Ronny Merkel

On non-invasive 2D and 3D Chromatic White Light image sensors for age determination of latent fingerprints

The feasibility of 2D-intensity and 3D-topography images from a non-invasive Chromatic White Light (CWL) sensor for the age determination of latent fingerprints is investigated. The proposed method might provide the means to solve the so far unresolved issue of determining a fingerprints age in forensics. Conducting numerous experiments for an indoor crime scene using selected surfaces, different influences on the aging of fingerprints are investigated and the resulting aging variability is determined in terms of inter-person, intra-person, inter-finger and intra-finger variation. Main influence factors are shown to be the sweat composition, temperature, humidity, wind, UV-radiation, surface type, contamination of the finger with water-containing substances, resolution and measured area size, whereas contact time, contact pressure and smearing of the print seem to be of minor importance. Such influences lead to a certain experimental variability in inter-person and intra-person variation, which is higher than the inter-finger and intra-finger variation. Comparing the aging behavior of 17 different features using 1490 time series with a total of 41,520 fingerprint images, the great potential of the CWL technique in combination with the binary pixel feature from prior work is shown. Performing three different experiments for the classification of fingerprints into the two time classes [0, 5 h] and [5, 24 h], a maximum classification performance of 79.29% (kappa=0.46) is achieved for a general case, which is further improved for special cases. The statistical significance of the two best-performing features (both binary pixel versions based on 2D-intensity images) is manually shown and a feature fusion is performed, highlighting the strong dependency of the features on each other. It is concluded that such method might be combined with additional capturing devices, such as microscopes or spectroscopes, to a very promising age estimation scheme.

Privacy preserving challenges: new design aspects for latent fingerprint detection systems with contact-less sensors for future preventive applications in airport luggage handling

This paper provides first ideas and considerations for designing and developing future technologies relevant for challenging privacy-preserving preventive applications of contact-less sensors. We introduce four use-cases: preventive detailed acquisition of fingerprints, coarse scans for fingerprint localisation, separation of overlapping fingerprints and age determination for manipulation detection and automatic securing of evidence. To enable and support these four use-cases in future, we suggest developing four techniques: coarse scans, detailed scans, separation and age determination of fingerprints. We derive a new definition for the separation from a forensic approach: presence detection of overlapping fingerprints, estimation of the number of fingerprints, separation and sequence (order) detection. We discuss main challenges for technical solutions enabling the suggested privacy-preserving use-cases combined with a brief summary of preliminary results from our first experiments. We analyse the legal principles and requirements for European law and the design of the use-cases, which show tendencies for other countries.

Benchmarking contact-less surface measurement devices for fingerprint acquisition in forensic investigations: Results for a differential scan approach with a chromatic white light sensor

With the advent of new contact-less sensors for forensic investigations of latent fingerprint traces, the authors see the need for a benchmarking framework to evaluate existing devices and promising combinations of data acquisition and signal processing techniques. This paper extends the existing benchmarking framework from [1] by categorizing it into properties from a forensic point-of-view (end-user) and a technical point-of-view (scientific-user) and applies a known differential image technique for the subjective evaluation of which traces are visible. We show exemplary results for a chromatic white light (CWL) sensor for the surface quality assessment, using and comparing the experimental setup of 10 surfaces from [1] and additional 10 surfaces, including real-world objects, to determine its potential for detecting latent fingerprints. Using a differential image approach, the particular influence of sensor noise signals is analyzed, showing that this differential approach cannot always be considered as an ideal filter for fingerprint pattern detection.

Statistical detection of malicious PE-Executables for fast offline analysis

While conventional malware detection approaches increasingly fail, modern heuristic strategies often perform dynamically, which is not possible in many applications due to related effort and the quantity of files. Based on existing work from [1] and [2] we analyse an approach towards statistical malware detection of PE executables. One benefit is its simplicity (evaluating 23 static features with moderate resource constrains), so it might support the application on large file amounts, e.g. for network-operators or a posteriori analyses in archival systems. After identifying promising features and their typical values, a custom hypothesis-based classification model and a statistical classification approach using the WEKA machine learning tool [3] are generated and evaluated. The results of large-scale classifications are compared showing that the custom, hypothesis based approach performs better on the chosen setup than the general purpose statistical algorithms. Concluding, malicious samples often have special characteristics so existing malware-scanners can effectively be supported.

General fusion approaches for the age determination of latent fingerprint traces: results for 2D and 3D binary pixel feature fusion

Determining the age of latent fingerprint traces found at crime scenes is an unresolved research issue since decades. Solving this issue could provide criminal investigators with the specific time a fingerprint trace was left on a surface, and therefore would enable them to link potential suspects to the time a crime took place as well as to reconstruct the sequence of events or eliminate irrelevant fingerprints to ensure privacy constraints. Transferring imaging techniques from different application areas, such as 3D image acquisition, surface measurement and chemical analysis to the domain of lifting latent biometric fingerprint traces is an upcoming trend in forensics. Such non-destructive sensor devices might help to solve the challenge of determining the age of a latent fingerprint trace, since it provides the opportunity to create time series and process them using pattern recognition techniques and statistical methods on digitized 2D, 3D and chemical data, rather than classical, contact-based capturing techniques, which alter the fingerprint trace and therefore make continuous scans impossible. In prior work, we have suggested to use a feature called binary pixel, which is a novel approach in the working field of fingerprint age determination. The feature uses a Chromatic White Light (CWL) image sensor to continuously scan a fingerprint trace over time and retrieves a characteristic logarithmic aging tendency for 2D-intensity as well as 3D-topographic images from the sensor. In this paper, we propose to combine such two characteristic aging features with other 2D and 3D features from the domains of surface measurement, microscopy, photography and spectroscopy, to achieve an increase in accuracy and reliability of a potential future age determination scheme. Discussing the feasibility of such variety of sensor devices and possible aging features, we propose a general fusion approach, which might combine promising features to a joint age determination scheme in future. We furthermore demonstrate the feasibility of the introduced approach by exemplary fusing the binary pixel features based on 2D-intensity and 3D-topographic images of the mentioned CWL sensor. We conclude that a formula based age determination approach requires very precise image data, which cannot be achieved at the moment, whereas a machine learning based classification approach seems to be feasible, if an adequate amount of features can be provided.

Reliable provenance information for multimedia data using invertible fragile watermarks

Today, more and more data is available in digital form, ranging from normal text to multimedia data such as image or video data. Since some data is of high sensitivity or undergoes legal restrictions, it is important to obtain more reliable information about the data origin and its transformations, known as data provenance. Unfortunately, current approaches for data provenance neither support multimedia data nor provide mechanisms to ensure reliability of the provenance information. In this paper, we present an approach based on existing watermarking schemes evaluated by a database system. Hence, this approach ensures the reliability of multi media data (e.g., fingerprint data) and its corresponding provenance information. Furthermore, we show how this approach can be applied within a specific database, used for fingerprint verification.

Evaluation of binary pixel aging curves of latent fingerprint traces for different surfaces using a chromatic white light (CWL) sensor

Determining the age of latent fingerprint traces found at crime scenes is an unresolved research challenge since decades. In prior work, we have suggested to use optical, non-invasive image sensory in combination with a new aging feature called binary pixel (shown to have a characteristic logarithmic aging tendency on an ideal hard disk platter surface) to solve this important research issue. In this paper, we want to evaluate the feasibility of this approach for a practical age determination by conducting 30 test series with a total of 1440 scans, investigating ten different surfaces with 3 different samples each. We suggest a three-step procedure: calculate the binary pixel feature, approximate the mathematical aging function using regression and calculate the coefficients of correlation, allowing for a formal evaluation and comparison of the aging property. We report a promising characteristic logarithmic aging property for 18 of the 30 test samples and evaluate possible influences on such property.

A first framework for the development of age determination schemes for latent biometric fingerprint traces using a chromatic white light (CWL) sensor

Since decades, the age determination of latent fingerprint traces left at crime scenes is a challenge to forensic investigators, since fingerprint traces can often only be used in a lawsuit if they can be assigned to the specific time interval of a crime taking place. In this paper, we suggest a six-step framework on how an age determination scheme might be developed for a given application scenario using optical and non-invasive image sensory. We explain and discuss each step of such framework, using three different aging features (the binary pixel feature based on prior work as well as the novel aging features corrosion blob size and corrosion blob amount), which are based on the loss of contrast of a fingerprint on a hard disk platter surface as well as on corrosion properties of fingerprint residue applied to a copper coin surface. We furthermore evaluate different aspects of the scheme in practical experiments, to show its feasibility and conclude, that the steps 1, 3, 5 and 6 of the framework are comparatively easy to be realized, whereas the steps 2 (developing new aging features) and 4 (determining all significant influences on a given aging feature) are challenging, yet possible.

How contact pressure, contact time, smearing and oil/skin lotion influence the aging of latent fingerprint traces: First results for the binary pixel feature using a CWL sensor

Determining the age of latent fingerprint traces found at crime scenes is an unresolved research issue since decades. In prior work, we have suggested to use optical, non-invasive image sensory in combination with a new aging feature called ‘binary pixel’ (shown to have a characteristic logarithmic aging tendency on hard disk platters) to solve this important research challenge. In this paper, we evaluate the influence of the fingerprint application process (such as contact pressure, contact time, smearing of the fingerprint or contamination with skin lotion or oil) on the aging curves of the binary pixel feature (inter-application-factor-variance). We furthermore evaluate differences of fingerprint traces applied in a similar way (intra-application-factor-variance). Examining 25 fingerprint samples of a test subject with a total of 500 scans, we show that the application of substances to a finger seems to increase the present amount of residue and that substances containing water increase the aging speed of a fingerprint trace significantly.

Modelling watermark communication protocols using the CASPER modelling language

In cryptography it is common to evaluate the security of cryptographic primitives and protocols in a computational model, with an attacker trying to break the primitive or protocol in question. To do so formalisation languages like CASPER or CSP (Communication Sequential Processes) and model checkers like FDR (Failures-Divergences Refinement) are used for automatic or semi-automatic machine-based security verification. Here we transfer the idea of machine-based verification of the security of communication protocols from cryptography to the domain of digital watermarking based media security protocols. To allow for such a mainly automatic verification approach, we introduce and illustrate in this paper a six step procedure for the modelling and verification of watermark communication protocols based on application scenario descriptions. The six steps are: First, a modelling of the used communication network and application scenario (as a task) in XML-structures, second, a path search comparing the network and the task and identifying possible watermarking channels, third, a path selection selecting one watermarking channel from the identified alternatives for the protocol realisation, fourth, an automatic CASPER protocol generation from the selected alternative followed by manual adjustments (if necessary), fifth, the CASPER compilation into CSP and sixth, the protocol security(confidentiality, integrity and authenticity) verification via the FDR model checker.