---
res:
  bibo_abstract:
  - Machine learning systems are increasingly integrated into security-relevant applications,
    making their vul-nerability to adversarial examples a potential risk. Banknote
    authentication is one such use case that ensures trustworthiness in financial
    transactions. In addition to traditional security features, the printing technique
    of banknotes itself is leveraged for authentication. The Intaglio printing produces
    particularly fine print structures that can be analyzed and differentiated using
    spatial frequency analysis, e.g. the wavelet packet transform. Ap-propriate feature
    engineering in the wavelet packet tree allows the extraction of features enabling
    fast and reliable authentication. This paper presents an approach that generates
    adversarial examples by manipulating the feature space, classifying counterfeit
    banknote specimens as genuine. To this end, the variance of the wavelet coefficient
    distribution of individual detail nodes in the wavelet packet tree is increased.
    The approach leads to minimally perturbed images that are visually indistinguishable
    from the original input. The majority of pixels remain unchanged, i.e. 77% for
    the lower-quality and 86% for the high-quality counterfeit. Furthermore, the limitations
    of this approach are discussed, shedding light on its applicability and potential
    challenges.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Julian
      foaf_name: Knaup, Julian
      foaf_surname: Knaup
      foaf_workInfoHomepage: http://www.librecat.org/personId=79206
  - foaf_Person:
      foaf_givenName: Christoph-Alexander
      foaf_name: Holst, Christoph-Alexander
      foaf_surname: Holst
      foaf_workInfoHomepage: http://www.librecat.org/personId=64782
  - foaf_Person:
      foaf_givenName: Volker
      foaf_name: Lohweg, Volker
      foaf_surname: Lohweg
      foaf_workInfoHomepage: http://www.librecat.org/personId=1804
    orcid: 0000-0002-3325-7887
  bibo_doi: 10.1109/rtsi61910.2024.10761182
  dct_date: 2024^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/979-8-3503-6214-5
  dct_language: eng
  dct_publisher: IEEE@
  dct_subject:
  - Printing
  - Technological innovation
  - Wavelet domain
  - Perturbation methods
  - Authentication
  - Feature extraction
  - Wavelet analysis
  - Wavelet packets
  - Security
  - Wavelet coefficients
  dct_title: 'Hidden in Plain Sight: Adversarial Attack on Wavelet-Based Banknote
    Authentication@'
...