Multimodal Biometrics for Person Authentication

Unimodal biometric systems have limited effectiveness in identifying people, mainly due to their susceptibility to changes in individual biometric features and presentation attacks. The identification of people using multimodal biometric systems attracts the attention of researchers due to their advantages, such as greater recognition efficiency and greater security compared to the unimodal biometric system. To break into the biometric multimodal system, the intruder would have to break into more than one unimodal biometric system. In multimodal biometric systems: The availability of many features means that the multimodal system becomes more reliable. A multimodal biometric system increases security and ensures confidentiality of user data. A multimodal biometric system realizes the merger of decisions taken under individual modalities. If one of the modalities is eliminated, the system can still ensure security, using the remaining. Multimodal systems provide information on the “liveness” of the sample being introduced. In a multimodal system, a fusion of feature vectors and/or decisions developed by each subsystem is carried out, and then the final decision on identification is made on the basis of the vector of features thus obtained. In this chapter, we consider a multimodal biometric system that uses three modalities: dorsal vein, palm print, and periocular

A Survey on Methods of Image Processing and Recognition for Personal Identification

The network of blood vessels possesses several properties that make a good biometric feature for personal identification: (1) they are difficult to damage and modify; (2) they are difficult to simulate using a fake template; and (3) vein information can represent the liveness of the person. In the process of recognition of the network of blood vessels, we encounter two main difficulties: the first difficulty concerns the enhancement of the image of blood vessels obtained from the camera working in visible and/or infrared light, and the second one concerns the process of extraction of features and methods of classification. In the first part, this chapter presents the basic methods of preprocessing biometric images. In the second part, we discuss the process of feature extraction with particular emphasis on the feature extraction from images depicting the network of blood vessels. This applies to texture analysis using the co-occurrence matrix, Gabor filtration, moments, and topological features using cross points. In the third part, we present the methods of processing images of the blood vessel network of dorsal part of the hand and wrist. We also discuss the process of reducing the dimensionality of a feature vector using the principal components analysis method

Software development metrics prediction using time series methods

The software development process is an intricate task, with the growing complexity of software solutions and inflating code-line count being part of the reason for the fall of software code coherence and readability thus being one of the causes for software faults and it’s declining quality. Debugging software during development is significantly less expensive than attempting damage control after the software’s release. An automated quality-related analysis of developed code, which includes code analysis and correlation of development data like an ideal solution. In this paper the ability to predict software faults and software quality is scrutinized. Hereby we investigate four models that can be used to analyze time-based data series for prediction of trends observed in the software development process are investigated. Those models are Exponential Smoothing, the Holt-Winters Model, Autoregressive Integrated Moving Average (ARIMA) and Recurrent Neural Networks (RNN). Time-series analysis methods prove a good fit for software related data prediction. Such methods and tools can lend a helping hand for Product Owners in their daily decision-making process as related to e.g. assignment of tasks, time predictions, bugs predictions, time to release etc. Results of the research are presented.Peer ReviewedPostprint (author's final draft

Comprehensive Approach to Increase Cyber Security and Resilience

In this paper the initial results of the European project CAMINO in terms of the realistic roadmap to counter cyber crime and cyber terrorism are presented. The roadmap is built in accordance to so called CAMINO THOR approach, where cyber security is perceived comprehensively in 4 dimensions: Technical, Human, Organizational, and Regulatory

Measuring and improving Agile Processes in a small-size software development company

Context: Agile software development has become commonplace in software development companies due to the numerous benefits it provides. However, conducting Agile projects is demanding in Small and Medium Enterprises (SMEs), because projects start and end quickly, but still have to fulfil customers' quality requirements. Objective: This paper aims at reporting a practical experience on the use of metrics related to the software development process as a means supporting SMEs in the development of software following an Agile methodology. Method: We followed Action-Research principles in a Polish small-size software development company. We developed and executed a study protocol suited to the needs of the company, using a pilot case. Results: A catalogue of Agile development process metrics practically validated in the context of a small-size software development company, adopted by the company in their Agile projects. Conclusions: Practitioners may adopt these metrics in their Agile projects, especially if working in an SME, and customise them to their own needs and tools. Academics may use the findings as a baseline for new research work, including new empirical studies.The authors would like to thank all the members of the QRapids H2020 project consortium.Peer ReviewedPostprint (published version

Strategies to manage quality requirements in agile software development: a multiple case study

Agile methods can deliver software that fulfills customer needs rapidly and continuously. Quality requirements (QRs) are important in this regard; however, detailed studies on how companies applying agile methods to manage QRs are limited, as are studies on the rationale for choosing specific QR management practices and related challenges. The aim of this study was to address why practitioners manage QRs as they do and what challenges they face. We also analyzed how existing practices mitigate some of the found challenges. Lastly, we connect the contextual elements of the companies with their practices and challenges. We conducted 36 interviews with practitioners from four companies of varying sizes. Since each company operates in different domains, comparing QR management strategies and related challenges in different contexts was possible. We found that the companies apply proactive, reactive, and interactive strategies to manage QRs. Additionally, our study revealed 40 challenges in six categories that companies applying agile methods may face in QR management. We also identified nine contextual elements that affect QR management practice choices and which, importantly, can explain many related challenges. Based on these findings, we constructed a theoretical model about the connection between context, QR management practices, and challenges. Practitioners in similar contexts can learn from the practices identified in this study. Our preliminary theoretical model can help other practitioners identify what challenges they can expect to face in QR management in different developmental contexts as well as which practices to apply to mitigate these challenges.This work was supported by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 732253.Peer ReviewedPostprint (published version

Continuously assessing and improving software quality with software analytics tools: a case study

In the last decade, modern data analytics technologies have enabled the creation of software analytics tools offering real-time visualization of various aspects related to software development and usage. These tools seem to be particularly attractive for companies doing agile software development. However, the information provided by the available tools is neither aggregated nor connected to higher quality goals. At the same time, assessing and improving software quality has also been a key target for the software engineering community, yielding several proposals for standards and software quality models. Integrating such quality models into software analytics tools could close the gap by providing the connection to higher quality goals. This study aims at understanding whether the integration of quality models into software analytics tools provides understandable, reliable, useful, and relevant information at the right level of detail about the quality of a process or product, and whether practitioners intend to use it. Over the course of more than one year, the four companies involved in this case study deployed such a tool to assess and improve software quality in several projects. We used standardized measurement instruments to elicit the perception of 22 practitioners regarding their use of the tool. We complemented the findings with debriefing sessions held at the companies. In addition, we discussed challenges and lessons learned with four practitioners leading the use of the tool. Quantitative and qualitative analyses provided positive results; i.e., the practitioners’ perception with regard to the tool’s understandability, reliability, usefulness, and relevance was positive. Individual statements support the statistical findings and constructive feedback can be used for future improvements. We conclude that potential for future adoption of quality models within software analytics tools definitely exists and encourage other practitioners to use the presented seven challenges and seven lessons learned and adopt them in their companies.Peer ReviewedPostprint (published version

Tight Arms Race: Overview of Current Malware Threats and Trends in Their Detection

Cyber attacks are currently blooming, as the attackers reap significant profits from them and face a limited risk when compared to committing the "classical" crimes. One of the major components that leads to the successful compromising of the targeted system is malicious software. It allows using the victim's machine for various nefarious purposes, e.g., making it a part of the botnet, mining cryptocurrencies, or holding hostage the data stored there. At present, the complexity, proliferation, and variety of malware pose a real challenge for the existing countermeasures and require their constant improvements. That is why, in this paper we first perform a detailed meta-review of the existing surveys related to malware and its detection techniques, showing an arms race between these two sides of a barricade. On this basis, we review the evolution of modern threats in the communication networks, with a particular focus on the techniques employing information hiding. Next, we present the bird's eye view portraying the main development trends in detection methods with a special emphasis on the machine learning techniques. The survey is concluded with the description of potential future research directions in the field of malware detection

Computational method for obtaining filiform Lie algebras of arbitrary dimension

This paper shows a new computational method to obtain filiform Lie algebras, which is based on the relation between some known invariants of these algebras and the maximal dimension of their abelian ideals. Using this relation, the law of each of these algebras can be completely determined and characterized by means of the triple consisting of its dimension and the invariants z1 and z2. As examples of application, we have included a table showing all valid triples determining filiform Lie algebras for dimension 13

A particular type of non-associative algebras and graph theory

Evolution algebras have many connections with other mathematical fields, like group theory, stochastics processes, dynamical systems and other related ones. The main goal of this paper is to introduce a novel non-usual research on Discrete Mathematics regarding the use of graphs to solve some open problems related to the theory of graphicable algebras, which constitute a subset of those algebras. We show as many our advances in this field as other non solved problems to be tackled in future