@inproceedings{abdrabou2018mum2,
 abstract = {Gesture-based authentication systems are gaining increasing attention from the research community due to their promising usability. However, the scalability of these systems has not been properly investigated against the number of users and the number of gestures. Accordingly, in this paper, we explore the scalability of mid-air gesture-based systems in both aforementioned dimensions to enhance the already existing systems. We implemented a gesture-based authentication model with 20 gestures and we invited 39 users for data collection. A Support Vector Machine (SVM) classifier with Grid search cross-validation was used for training to prove the concept of the model's prototype. The obtained results proved that with the upscaling of the system from the aspect of the number of users, performance gets worse. On the other hand, as gestures introduced to the system increases, the performance improves.},
 acmid = {3289725},
 address = {New York, NY, USA},
 author = {Abdrabou, Yasmeen and Mourad, Nadeen and Elmougy, Amr},
 booktitle = {Proceedings of the 17th International Conference on Mobile and Ubiquitous Multimedia},
 doi = {10.1145/3282894.3289725},
 isbn = {978-1-4503-6594-9},
 keywords = {Behavioral biometrics, Gestures, User Authentication, User Identification},
 location = {Cairo, Egypt},
 numpages = {7},
 pages = {351--357},
 publisher = {ACM},
 series = {MUM 2018},
 title = {Exploring the Scalability of Behavioral Mid-air Gestures Authentication},
 url = {https://www.unibw.de/usable-security-and-privacy/publikationen/pdf/abdrabou2018mum2.pdf},
 year = {2018}
}