Rafał Kozik

Bydgoszcz University of Science and Technology · Institute of Telecommunications

In the rapidly evolving domain of cybersecurity, the imperative for intrusion detection systems is undeniable; yet, it is increasingly clear that to meet the ever-growing challenges posed by sophisticated threats, intrusion detection itself stands in need of the transformative capabilities offered by the explainable artificial intelligence (xAI). A...

The current threat landscape identifies Distributed Denial of Service (DDoS) attacks as one of the most critical hazards for network security. Given the constant variation in attack dynamics, enhancing existing detection techniques has become imperative. Indeed, traditional rule-based Security Information and Event Management (SIEM) systems often f...

In today’s interconnected digital landscape, Security Information and Event Management (SIEM) systems play a vital role as the frontline defense against cyber threats, providing prompt detection of the most common cyber-threats. As Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks remain among the most challenging hazards for...

With the emergence of advanced artificial intelligence technologies, the use of ChatGPT (Generative Pre-trained Transformer) has gained significant attention in the scientific writing community. ChatGPT is a machine learning algorithm that has the capability to generate text that resembles human writing. This article provides a comprehensive review...

In the realm of cybersecurity, the detection of Concept Drift holds the potential to improve the adaptability and effectiveness of security systems. In particular, Security Information and Event Management (SIEM) frameworks can benefit from real-time Drift Detection, enabling prompt detection of changing attack patterns, and consequent update of th...

Despite the fact that machine learning has been applied in innumerable domains, its models have usually operated in a black box fashion, i.e. without revealing the rationale behind their decisions. For human users, insufficient model transparency may result in the lack of trust in the technology, effectively hindering its development and adoption....

Currently, one can observe the evolution of social media networks. In particular, humans are faced with the fact that, often, the opinion of an expert is as important and significant as the opinion of a non-expert. It is possible to observe changes and processes in traditional media that reduce the role of a conventional ’editorial office’, placing...

Machine learning has become a key component of the effective detection of network intrusions. Yet, it comes with the lack of transparency - an issue which can be mitigated with the employment of explainable AI techniques. In this paper, the crucial role of explainability in intrusion detection is discussed, along with its benefits and drawbacks, fo...

Every day, the average Internet user perceives an abundance of content that is unintentionally consumed every day. We frequently hear the seemingly obvious remark that the modern world is full of data. We are bombarded with numerous links to amusing content circulated by our friends, various news and content providers, and social media. Unfortunate...

Network Intrusion Detection is one of the major components of maintaining cybersecurity. This is especially crucial in Soft Targets, important places which are easily accessible, and thus more vulnerable. Real-time machine-learning-based network intrusion detection is an increasingly more relevant field of study offering important benefits to the p...

One of the critical challenges for natural language processing methods is the issue of automatic content summarization. The enormous increase in the amount of data delivered to users by news services leads to an overload of information without meaningful content. There is a need to generate an automatic text summary that contains as much essential...

We often come across the seemingly obvious remark that the modern world is full of data. From the perspective of a regular Internet user, we perceive this as an abundance of content that we unintentionally consume every day, including links and amusing images that we receive from friends and content providers via webpages, social media, and other s...

Artificial Intelligence (AI) systems have grown commonplace in modern life, with various applications from customized suggestions to self-driving vehicles. As these systems get more complicated, the necessity for transparency in their decision-making processes becomes more critical. Explainability refers to an AI system’s ability to explain how and...

Recently, various BERT-based architectures for fake news detection have been proposed. In many cases, these methods work well on various benchmark datasets. However, the performance quickly deteriorates when the models are tested with samples coming from distributions which essentially differ from the ones the model has been trained on. To overcome...

Network traffic analysis is a process of paramount importance to monitor network availability and operational activity, identify anomalies, maximize performance, find threats, and detect attacks. Due to this fact, in everyday work network managers need to capture, analyze and store a tremendous amount of data which can definitely be classified as ”...

There has been an ongoing debate whether the possibility of cyberspace becoming both a weapon and a battlefield should be treated as an act of war. Although NATO recognized in 2014 that an armed response can be invoked following a cyberattack, the anonymous nature of the Internet makes it extremely difficult to attribute the attack to a specific na...

The Denial of Service attacks are one of the most common attacks used to disrupt the services of public institutions. The criminal act of exhausting a network resource with the intent to obstruct the utility of a service is associated with hacktivism, blackmailing and extortion attempts. Intrusion Prevention Systems are an essential line of defence...

Although the ethics of cybersecurity might seem to be simple, the matter can be surprisingly complicated. This paper discusses the results of an extensive study aimed at uncovering the anticipated, emerging ethical issues related to cybersecurity. First, it discusses the "strong signals", i.e., the "mainstream" worries and concerns. Then, it uncove...

Recently, various artificial intelligence (AI)-based methods have been proposed to support humans in detecting disinformation and fake news. The goal of this article is to provide a meta-analysis, and formally evaluate, compare, and benchmark various classes of fake news detection approaches. To this end, the following paper performs a comprehensiv...

Network flow-based cyber anomaly detection is a difficult and complex task. Although several approaches to tackling this problem have been suggested, many research topics remain open. One of these concerns the problem of model transferability. There is a limited number of papers which tackle transfer learning in the context of flow-based network an...

In intelligent information systems data play a critical role. The issue of missing data is one of the commonplace problems occurring in data collected in the real world. The problem stems directly from the very nature of data collection. In this paper, the notion of handling missing values in a real-world application of computational intelligence i...

Contemporary cyberthreats continue to evolve, powering the neverending development arms race [...]

Purpose The purpose of this paper is to challenge the prevailing, stereotypical approach of the human aspect of cybersecurity, i.e. treating people as weakness or threat. Instead, several reflections are presented, pertaining to the ways of making cybersecurity human-centred. Design/methodology/approach This paper bases on the authors’ own experie...

Currently, the doors are open to novel paradigms of the use of connected technologies. E-commerce and the Internet of Things devices experience substantial growth in popularity. However, this unprecedented increase in popularity comes at a price of a wide attack surface. This paper proposes an efficient Post Event Analysis and Incident Response pro...

The goal of this systematic and broad survey is to present and discuss the main challenges that are posed by the implementation of Artificial Intelligence and Machine Learning in the form of Artificial Neural Networks in Cybersecurity, specifically in Intrusion Detection Systems. Based on the results of the state-of-the-art analysis with a number o...

In recent years, false information has acquired a new significance, with the (in)famous term fake news' entering the collective consciousness. False but controversial or sensational news tends to spread incomparably faster than genuine information. The world has already witnessed how Internet news can help raise the publica's doubt in the actions t...

Contemporary Artificial Intelligence methods, especially their subset-deep learning, are finding their way to successful implementations in the detection and classification of intrusions at the network level. This paper presents an intrusion detection mechanism that leverages Deep AutoEncoder and several Deep Decoders for unsupervised classificatio...

Countering the fake news phenomenon has become one of the most important challenges for democratic societies, governments and non-profit organizations, as well as for the researchers coming from several domains. This is not a local problem and demands a holistic approach to analyzing heterogeneous data and storing the results. The research problem...

Fake news detection is a challenging and complex task. Yet, several approaches to deal with this problem have already been proposed. The majority of solutions employ the NLP-based approach, where various architectures of a deep artificial neural network are proposed. However, as the experiments show, different NLP-based solutions have great perform...

This Special Issue aimed to gather high-quality advancements in theoretical and practical aspects of computer recognition, pattern recognition, image processing and machine learning (shallow and deep), including, in particular, novel implementations of these techniques in the areas of modern telecommunications and cybersecurity [...]

Cybersecurity is relevant to everyone, as cyberthreat concerns individuals and whole societies, and a precise cyberattack targeted at critical infrastructure may pose danger to millions of citizens. At a European level, several initiatives have aimed at protecting CI, one of them being InfraStress. This paper presents a part of the InfraStress arch...

With the advancement of internet technologies, network traffic monitoring and cyber-attack detection are becoming more and more important for critical infrastructure. Unfortunately, there are still relatively few works in the literature that interpret the available benchmark data as data streams and take into account the dynamic characteristics of...

The ubiquity of social media and their deep integration in the contemporary society has granted new ways to interact, exchange information, form groups, or earn money—all on a scale never seen before. Those possibilities paired with the widespread popularity contribute to the level of impact that social media display. Unfortunately, the benefits br...

The number of security breaches in the cyberspace is on the rise. This threat is met with intensive work in the intrusion detection research community. To keep the defensive mechanisms up to date and relevant, realistic network traffic datasets are needed. The use of flow-based data for machine-learning-based network intrusion detection is a promis...

Quality assessment of stitched images is an important element of many virtual reality and remote sensing applications where the panoramic images may be used as a background as well as for navigation purposes. The quality of stitched images may be decreased by several factors, including geometric distortions, ghosting, blurring, and color distortion...

The Internet of Things (IoT) appliances often expose sensitive data, either directly or indirectly. They may, for instance, tell whether you are at home right now or what your long or short-term habits are. Therefore, it is crucial to protect such devices against adversaries and has in place an early warning system which indicates compromised devic...

Handling the data imbalance problem is one of the crucial steps in a machine learning pipeline. The research community is well aware of the effects of data imbalance on machine learning algorithms. At the same time, there is a rising need for explainability of AI, especially in difficult, high-stake domains like network intrusion detection. In this...

The aim of the article is to give the rationale behind employing AI tools to help Law Enforcement Agencies analyze data, based on the existing solution, i.e., the MAGNETO (Multimedia Analysis and correlation enGine for orgaNised crime prevention and investigation) platform. In order to do this, the challenges Law Enforcement Agencies (LEAs) face wi...

E-commerce services have expanded tremendously in the recent years, with market value estimations for cross-border trade reaching well over a hundred billion euro just in the European Union. At the same time, e-commerce-related fraud rate and cybersecurity issues are staggering. With e-commerce clearly gaining the critical infrastructure status, an...

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 s...

Recent progress in the area of modern technologies confirms that information is not only a commodity but can also become a tool for competition and rivalry among governments and corporations, or can be applied by ill-willed people to use it in their hate speech practices. The impact of information is overpowering and can lead to many socially undes...

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...

Cybersecurity is an arms race, with both the security and the adversaries attempting to outsmart one another, coming up with new attacks, new ways to defend against those attacks, and again with new ways to circumvent those defences. This situation creates a constant need for novel, realistic cybersecurity datasets. This paper introduces the effect...

The article presents models for detecting fake news and the results of the analyzes of the application of these models. The precision, f1-score, recall metrics were proposed as a measure of the model quality assessment. Neural network architectures, based on the state-of-the-art solutions of the Transformer type were applied to create the models. T...

Nowadays,the use of digital technologies is promoting three main characteristics of information, i.e. the volume, the modality and the frequency. Due to the amount of information generated by tools and individuals, it has been identified a critical need for the Law Enforcement Agencies to exploit this information and carry out criminal investigatio...

Nowadays, law enforcement agencies – LEAs – are forced to deal with extreme volumes of data, being in need to analyse from heterogeneous data sources, uncover hidden relationships, trends and patterns of incidents and ultimately reach solid evidence to be used in court. In this chapter, a system is presented that can assist LEA officers in fighting...

In intelligent information systems data plays a critical role. Preparing data for the use of artificial intelligence is therefore a substantial step in the processing pipeline. Sometimes, modest improvements in data quality can translate into a vastly superior model. The issue of missing data is one of the commonplace problems occurring in data col...

In this paper, the performance of a solution providing stream processing is evaluated, and its accuracy in the classification of suspicious flows in simulated network traffic is investigated. The concept of the solution is fully disclosed along with its initial evaluation in a real-world environment. The proposition features Apache Kafka for effici...

The growing volume of cloud-based applications, services and cyber-physical IoT solutions presents vital challenges linked to resource allocation, misconfiguration, scaling, and running software updates. Various solutions and applications have different hardware and energy requirements of the involved elements. Hence, the recent technology trends s...

Cybersecurity and cybercrime cannot exist without each other. They are not contraries, but rather two opposite poles of the same idea. Although it may seem that it is a rather black and white kind of relationship, the measures aimed at protecting innocent people raise a myriad of ethical dilemmas. This paper presents the results of a horizon scanni...

Countering the fake news phenomenon has become one of the most important challenges for democratic societies, governments and non-profit organizations, as well as for the researchers coming from several domains. This is not a local problem, and demands a holistic approach to analyzing heterogeneous data and storing the results. The major contributi...

Recent progress in the area of modern technologies confirms that information is not only a commodity but can also become a tool for competition and rivalry among governments and corporations, or can be applied by ill-willed people to use it in their hate speech practices. The impact of information is overpowering and can lead to many socially undes...

Call Detail Records (CDRs) are one of the most popular information sources used in criminal investigations. They allow police officers to quickly identify the key actors and relations between them. Of course, the challenge for law enforcement officers is to process and understand the large volume of such data. Typically, the process is long and mos...

Practitioners adopt software metrics programs to support their software development from the perspective of either overall quality, performance, or both. Current literature details and justifies the role of a metrics program in a software organization’s software development, but empirical evidence to demonstrate its actual use and concomitant benef...

Using fake news as a political or economic tool is not new, but the scale of their use is currently alarming, especially on social media. The authors of misinformation try to influence the users' decisions, both in the economic and political sphere. The facts of using disinformation during elections are well known. Currently, two fake news detectio...

Quality requirements (QRs) are a key artifact needed to ensure the quality and success of a software system. Despite their importance, QRs rarely get the same degree of attention as their functional counterpart in agile software development (ASD) projects. Moreover, crucial information that can be obtained from software development repositories (e....