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In this paper we propose an improved feature extraction for scans using a confocal microscope to reduce the overall analysis time and to increase the recognition accuracy. Our evaluation is based on 3000 printed and 3000 real fingerprints on the three surfaces hard disk platter, overhead foil and compact disk advancing the research from Hildebrandt et al.2 Our goal is to benchmark the feature extraction and recognition of printed fingerprints for the three substrates as well as for the combination thereof. The results indicate a significant reduction of the necessary analysis time to less than one minute as well as an improved recognition rate of up to 99.7 percent for all samples on the three surfaces in comparison to the previously achieved 91.48 percent on two surfaces as reported in Hildebrandt et al.2
Digitized forensics: retaining a link between physical and digital crime scene traces using QR-codes
Watermarking protocols for authentication and ownership protection based on timestamps and holograms
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This course will present an integrative overview of recent work of cryptography, digital watermarking, media forensics, and biometrics in the field of multimedia systems. Recent advances in image, video, and audio processing to achieve security are introduced covering the full range of security aspects: data confidentiality, data integrity and authenticity, and non-repudiation, as well as user identification and authentication.
The first part of the course will introduce symmetric (private-key) and asymmetric (public-key) crypto systems to ensure confidentiality along with authentication techniques to ensure integrity and authenticity. Infrastructure solutions for non-repudiation of digital signatures will be discussed.
Furthermore, the course will describe digital watermarking techniques that include both spatial, spectral, and temporal watermarking algorithms, as well as the approaches and roles of steganography, perceptual hashing techniques, and media forensics. The goal is to show which security aspects can be met by security mechanisms, as well as how all mechanisms can be combined usefully to achieve, for example, data authentication. Additionally, the unique nature of these new technologies relative to intellectual property rights and digital rights management systems (DRM) will be presented.
In the second part of the course, particular emphasis will be placed on user authentication techniques by image and signal processing and multimodal approaches by combining and fusing multiple single biometric traits for more convenient and reliable identification or verification of users. Based on a case-by-case examination of the modalities of face (2D and 3D face analysis), fingerprint (fingerprint image analysis), signature (handwriting analysis of visual and dynamic signals), and voice (speech signals), the underlying technical concepts will be elaborated and design paradigms, as well as performance evaluations, will be given.
This course will present an overview of recent work in modern encryption techniques and recent advances in image, video, audio watermarking, and forensic methods for multimedia data. The course will describe block cipher systems (e.g. DES and AES) and public key systems (e.g. RSA) along with authentication techniques. The course will also describe digital watermarking techniques that include both spatial, spectral, and temporal watermarking algorithms. Particular emphasis will be placed on how encryption and watermarking can be used in the context of the protection of imaging, video, and multimedia systems. The unique nature of these new technologies relative to intellectual property rights will be presented.
This course will present an overview of recent work of media forensics with focus on sensometrics for sensor identification and signal processing for tamper detection. Particularly, we define sensometrics as the application of methods for the analysis and determination of a particular sensor (capturing or sampling device for digital media), whereby the actual application and context in which the original sampling has been performed can vary. For example, for identifying digital cameras, any photographic image can be taken into account, whereas for identifying pen digitizer, sensors for capturing handwriting samples such as signatures can be analyzed. The general fundamentals will be introduced and specific approaches for selected media examples of image, audio and digital handwritten documents will be discussed to show the recent advances and still open problems.
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