One of key elements when implementing e-learning system is integration in already existing system. System implementation begins with a planning process and ends with installation and maintenance. First of all, it is necessary to determine project team and set responsibilities, collect all information about current situation and possible changes. Latvia University of Agriculture has just started to plan implementation of Moodle system, as its e-learning environment. This article attempts to provide answers on some implementation questions during the system development lifecycle process.

Intrusion Detection Systems is defined as a component that analyses system and user operations in computer and network system to protect it from possible intrusions. Current intrusion detection technologies have several shortcomings. Applying mobile agents to intrusion detection design is step forward on better intrusion detection. Mobile-agent based distributed intrusion detection systems are very promising for the following reasons: reduction of data movement, load-balance, flexibility, fault-tolerance, detection of distributed attacks. Hybrid intrusion detection is defined by both the method used to detect attacks and the placement of the system on the network. Intrusion detection system may perform either misuse detection or anomaly detection and may be deployed as network-based or host-based system. This paper proposes to distribute classical intrusion detection model with mobile agents making an agent-based hybrid intrusion detection system. The proposed model can help detect simple intrusions in early stage and also distributed intrusions by monitoring several subjects installed on network. Main benefit from mobile agents in such system is ability to generate separate services for specific tasks and analyze unknown user patterns with several methods of artificial intelligence.

The aim of the paper is to show the general trend of consumption in the Baltic countries. The member states of the European Union attach great importance to the well-being, health and the promotion of healthy lifestyle. In order to be able to make decisions on the future plan of action, COBEREN (Consumer Behaviour Erasmus Network) carried out a project with an aim of studying the food consumption habits in the European Union countries. The obtained results show the consumer habits of each participating state, although not on the regional level. This study will look at the consumption habits in the Baltic countries and find out the nature of consumption in those three states. The statistical method – analysis of variance – was used to analyse the COBEREN data. The main conclusion is that consumers of the Baltic countries do not differ greatly in their consumption habits.

This article presents theoretical and practical aspects of content marketing decisions for the customer value creation in social networks by using the case of the organic farm ʻIlzenberg manor’. Focus of this paper is to determine which content marketing decisions create the biggest value for the customer in social networks. The first part of the paper deals with theoretical insights into the content marketing decisions and their ability to create the customer value in social networks. Findings of theoretical analysis disclose that there are interfaces between content marketing, separate content marketing decisions and the customer value in the context of social networks. Respectively, it leads to an assumption that the usage of content marketing decisions can be valuable for the customer value creation in social networks. The second part of the paper focuses on the case analysis of the organic farm ‘Ilzenberg manor’. In order to determine which content marketing decisions create value for the customer in social networks, authors examine a correlation between separate content marketing decisions and consumer value indicators by using data from ʻIlzenberg manor’ Facebook page. The obtained results expose that not all content marketing decisions create value for the customer in social networks. Hence, it means that a selection of separate content marketing decisions in social networks can be made through the customer value perspective. The article ends with insights, conclusions, limitations and future research possibilities.

Cyberattacks have become a regular part of network activity. To mitigate the risks from possible threats, organisations have implemented firewalls and intrusion detection systems, which can help stop network attacks. The problem is that often the accuracy of these systems is not effective enough. Another part of network security is security information and management platforms. These systems are more advanced versions of Threat Intelligence Platforms, because it is possible to make in-depth analyses of real-time events in a network. This research paper proposes improving intrusion detection system functionality using Open-Source Intelligence. Anomaly-based intrusion detection systems often generate alerts, but these alerts require deeper analysis to understand whether it is a real attack or just a false alarm. By making Open-Source Intelligence requests and evaluating extra information, it is possible to make more precise rules to stop attacks against network infrastructure. Open-Source Intelligence requests are generated directly from the intrusion detection system or with Python scripts based on the organisation’s infrastructure profile. The proposed architecture was experimentally tested by automating Open-Source Intelligence requests and intrusion detection rule generation by Python scripts.