Jevgenijus Toldinas

Domain Ontology-Based Generative Component Design Using Feature Diagrams and Meta-programming Techniques

In domains, where great variability of requirements and products exists such as embedded system design domain, a product line (PL) approach is emerging as the most promising design paradigm. The key for the PL implementation is the use of domain analysis and domain modelling methods. We propose to represent domain variability using feature models enriched with lightweight domain ontology. We transform such models into generative component specifications using meta-programming techniques. We suggest: 1) to use domain analysis methods from two perspectives, software engineering and cognitive science; 2) to enrich domain variability models explicitly by contextualization and repurposing (i.e., by lightweight domain ontology); 3) to represent the model using the enriched feature diagrams (EFDs); 4) to encode EFDs using heterogeneous meta-programming.

A Methodology and Tool for Investigation of Artifacts Left by the BitTorrent Client

The BitTorrent client application is a popular utility for sharing large files over the Internet. Sometimes, this powerful utility is used to commit cybercrimes, like sharing of illegal material or illegal sharing of legal material. In order to help forensics investigators to fight against these cybercrimes, we carried out an investigation of the artifacts left by the BitTorrent client. We proposed a methodology to locate the artifacts that indicate the BitTorrent client activity performed. Additionally, we designed and implemented a tool that searches for the evidence left by the BitTorrent client application in a local computer running Windows. The tool looks for the four files holding the evidence. The files are as follows: *.torrent, dht.dat, resume.dat, and settings.dat. The tool decodes the files, extracts important information for the forensic investigator and converts it into XML format. The results are combined into a single result file.

Investigation of Artifacts Left by BitTorrent Client on the Local Computer Operating under Windows 8.1

BitTorrent client application is a popular tool to download large files from Internet, but this application is quite frequently used for illegal purposes that are one of the types of cybercrimes. If order to fight against this type of cybercrime we carried out the research, during which we investigated the evidences left by BitTorrent client application in registry under Windows 8.1 operating system. The experiment was carried out in three steps: installation, download, and uninstallation. The snapshots of registry were taken and compared prior and after each step. Changes in Windows registry were collected and joined into tables. The experiment revealed that BitTorrent client application creates Windows registry artefacts that can contain information which might be used as evidence during an investigation. The evidence remains in the registry even after the removal of the application, although it can really prove the fact of usage of the application only. The investigation of file system can reveal the purpose and the contents of the BitTorrent client session. DOI: http://dx.doi.org/10.5755/j01.itc.44.4.13082

An Ontology-Based Transformation Model for the Digital Forensics Domain

The creation of an ontology makes it possible to form common information structures, to reuse knowledge, to make assumptions within a domain and to analyse every piece of knowledge. In this paper, we aim to create an ontology-based transformation model and a framework to develop an ontology-based transformation system in the digital forensics domain. We describe the architecture of the ontology-based transformation system and its components for assisting computer forensics experts in the appropriate selection of tools for digital evidence investigation. We consider the use of the attributes of Extensible Markup Language document transformation to map the computer forensics ontology and we use the representations in the National Institute of Standards and Technology’s “Computer Forensics Tool Catalog” for aligning one form with the other. DOI: http://dx.doi.org/10.5755/j01.eie.23.3.18337

A Model-Driven Framework to Develop Personalized Health Monitoring

Both distributed healthcare systems and the Internet of Things (IoT) are currently hot topics. The latter is a new computing paradigm to enable advanced capabilities in engineering various applications, including those for healthcare. For such systems, the core social requirement is the privacy/security of the patient information along with the technical requirements (e.g., energy consumption) and capabilities for adaptability and personalization. Typically, the functionality of the systems is predefined by the patient’s data collected using sensor networks along with medical instrumentation; then, the data is transferred through the Internet for treatment and decision-making. Therefore, systems creation is indeed challenging. In this paper, we propose a model-driven framework to develop the IoT-based prototype and its reference architecture for personalized health monitoring (PHM) applications. The framework contains a multi-layered structure with feature-based modeling and feature model transformations at the top and the application software generation at the bottom. We have validated the framework using available tools and developed an experimental PHM to test some aspects of the functionality of the reference architecture in real time. The main contribution of the paper is the development of the model-driven computational framework with emphasis on the synergistic effect of security and energy issues.

Security Level versus Energy Consumption in Wireless Protocols for Internet of Things

The Internet of Things is a rapidly evolving technology, which creates new challenges to security and energy consumption of devices at the various environmental conditions. Wireless communication technologies are one of the bases of IoT. In this paper, we proposed the security requirements of IoT applications to relate with the operating modes of wireless protocols. In addition, we presented the measurement and analysis of energy consumption and data transfer rates of Wi-Fi and Bluetooth protocols, depending on the security requirements of applications and conditions of environment.