Justinas Rastenis

This article provides a concise overview of the existing tunnels located within the historic cultural heritage site of Gediminas Hill in Vilnius, with particular emphasis on the implications of a recently discovered tunnel. This newly identified tunnel is of particular interest due to its location beneath a retaining wall in close proximity to an adjacent structure. Long-term structural monitoring data indicate that the building has experienced displacement away from the retaining wall. Although the precise cause of this movement remains undetermined, the discovery of the tunnel adjacent to the structure has raised concerns regarding its potential role in the observed displacements. To investigate this hypothesis, a previously developed numerical model was employed to simulate the tunnel’s impact. The simulation results suggest that the tunnel’s construction was executed with careful consideration. During the excavation phase, the retaining wall exhibited displacements in a direction opposite to the expected ground pressure, indicating effective utilization of the wall’s gravitational mass. However, historical records indicate that no retaining structures were present in the area during the tunnel’s initial period of existence. Consequently, an additional simulation phase was introduced to model the behavior of the surrounding loose soil in the absence of retaining support. The results from this phase revealed that the deformations of the retaining wall and the adjacent building were elastically interdependent. The simulated deformation patterns closely matched the temporal trends observed in the monitoring data. These findings support the hypothesis that the tunnel’s construction may have contributed to the displacement of the nearby building.

Organizational security assurance is a complex and multi-dimensional task. One of the biggest threats to an organization is the credulity of phishing attacks for its employees. To prevent attacks, employees must maintain cyber security hygiene and increase their awareness of the cyberattack landscape. In this paper, we investigate how selected Lithuanian education system employees are vulnerable to spear-phishing attacks. In various education organizations, spear-phishing attacks were imitated, and user responses to received emails were monitored and analyzed. Each organization needs a different attention because employee behavior varies. Employees’ reaction time dimension is explored in the research. Based on these results, it appears that the organization has no time for delayed responses. Employees in the education system are highly affected by spear-phishing attacks and need less than one minute to provide attacker-requested data. This illustrates that automated e-mail filtering systems are a key element in the fight against these kinds of attacks.

In this manuscript, we present the results of three-dimensional finite element analyses performed in the cloud of a large-scale model of the Gediminas Hill buildings and the construction remains of the Upper and Lower castles in Vilnius city. The greatest challenge associated with the simulated numerical model is the difficult geological layer surface inclinations and soil–structure interaction behavior prognosis, which require significant computational resources. The purpose of this research work is to present current and possible worst-case scenarios for Gediminas Hill, considering its buildings and construction remains, regarding the stability of its slopes through a safety analysis. The construction of a numerical three-dimensional model of Gediminas Hill allows for us to assess the soil–structure interaction behavior. The results of non-linear analysis on the created model are in agreement with the tendencies observed in direct geodetic measurements and the relevant landslide history.

Cybersecurity solutions are highly based on data analysis. Currently, it is not enough to make an automated decision; it also has to be explainable. The decision-making logic traceability should be provided in addition to justification by referencing different data sources and evidence. However, the existing security ontologies, used for the implementation of expert systems and serving as a knowledge base, lack interconnectivity between different data sources and computer-readable linking to the data source. Therefore, this paper aims to increase the possibilities of ontology-based cyber intelligence solutions, by presenting a security ontology structure for data storage to the ontology from different text-based data sources, supporting the knowledge traceability and relationship estimation between different security documents. The proposed ontology structure is tested by storing data of three text-based data sources, and its application possibilities are provided. The study shows that the structure is adaptable for different text data sources and provides an additional value related to security area extension.

Spamming and phishing are two types of emailing that are annoying and unwanted, differing by the potential threat and impact to the user. Automated classification of these categories can increase the users’ awareness as well as to be used for incident investigation prioritization or automated fact gathering. However, currently there are no scientific papers focusing on email classification concerning these two categories of spam and phishing emails. Therefore this paper presents a solution, based on email message body text automated classification into spam and phishing emails. We apply the proposed solution for email classification, written in three languages: English, Russian, and Lithuanian. As most public email datasets almost exclusively collect English emails, we investigate the suitability of automated dataset translation to adapt it to email classification, written in other languages. Experiments on public dataset usage limitations for a specific organization are executed in this paper to evaluate the need of dataset updates for more accurate classification results.

The amount of fraud on the Internet is increasing along with the availability and the popularity of the Internet around the world. One of the most common forms of Internet fraud is phishing. Phishing attacks seek to obtain a user’s personal or secret information. The variety of phishing attacks is very broad, and usage of novel, more sophisticated methods complicates its automated filtering. Therefore, it is important to form up-to-date and detailed phishing attack taxonomy, which could be used for both human education purposes as well as phishing attack discrete notation. In this paper, we propose an e-mail-based phishing attack taxonomy, which includes six phases of the attack. Each phase has at least one criterion for the attack categorization. Each category is described, and in some cases the categories have sub-classes to present the full variety of phishing attacks. The proposed taxonomy is compared to similar taxonomies. Our taxonomy outperforms other phishing attack taxonomies in numbers of phases, criteria and distinguished classes. Validation of the proposed taxonomy is achieved by adapting it as a phishing attack notation for an incident management system. Taxonomy usage for phishing attack notation increases the level of description of phishing attacks compared to free-form phishing attack descriptions.