Nowadays, information security is very important, because more and more confidential information, like medical reports, is being stored electronically on computer systems and those systems are often connected to computer networks. This represents new challenges for people working in information technology. They have to ensure that those systems are as much secure as possible and confidential information will not be revealed. One possible way how to prove system security is to conduct regular penetration tests - e.g. simulate attacker's malicious activity. This article briefly introduces the basics of penetration testing and shows how to deploy and use Metasploit framework when conducting penetration testing. Finally, a case study in production environment is shown. Software tools and techniques described in this work are also valid and applicable for SCADA systems and moreover in any other field where computer networks are used.

A full smart grid implementation requires the digitization of all parts of the smart grid infrastructure, including secondary electrical substations. Unfortunately, this introduces new security threats, which were not apparent before. This article uses a Smart Grid Threat Modeling Template implementing the STRIDE model to create a threat model of a digital secondary substation and its communication with the control center. Threats are classified by priority and need for further investigation. The tool was compared with a CORAS analysis, and was determined to be more time efficient. Denial of service (DoS) threats were classified as the most critical, and they were further evaluated in a precise simulation model created for this purpose. This model combines simulation with emulated communication, and enables verification of threat likelihoods and impacts. The results show that even publicly available tools can be easily used to disrupt grid communication and potentially cause loss of the entire grid’s observability and controllability.

This paper acquaints with a created application for generating Rainbow Tables and the results of testing Rainbow Tables, according to the length of the chosen chain. The paper presents a specialized application containing its own algorithms for reduction functions, changing the length of chain, generating Rainbow Tables and measuring the effectivity of the password search in detail. Within the executed tests, the dependence of Rainbow Tables size on the password length, the affection of the hash search by the size of the chosen chain and their links to collisions, which arise from the principle of using the reduction function, were observed. The results objectively describe the pros and cons of using Rainbow Tables and show the possibilities and restrictions for their effective usage.

Increasing power consumption and reliance on non-predictable renewable power generation is pushing the transition from analog to digital power grid substations forward. Grid digitalization helps to reduce substation complexity and therefore costs, and improves observability and management, but introduces new cyber security issues. To make the digital substations secure, cyber security awareness and efficient personnel training is one of the most important research areas as the power grid is a part of critical infrastructure. In our previous work, we have proposed an approach for analyzing cyber security threats and attacks in digital substations based on a case study from Norway. In this article, we present how we developed a tool for emulation of digital substation communication for cyber security awareness based on experiences from the case study. We present technical details of the tool—called the SGSim—so the community can easily replicate the process or only the selected parts. We also freely provide source code on GitHub and distribution in the form of a virtual machine on request. Finally, we validate the tool performance in several scenarios and evaluate its usability on a survey conducted among a wide range of professionals.

The current demand for remote work, remote teaching and video conferencing has brought a surge not only in network traffic, but unfortunately, in the number of attacks as well. Having reliable, safe and secure functionality of various network services has never been more important. Another serious phenomenon that is apparent these days and that must not be discounted is the growing use of artificial intelligence techniques for carrying out network attacks. To combat these attacks, effective protection methods must also utilize artificial intelligence. Hence, we are introducing a specific neural network-based decision procedure that can be considered for application in any flow characteristic-based network-traffic-handling controller. This decision procedure is based on a convolutional neural network that processes the incoming flow characteristics and provides a decision; the procedure can be understood as a firewall rule. The main advantage of this decision procedure is its depiction process, which has the ability to transform the incoming flow characteristics into a graphical structure. Graphical structures are regarded as very efficient data structures for processing by convolutional neural networks. This article’s main contribution consists of the development and improvement of the depiction process using a genetic algorithm. The results presented at the end of the article show that the decision procedure using an optimized depiction process brings significant improvements in comparison to previous experiments.