Keystroke dynamics are used to authenticate users, to reveal some of their inherent or acquired characteristics and to assess their mental and physical states. The most common features utilized are the time intervals that the keys remain pressed and the time intervals that are required to use two consecutive keys. This paper examines which of these features are the most important and how utilization of these features can lead to better classification results. To achieve this, an existing dataset consisting of 387 logfiles is used, five classifiers are exploited and users are classified by gender and age. The results, while demonstrating the application of these two characteristics jointly on classifiers with high accuracy, answer the question of which keystroke dynamics features are more appropriate for classification with common classifiers.

This research demonstrates a design of an experiment of a hacker infiltrating a server where it is assumed that the communication between the hacker and the target server is established, and the hacker also escalated his rights on the server. Therefore, the honeypot server setup has been designed to reveal the correlation of a hackers actions with that of the hackers experience, personality, expertise, and psychology. To the best of our knowledge, such a design of experiment has never been tested rigorously on a honeypot implementation except for self-reporting tests applied to hackers in the literature. However, no study evaluates the actual data of these hackers and these tests. This study also provides a honeypot design to understand the personality and expertise of the hacker and displays the correlation of these data with the tests. Our Honeypsy system is composed of a Big-5 personality test, a cyber expertise test, and a capture-the-flag (CTF) event to collect logs with honeypot applied in this sequence. These three steps generate data on the expertise and psychology of known cyber hackers. The logs of the known hacker activities on honeypots are obtained through the CTF event that they have participated in. The design and deployment of a honeypot, as well as the CTF event, were specifically prepared for this research. Our aim is to predict an unknown hacker's expertise and personality by analyzing these data. By examining/analyzing the data of the known hackers, it is now possible to make predictions about the expertise and personality of the unknown hackers. The same logic applies when one tries to predict the next move of the unknown hackers attacking the server. We have aimed to underline the details of the personalities and expertise of hackers and thus help the defense experts of victimized institutions to develop their cyber defense strategies in accordance with the modus operandi of the hackers.

The introduction of Data Protection by Default and Design (DPbDD) brought in as part of the General Data Protection Regulation (GDPR) in 2018, has necessitated that businesses review how best to incorporate privacy into their processes in a transparent manner, so as to build trust and improve decisions around privacy best practice. To address this issue, this paper presents a 7-stage data lifecycle, supported by nine privacy goals that together, will help practitioners manage data holdings throughout data lifecycle. The resulting data lifecycle (7-DL) was created as part of the Ideal-Cities project, a Horizon-2020 Smart-city initiative, that seeks to facilitate data re-use and/or repurposed. We evaluate 7-DL through peer review and an exemplar worked example that applies the data lifecycle to a real-time life logging fire incident scenario, one of the Ideal-Cities use cases to demonstrate the applicability of the framework.

Technologies providing copyright-infringing IPTV content are commonly used as an illegal alternative to legal IPTV subscriptions and services, as they usually have lower monetary costs and can be more convenient for users who follow content from different sources. These infringing IPTV technologies may include websites, software, software add-ons, and physical set-top boxes. Due to the free or low cost of illegal IPTV technologies, illicit IPTV content providers will often resort to intrusive advertising, scams, and the distribution of malware to increase their revenue. We developed an automated solution for collecting and analysing malware from illegal IPTV technologies and used it to analyse a sample of illicit IPTV websites, application (app) stores, and software. Our results show that our IPTV Technologies Malware Analysis Framework (IITMAF) classified 32 of the 60 sample URLs tested as malicious compared to running the same test using publicly available online antivirus solutions, which only detected 23 of the 60 sample URLs as malicious. Moreover, the IITMAF also detected malicious URLs and files from 31 of the sample’s websites, one of which had reported ransomware behaviour.

Spurred by the rapid modernisation of the sector and the advent of Internet Protocol Television (IPTV), audiovisual (AV) piracy is at epidemic levels, with interventions having limited effect. To date, the dominant themes in interventions have been around personal deterrence (i.e. the threat of legal action) and have not considered other factors that may influence an individual’s decision to consume infringing content. In this paper, we consider psychological factors, including perceptions around risk-taking, security behaviours, problematic internet use and personality traits, to gain a comprehensive understanding of factors influencing engagement with IPTV and the potential implications for cyber security. For this purpose, a survey was conducted with 283 participants living in the UK (age range 18–74, male 104), and an integrated structural equation model was constructed. Our findings showed a positive relationship between security behaviours and the perceived risk of viewing IPTV and a negative relationship between the dark personality triad and the perceived risk of viewing IPTV. They suggest that security behaviours fully mediate the relationship between problematic internet use and IPTV risk-taking, indicating a potential new path for anti-piracy interventions with greater efficacy.