This paper discusses the valuable role recommender systems may play in cybersecurity. First, a comprehensive presentation of recommender system types is presented, as well as their advantages and disadvantages, possible applications and security concerns. Then, the paper collects and presents the state of the art concerning the use of recommender systems in cybersecurity; both the existing solutions and future ideas are presented. The contribution of this paper is two-fold: to date, to the best of our knowledge, there has been no work collecting the applications of recommenders for cybersecurity. Moreover, this paper attempts to complete a comprehensive survey of recommender types, after noticing that other works usually mention two–three types at once and neglect the others.

Cybercrime and cybersecurity are like two sides of the same coin: They are opposites but cannot exist without each other. Their mutual relation generates a myriad of ethical issues, ranging from minor to vital. The rapid development of technology will surely involve even more ethical concerns, like the infamous example of a fitness tracking company allegedly paying $10 million worth of ransom. Every cybersecurity solution, tool, or practice has to be ethical by design if it is to protect people and their rights. To identify the ethical issues that cybersecurity/cybercrime might bring about in the future, we conducted the first broad and comprehensive horizon-scanning study since the COVID-19 pandemic arose. As we began this project, nobody had the slightest idea that the coming months would bring the COVID-19 pandemic, and that the reality we had known was about to change dramatically. As it soon became apparent, the deadly coronavirus brought completely new cybersecurity/cybercrime ethical dilemmas to light, and some of the ones known before were transformed or shifted. This article presents the results of our horizon-scanning study concerning the ethical dilemmas that emerged amid the COVID-19 pandemic.

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The subject literature analyses as well as the social life practice show that there has been a progressive lack in the work-life balance of individuals nowadays. As a result, people suffer from disturbances in their physical, mental and social development, and the organisations that employ them suffer from their poorer performance, too. Popularising the knowledge and developing the ability to combine work and the life outside it are one of the major challenges for contemporary societies, all the more since healthy and sustainable lifestyles of the employed individuals foster both their personal development and the development of organisations. The aim of the article is to present the selected results of the Professional workpersonal life. Balance or conflict? study. According to the applied methodology, after the aim and the subject of the study were determined, the diagnostic poll method was employed. Based on the theoretical scientific analyses present in the subject literature an original questionnaire was designed, which then was responded to by 800 employers working for 80 Polish companies. The main conclusion drawn from the empirical research results pointed out strong work ethos and progressive imbalance in the professional workpersonal life relations that the people in the studied group were not aware of.

The development of cyberspace has brought about innumerable advantages for the mankind. However, it also came with several serious drawbacks; as cyberspace evolves, so does cybercrime. Since the birth of cyberspace, individuals, groups and whole nations have been engaging in computer-related offences of various significance and impact, trying to exploit systems’ vulnerabilities, disseminate malicious software and steal data or funds. The concept of a hacker has entered the collective consciousness and become an intrinsic element of popular culture. However, there are hackers, or rather, cyberspace actors, who challenge this common view. This paper presents three types of such people, namely hacktivists, members of cyber militias and Internet trolls. Although they all use the Internet to break the laws or rules, their internal motivations are not always utterly sinister; actually, some of them firmly believe that their actions are for the greater good. This paper is structured as follows: Firstly, the general profile of a hacker is presented. Then, the state of the art is outlined, concerning other papers dealing with the motivations behind cyber threat actors. Following that, the three aforementioned groups of cyberspace actors are contrasted with the profile of a ‘typical’ hacker. Then, the profiles of a typical representative for each of the group and their motivations are indicated, followed by the final conclusions.

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At present, many researchers see hope that artificial intelligence, machine learning in particular, will improve several aspects of the everyday life for individuals, cities and whole nations alike. For example, it has been speculated that the so-called machine learning could soon relieve employees of part of the duties, which may improve processes or help to find the most effective ways of performing tasks. Consequently, in the long run, it would help to enhance employees' work-life balance. Thus, workers' overall quality of life would improve, too. However, what would happen if machine learning as such were employed to try and find the ways of achieving work-life balance? This is why the authors of the paper decided to utilize a machine learning tool to search for the factors that influence the subjective feeling of one's work-life balance. The possible results could help to predict and prevent the occurrence of work-life imbalance in the future. In order to do so, the data provided by an exceptionally sizeable group of 800 employees was utilised; it was one of the largest sample groups in similar studies in Poland so far. Additionally, this was one of the first studies where so many employees had been analysed using an artificial neural network. In order to enable replicability of the study, the specific setup of the study and the description of the dataset are provided. Having analysed the data and having conducted several experiments, the correlations between some factors and work-life balance have indeed been identified: it has been found that the most significant was the relation between the feeling of balance and the actual working hours; shifting it resulted in the tool predicting the switch from balance to imbalance, and vice versa. Other factors that proved significant for the predicted WLB are the amount of free time a week the employee has for themselves, working at weekends only, being selfemployed and the subjective assessment of one's financial status. In the study the dataset gets balanced, the most important features are selected with the selectKbest algorithm, an artificial neural network of 2 hidden layers with 50 and 25 neurons, ReLU and ADAM is constructed and trained on 90% of the dataset. In tests, it predicts WLB based on the prepared dataset and selected features with 81% accuracy.