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Face recognition systems are susceptible to presentation attacks such as printed photo attacks, replay attacks, and 3D mask attacks. These attacks, primarily studied in visible spectrum, aim to obfuscate or impersonate a person’s identity. This paper presents a unique multispectral video face database for face presentation attack using latex and paper masks. The proposed Multispectral Latex Mask based Video Face Presentation Attack (MLFP) database contains 1350 videos in visible, near infrared, and thermal spectrums. Since the database consists of videos of subjects without any mask as well as wearing ten different masks, the effect of identity concealment is analyzed in each spectrum using face recognition algorithms. We also present the performance of existing presentation attack detection algorithms on the proposed MLFP database. It is observed that the thermal imaging spectrum is most effective in detecting face presentation attacks.
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A data‐based private learning framework for enhanced security against replay attacks in cyber‐physical systems
Summary This article develops a data‐based and private learning framework of the detection and mitigation against replay attacks for cyber‐physical systems. Optimal watermarking signals are added to assist in the detection of potential replay attacks. In order to improve the confidentiality of the output data, we first add a level of differential privacy. We then use a data‐based technique to learn the best defending strategy in the presence of worst case disturbances, stochastic noise, and replay attacks. A data‐based Neyman‐Pearson detector design is also proposed to identify replay attacks. Finally, simulation results show the efficacy of the proposed approach along with a comparison of our data‐based technique to a model‐based one.
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- PAR ID:
- 10452687
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- International Journal of Robust and Nonlinear Control
- Volume:
- 31
- Issue:
- 6
- ISSN:
- 1049-8923
- Format(s):
- Medium: X Size: p. 1817-1833
- Size(s):
- p. 1817-1833
- Sponsoring Org:
- National Science Foundation
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