3 citations


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Proceedings ArticleDOI
22 Feb 2023
TL;DR: A coloring bipartite graph (CBG) is the main point in creating new version of the symmetric encryption (SE) scheme as mentioned in this paper , and the security issue of the CBG-SE scheme is determined.
Abstract: A coloring bipartite graph (CBG) is a main point in this work for creating new version of the symmetric encryption (SE) scheme. The security of this version has been increased comparing with other ES schemes, since a shared secret key is generated based on the CBG. The ciphertext of a plaintext reaches to receiver as the CBG. A new experimental result of CBG-SE scheme is presented through study case. The security issue of the CBG-SE scheme is determined. The CBG-SE scheme considers as an alternative insight for symmetric communications with more security.
TL;DR: The you only look once (YOLO) detector has been retrained to better recognize objects in UAV photographs and competes with other deep-learning frameworks such as the faster region convolutional neural network.
Abstract: Received Jun 1, 2022 Revised Jul 15, 2022 Accepted Aug 16, 2022 An unmanned aerial vehicle (UAV) image recognition system in real-time is proposed in this study. To begin, the you only look once (YOLO) detector has been retrained to better recognize objects in UAV photographs. The trained YOLO detector makes a trade-off between speed and precision in object recognition and localization to account for four typical moving entities caught by UAVs (cars, buses, trucks, and people). An additional 1500 UAV photographs captured by the embedded UAV camera are fed into the YOLO, which uses those probabilities to estimate the bounding box for the entire image. When it comes to object detection, the YOLO competes with other deep-learning frameworks such as the faster region convolutional neural network. The proposed system is tested on a wild test set of 1500 UAV photographs with graphics processing unit GPU acceleration, proving that it can distinguish objects in UAV images effectively and consistently in real-time at a detection speed of 60 frames per second.