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A dictionary attack in a biometric system entails the use of a small number of strategically generated images or tem- plates to successfully match with a large number of identi- ties, thereby compromising security. We focus on dictionary attacks at the template level, specifically the IrisCodes used in iris recognition systems. We present an hitherto unknown vulnerability wherein we mix IrisCodes using simple bit- wise operators to generate alpha-mixtures —alpha-wolves (combining a set of “wolf” samples) and alpha-mammals (combining a set of users selected via search optimization) that increase false matches. We evaluate this vulnerabil- ity using the IITD, CASIA-IrisV4-Thousand and Synthetic datasets, and observe that an alpha-wolf (from two wolves) can match upto 71 identities @FMR=0.001%, while an alpha-mammal (from two identities) can match upto 133 other identities @FMR=0.01% on the IITD dataset.
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Biologically Inspired Multi-Robot System based on Wolf Hunting Behavior
Studies involving the group predator behavior of wolves have inspired multiple robotic architectures to mimic these biological behaviors in their designs and research. In this work, we aim to use robotic systems to mimic wolf packs' single and group behavior. This work aims to extend the original research by Weitzenfeld et al [7] and evaluate under a new multi-robot robot system architecture. The multiple robot architecture includes a 'Prey' pursued by a wolf pack consisting of an 'Alpha' and 'Beta' robotic group. The Alpha Wolf' will be the group leader, searching and tracking the 'Prey.' At the same time, the multiple Beta 'Wolves' will follow behind the Alpha, tracking and maintaining a set distance in the formation. The robotic systems used are multiple raspberry pi-robots designed in the USF bio-robotics lab that use a combination of color cameras and distance sensors to assist the Beta 'Wolves' in keeping a set distance between the Alpha "Wolf" and themselves. Several experiments were performed in simulation, using Webots, and with physical robots. An analysis was done comparing the performance of the physical robot in the real world to the virtual robot in the simulated environment.
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- Award ID(s):
- 1703225
- PAR ID:
- 10519508
- Editor(s):
- Weitzenfeld, A
- Publisher / Repository:
- University of South Florida
- Date Published:
- Subject(s) / Keyword(s):
- Wolf Packs, Computer Vision, Webots
- Format(s):
- Medium: X
- Location:
- Tampa, FL
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.5038/YCJK4503
