Towards Using Police Officers’ Business Smartphones for Contactless Fingerprint Acquisition and Enabling Fingerprint Comparison against Contact-Based Datasets

Recent developments enable biometric recognition systems to be available as mobile solutions or to be even integrated into modern smartphone devices. Thus, smartphone devices can be used as mobile fingerprint image acquisition devices, and it has become feasible to process fingerprints on these devices, which helps police authorities carry out identity verification. In this paper, we provide a comprehensive and in-depth engineering study on the different stages of the fingerprint recognition toolchain. The insights gained throughout this study serve as guidance for future work towards developing a contactless mobile fingerprint solution based on the iPhone 11, working without any additional hardware. The targeted solution will be capable of acquiring 4 fingers at once (except the thumb) in a contactless manner, automatically segmenting the fingertips, pre-processing them (including a specific enhancement), and thus enabling fingerprint comparison against contact-based datasets. For fingertip detection and segmentation, various traditional handcrafted feature-based approaches as well as deep-learning-based ones are investigated. Furthermore, a run-time analysis and first results on the biometric recognition performance are included.

From generic partition refinement to weighted tree automata minimization

Partition refinement is a method for minimizing automata and transition systems of various types. Recently, we have developed a partition refinement algorithm that is generic in the transition type of the given system and matches the run time of the best known algorithms for many concrete types of systems, e.g. deterministic automata as well as ordinary, weighted, and probabilistic (labelled) transition systems. Genericity is achieved by modelling transition types as functors on sets, and systems as coalgebras. In the present work, we refine the run time analysis of our algorithm to cover additional instances, notably weighted automata and, more generally, weighted tree automata. For weights in a cancellative monoid we match, and for non-cancellative monoids such as (the additive monoid of) the tropical semiring even substantially improve, the asymptotic run time of the best known algorithms. We have implemented our algorithm in a generic tool that is easily instantiated to concrete system types by implementing a simple refinement interface. Moreover, the algorithm and the tool are modular, and partition refiners for new types of systems are obtained easily by composing pre-implemented basic functors. Experiments show that even for complex system types, the tool is able to handle systems with millions of transitions.

Building a methodology for secure system software development on the example of operating systems

System software is a cornerstone of any software system, so building secure system software in accordance with requirements of certification authorities and state-of-the-art practices is an important scientific and technical problem. One of possible approaches to cope with the problem is to build a methodology for secure system software development including advanced scientific technologies and industry best practices. The paper presents current results achieved in building such methodology in the following directions. The first one is regulatory framework improvement including development of GOST R specifications defining requirements to formal models of access control policies and their formal verification. The second direction is design and verification of formal models of corresponding security functional requirements. The third direction is application of new and well established technologies of static and run-time analysis of systems software. The considered technologies include static analysis, fuzzing, functional and unit testing as well as testing the system software against formal models of its functional security requirements. The forth direction is development of methods for acquisition of results of all kinds of the analysis and for its analytical processing. All the directions are illustrated by practical examples of application of the methodology to development of Astra Linux operating system distribution that is certified according to the highest evaluation assurance levels.

Classification and Analysis of Static Metric Based Antipattern Detection in Service Computing

Background: Design Pattern is regarded as an essential component for enhancement of system design which can further improve the reusability and maintainability whereas antipattern degrades the quality of the program. Antipatterns are sub-optimal implementation choices which initially appears to be a good concept but later on leads to low code maintainability and higher maintenance costs. Objective: The identification of antipatterns which lead to performance degradation plays an important role in the reduction of expensive work and cost involved in maintenance, redesign, reimplementation, and redeployment. The main motivation is to refactor the source code in order to reduce maintenance efforts. Antipatterns impact reliability, testability and maintainability, but they still lack clear identification because of different interpretations and definition of each antipattern. There is a need for a benchmark to analyze the result generated by antipatterns. Methods: Static and dynamic analysis individually do not suffice for antipattern .A hybrid approach is proposed by combining rule based static analysis with dynamic run time analysis. Before applying the hybrid approach a simple manual validation was done to exclude the type of input which had the least probability of containing antipattern. The approach aims at optimizing the results by inclusion of response time metric measure which can be evaluated at runtime execution of the web service. Results and Conclusion: : The paper focusses on detection of antipatterns from web services based on code level and interface level static metrics .Only a brief overview of dynamic approach for detection is proposed. The future scope of this paper will focus on detection of antipattern based on more number of dynamic metrics and also a comparative analysis of the results generated from static, dynamic and hybrid approach.