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In forensic investigations, the recovering of latent fingerprints is one of the most essential issues. Driven by human experts, today this process is very time consuming. An automation of both examination of suspicious areas and acquisition of fingerprints lead on the one hand to the covering of larger surfaces and on the other hand to significant speed up of the evidence collection. This work presents an experimental study on capabilities of chromatic white-light sensor (CWL) regarding the contact-less localization of latent fingerprints on differently challenging substrates. The fully automatic CWL-based system is implemented from the acquisition through the feature extraction right up to the classification. The key objective of the work is to develop a methodological approach for the quantitative evaluation of the localization success. Based on the proposed performance measures, the optimal system parameters such as scan resolution, extracted features and classification scheme are specified dependent on the surface material. Our experiments from an actual project with the sensor industry partner show convincing localization performance on easy-to-localize and adequate performance on moderate-to-localize substrates. The hard-to-localize substrates require further improvements of the localization system.
The technology-aided support of forensic experts while investigating crime scenes and collecting traces becomes a more and more important part in the domains of image acquisition and signal processing. The manual lifting of latent fingerprints using conventional methods like the use of carbon black powder is time-consuming and very limited in its scope of application. New technologies for a contact-less and non-invasive acquisition and automatic processing of latent fingerprints, promise the possibilities to inspect much more and larger surface areas and can significantly simplify and speed up the workflow. Furthermore, it allows multiple investigations of the same trace, subsequent chemical analysis of the residue left behind and the acquisition of latent fingerprints on sensitive surfaces without destroying the surface itself. In this work, a FRT MicroProf200 surface measurement device equipped with a chromatic white-light sensor CWL600 is used. The device provides a gray-scale intensity image and 3D-topography data simultaneously. While large area scans are time-consuming, the detection and localization of finger traces are done based on low-resolution scans. The localized areas are scanned again with higher resolution. Due to the broad variety of different surface characteristics the fingerprint pattern is often overlaid by the surface structure or texture. Thus, image processing and classification techniques are proposed for validation and visualization of ridge lines in high-resolution scans. Positively validated regions containing complete or sufficient partial fingerprints are passed on to forensic experts. The experiments are provided on a set of three surfaces with different reflection and texture characteristics, and fingerprints from ten different persons.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).
Application of non-invasive scan technologies for acquisition of latent fingerprints promise a better support of forensic and dactyloscopic experts when securing evidence at crime scenes. Furthermore, non-destructive acquisition preserve the chance of subsequent chemical and forensic analysis of left residue. Based on results of an ongoing research project with sensor industry partners, this paper presents a collection of 28 statistical, gradient-, and spectral density-based features for latent fingerprint detection using low resolution scans. Within this work a chromatic white light (CWL) sensor is used for image acquisition. Furthermore, based on concepts of biometric fusion, a taxonomy for possible fusion strategies is presented and very first results for three different strategies on decision level are discussed. Experimental evaluation is performed based on scans of 1680 latent fingerprints on three different surfaces. The results show very good performance on planar, non-absorbing surfaces with uniform reflection characteristics with an detection rate of 2.51% in the best case. On the other hand difficulties are arising from surfaces with non-uniform/predictable reflection characteristics.
The automated forensic analysis of latent fingerprints poses a new challenge. While for the pattern recognition aspects involved, the required processing steps can be related to fingerprint biometrics, the common biometric model needs to be extended to face the variety of characteristics of different surfaces and image qualities and to keep the chain of custody. Therefore, we introduce a framework for automated forensic analysis of latent fingerprints. The framework consists of a generic process model for multi-branched process graphs w.r.t. security aspects like integrity, authenticity and confidentiality. It specifies a meta-model to store all necessary data and operations in the process, while keeping the chain of custody. In addition, a concept for a technical implementation of the meta-model is given, to build a container format, which suits the needs of an automated forensic analysis in research and application.
Technologies for advancing and supporting criminalistic forensic are an upcoming challenge with rising importance within the domain of multimedia security and forensic. For example the acquisition and automated analysis of latent fingerprints, using high resolution 3D scanners, appears to be a promising area of research. Within the paper we will give a detailed demarcation of biometric and forensic fingerprint analysis. We will introduce the aim of a partly automated process for forensic fingerprint acquisition, detection, and processing. Based on the idea of splitting the overall scan process into a fast, low resolution coarse scan and a high resolution detailed scan, different approaches and algorithms has to be evaluated, whether they are feasible for detecting latent fingerprints. Referring to the subject of biometrics and emerging applications, this work will show an approach of a novel Fourier-based spectral texture feature for detecting latent fingerprints in low resolution grey-scale images. Our work is based on data that is acquired using a chromatic white light sensor (CWL), which provides intensity and topographic information of the scanned surface areas. While using a very limited set of different surfaces so far, our first experiments have shown good results on flat and non structured surfaces. Using the presented feature, it is possible to detect latent fingerprints on these surfaces. Even on slightly structured surfaces, like wood imitation, the application of the spectral density feature yields promising results. However the first evaluation of the spectral density feature has also shown some serious limitations of its use on low resolution images.
Visibility enhancement and validation of segmented latent fingerprints in crime scene forensics
(2013)
Short Term Template Aging Effects on Biometric Dynamic Handwriting Authentication Performance
(2012)
Investigation of adaptive local threshold segmentation in context of 3D-handwriting forensics
(2016)
First investigation of latent fingerprints long-term aging using chromatic white light sensors
(2013)
Towards a Protection Profile for User-Centric andSelf-Determined Privacy Management in Biometrics
(2018)
Due to the increasing number of complaints alleging privacy violations against companies to data protection authorities, the translation of business goals to system design goals and the subsequent consequences for customers’ privacy poses a challenge for many companies. For this reason, there is a need to bridge the economics of privacy and threats to privacy. To this end, our work relies on the concept of privacy as contextual integrity. This framework defines privacy as appropriate information flows subjected to social norms within particular social contexts or spheres. In this paper, we introduce a preliminary version of a semantic model which aims to relate and provide understanding on how well-established business goals may affect their customers’ privacy by designing IoT devices with permission access, data acquired by sensors, among other factors. Finally, we provide a use case application showing how to use the semantic model. The model aims to be an educational tool for professionals in business informatics during the modeling and designing process of a product which may gather sensitive data or may infer sensitive information, giving an understanding of the interaction of the product and its footprint with diverse actors (humans or machines). In the future, a further complete model of the presented may also target other groups, such as law enforcement bodies, as part of their educational training in such systems.
Steganography embraces several hiding techniques which spawn across multiple domains. However, the related terminology is not unified among the different domains, such as digital media steganography, text steganography, cyber-physical systems steganography, network steganography (network covert channels), local covert channels, and out-of-band covert channels. To cope with this, a prime attempt has been done in 2015, with the introduction of the so-called hiding patterns, which allow to describe hiding techniques in a more abstract manner. Despite significant enhancements, the main limitation of such a taxonomy is that it only considers the case of network steganography. Therefore, this paper reviews both the terminology and the taxonomy of hiding patterns as to make them more general. Specifically, hiding patterns are split into those that describe the embedding and the representation of hidden data within the cover object. As a first research action, we focus on embedding hiding patterns and we show how they can be applied to multiple domains of steganography instead of being limited to the network scenario. Additionally, we exemplify representation patterns using network steganography.
Steganographic and covert communication is increasingly used for hiding attacks. Often information hiding is used by attackers in advanced persistent threats in order to operate without being noticed. Attackers might use it to hide data exfiltration or control channels for persistent malware. The paper analyzes potential threats to operational technology by investigating different communication protocols towards their suitability as cover channels. Using a generalized network architecture model and the communication flows of nuclear power plants, the attack potential using information hiding is exemplary assessed. An example for a supply chain attack for command injection is given on the foundation of the OPC UA protocol and an off-theshelf programmable logic controller. Subsequently, recommendations for a strategic and operational preparation for operators towards the prevention and detection of information hiding attacks are derived.
Kill Chain Attack Modelling for Hidden Channel Attack Scenarios in Industrial Control Systems
(2020)
Surface classification and detection of latent fingerprints based on 3D surface texture parameters
(2012)
A unified understanding of terms and their applicability is essential for every scientific discipline: steganography is no exception. Being divided into several domains (for instance, text steganography, digital media steganography, and network steganography), it is crucial to provide a unified terminology as well as a taxonomy that is not limited to some specific applications or areas. A prime attempt towards a unified understanding of terms was conducted in 2015 with the introduction of a pattern-based taxonomy for network steganography. Six years later, in 2021, the first work towards a pattern-based taxonomy for steganography was proposed. However, this initial attempt still faced several shortcomings, e.g., the lack of patterns for several steganography domains (the work mainly focused on network steganography and covert channels), various terminology issues, and the need of providing a tutorial on how the taxonomy can be used during engineering and scientific tasks, including the paper-writing process.</p>
<p>As the consortium who published this initial 2021-study on steganography patterns, in this paper we present the first comprehensive pattern-based taxonomy tailored to fit all known domains of steganography, including smaller and emerging areas, such as filesystem steganography and cyber-physical systems steganography. Besides, to make our contribution more effective and promote the use of the taxonomy to advance research on steganography, we also provide a thorough tutorial on its utilization. </p>
<p>Our pattern collection is available at <a href="https://patterns.ztt.hs-worms.de/" target="_blank">https://patterns.ztt.hs-worms.de</a>.</p>