http://hdl.handle.net/20.500.14044/33790 2026-07-26T08:58:36Z 2026-07-26T08:58:36Z Saulaiman, Nizam-Edden Mera Csilling, Akos Kozlovszky, Miklos http://hdl.handle.net/20.500.14044/32127 2025-09-17T08:25:17Z 2025-01-01T00:00:00Z

Integrated Automation for Threat Analysis and Risk Assessment in Automotive Cybersecurity Through Attack Graphs Saulaiman, Nizam-Edden Mera; Csilling, Akos; Kozlovszky, Miklos Attack graphs contribute to the evaluation of network security vulnerabilities, offering a visualization of possible attack paths. Despite their common use in IT security for analyzing system vulnerabilities, attack graphs are not commonly used in the automotive sector. As smart vehicles increasingly rely on 5G networks for high-bandwidth, low-latency communication – necessary for advanced vehicle-to-everything (V2X) services and sensor data processing – security concerns escalate. The complexity of 5G-enabled vehicles significantly expands a vehicle's attack surface. The ISO/SAE 21434 standard establishes a framework for securing road vehicle systems. The Threat Analysis and Risk Assessment (TARA) process, a vital part of this standard, helps identify and mitigate security risks. However, the current TARA process relies heavily on manual effort to identify potential attack vectors and assess risks. This can be time consuming, resource- intensive, and prone to human error. This paper discusses the concept of an automated attack graph generation tool specifically designed for automotive threat analysis. We propose a new Graph-based Attack Path Prioritization tool (GAPP), tailored for automotive networks. GAPP focuses on generating attack paths, assessing their feasibility, and identifying the most likely attack scenarios. This aims to enhance the efficiency, comprehensiveness, and accuracy of the TARA process in evaluating network security.

2025-01-01T00:00:00Z Bánáti, Anna http://hdl.handle.net/20.500.14044/32126 2025-09-17T08:24:49Z 2025-01-01T00:00:00Z

Developing Security Information and Events Management Use Cases for 5G Specific Vulnerabilities and Attacks Bánáti, Anna The number of cybersecurity attacks and sensitive data breaches in businesses and organizations has increased significantly in recent years, and companies that are increasingly using or providing 5G technology are no exception. The impact of these incidents not only results the sensitive data breaches, financial losses and unexpected operational patterns for the targeted companies or organizations but can also extend to their peers in the same industry. Therefore, prevention and early detection of cyberattacks is also a key issue for IT infrastructures extended with emerging 5G technology. At the same time, detecting different types of attacks has become extremely challenging as attacks have become more sophisticated, distributed and stealthy with the help of artificial intelligence and other modern technologies. Detecting and managing such attacks requires sophisticated intrusion detection systems running on high-performance hardware and managed by expert security personnel. However, these resources are expensive to deploy, especially for small and medium-sized enterprises (SMEs). Therefore, in many cases, open source and free solutions are needed that allow SMEs to operate a security information event management (SIEM) system. Thanks to the low cost of implementation, it is affordable for SMEs and, after a short configuration and learning phase, it is self-sufficient and stable. Our goal is to provide detection solutions for attacks and vulnerabilities specific to 5G networks that provide effective detection and response for open source SIEM systems. Alerts on detected anomalies notify security personnel, who can efficiently and quickly implement incident response through graphical and visual dashboards.

2025-01-01T00:00:00Z Orsós, Miklós Török, Roland Faragó, Csaba Antalfia, Benjamin Kail, Eszter Bánáti, Anna http://hdl.handle.net/20.500.14044/32125 2025-09-17T08:24:34Z 2025-01-01T00:00:00Z

Security Operation Center Methodology for 5G Networks Orsós, Miklós; Török, Roland; Faragó, Csaba; Antalfia, Benjamin; Kail, Eszter; Bánáti, Anna The utilization of the recently introduced yet rapidly proliferating new generation of 5G mobile communications offers many new advantages. However, it has also brought with it the introduction of many new services and technologies compared to its predecessors. This, combined with the ever-expanding threat landscape, means that traditional methods of protection are no longer sufficient. Security Operation Centres (SOCs) are not only popular today, they are becoming an essential part of many organisations. Consequently, the development of a 5G SOC methodology for 5G technology has become progressively imperative. This paper presents our 5G SOC methodology. The SOC developed at Óbuda University, designed for monitoring, analyzing, managing data and log data for incident handling has been specifically tailored for 5G-specific usage. The showcased results underscore the utility and success in the pursuit of pioneering a 5G SOC methodology.

2025-01-01T00:00:00Z Azemi, Fatmir Lujić, Roberto Šimunović, Goran Zeqiri, Fitim Rajnai, Zoltan Altaleb, Haya Ady, Laszlo Tokody, Daniel http://hdl.handle.net/20.500.14044/32124 2025-09-17T08:24:20Z 2025-01-01T00:00:00Z

Optimizing Production Processes through 5G- Enabled Job Shop Scheduling: A Case Study Azemi, Fatmir; Lujić, Roberto; Šimunović, Goran; Zeqiri, Fitim; Rajnai, Zoltan; Altaleb, Haya; Ady, Laszlo; Tokody, Daniel The complexity of scheduling in manufacturing systems, is examined in this article, with a focus on the important factors that determine time and production costs. Addressing the inefficiencies in resource utilization and recognizing the limited integration of Information and Communication Technology (ICT), particularly the transformative 5G, in Kosovo’s Manufacturing Industry, we advocate for an advanced scheduling model. This model aims to propel productivity, curtail production time and elevate overall manufacturing system performance. Grounded in linear programming, our developed model strategically optimizes the objective function, encompassing total flow time and makespan. Significantly, the model achieves optimal allocation of start and end times for each job, coupled with an efficient overall processing time, substantially reducing planning times for “job shop” scheduling problems. Beyond the immediate benefits, our adaptable scheduling model stands poised for seamless modification to accommodate diverse objective functions and instances, including the incorporation of 5G technology. The practical case study underscores the tangible benefits of our approach, showcasing its ability to streamline production processes and enhance operational efficiency within a real-world manufacturing setting. Future iterations may harness 5G's transformative capabilities to further refine and improve the efficiency of the scheduling process.

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