The paper analyses cyber security challenges of smart cities with a particular focus on the intelligent integrated and interconnected electric vehicle (EV) charging infrastructure. The analysis indicates that not all innovative elements and smart city solutions have adequate cybersecurity protection. Digital technologies vary considerably in terms of the level of potential risks, with certain novel technologies — such as V2G, smart charging, and smart energy management — posing higher risks than others. It is intended to lay a foundation for securing EV charging infrastructure by analysing problem context and data to be protected, including attack surfaces and cybersecurity threats and vulnerabilities in the EV ecosystem, analysing standardisation for the EV connection to the charging infrastructure, and providing a set of recommendations and best practices to securing EV charging infrastructure.

The paper outlines some aspects of developing a cyber-forensic framework for Smart Grid cyber-crime investigations. In this research, we examine a key forensic instrument in reconstructing events, the timeline, followed by correlation of data from different sources. Then, we deal with the tasks of collecting and storing the monitored data. The paper also covers some aspects of the legal ramifications from collecting this data and touches on the preconditions that must be met to enable network forensics. Then we present the logging architecture, based on the recommendations of the UK National Cyber Security Center. The final part presents the methodological framework that is the result of applying the OSCAR methodology and relevant open source tools in order to ensure that necessary forensic information can be collected, stored and used as legal evidence in court.

Recently, smart grids have become a vector of the energy policy of many countries. Due to structural and operation features, smart grids are a constant target of combined and simultaneous cyberattacks. To maximize security and to optimize existing network schemes to prevent cyber intrusion, in this paper, we propose an approach to decision support in finding and identifying the most potent attack combinations that can set the system to maximum damage. The main purpose is to identify the most severe combinations of attacks on smart grid components that potentially can be implemented from the perspective of the attacker. In this context, the problem of finding weaknesses points in the network configuration of a smart grid and assessing the impact of events on cyberinfrastructure is considered. The technique for detecting and investigating the strongest combinations of cyberattacks on the smart grid network is given with an example of the analysis of the spread of pandemic software in a system with arbitrary structure.

The omnipresence of smart devices in many aspects of modern everyday life has helped to achieve an enormous level of automation, has ensured sustainable development, and improved quality of life. Over the last decade, such small and portable devices became cheap and easy to deploy in any kind of application. With the full range of versatile connectivity, such technological development also brings multiple challenges related to the security of infrastructure and data. Many individuals, companies, and states worldwide experience the previously unseen scale and scope of the attacks using novel approaches. All these smart applications have also increased the overall attack surface leading to multiple attack vectors available through vulnerabilities. Lack of standards, insufficient security awareness, and new technological landscape does not help either. Considering this, one needs to enhance forensics investigation methodologies, employ novel tools, combine threat intelligence, and integrate forensic readiness. Such measures will help to reduce the total cyber risk through a high level of preparedness for anticipated data-driven crimes in smart applications. We believe that this paper will help in bringing novel focus to existing digital forensics methodologies with a focus on smart applications.

The paper outlines some aspects of developing an information system for e-Health database administrators (DBA). This system is equipped with advanced database performance monitoring and prediction features and based on different captured metrics as CPUs, RAMs, HDDs, and other values as well as historical events from host cluster/nodes. The data are aggregated, processed and transformed to provide the developers, production and host DBA teams with timely, proper, and valuable information about existing issues. The graphical representation of critical parameters to the working instance is provided. The approaches to forecasting database performance troubles related to the degradation of its characteristics due to different cumulative effects are discussed.

Smart Grids is an emerging technology promising significant changes in the economy and the social sphere. One among many challenges in their development and distribution is security. Considering recent hackers attacks on energy grids and taking into account the distributed structure of these systems the use of traditional means of computer protection and the search for a crime figure becomes more difficult or impossible. In this article, we introduce some application areas of smart grid forensic science, discuss the opportunities, and outline the open issues in the topic. We summarized challenges for forensic in Smart Grids in connection with a Blockchain and proposed a decentralized transaction platform based on Blockchain tailored to the energy sector with all the latest technology such as advanced metering infrastructure, distributed generation, etc.