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- ItemIdentification of industrial devices based on payload(Association for Computing Machinery, 2024-07-30) Pospíšil, Ondřej; Fujdiak, RadekIdentification of industrial devices based on their behavior in network communication is important from a cybersecurity perspective in two areas: attack prevention and digital forensics. In both areas, device identification falls under asset management or asset tracking. Due to the impact of active scanning on these networks, particularly in terms of latency, it is important to use passive scanning in industrial networks. For passive identification, statistical learning algorithms are nowadays the most appropriate. The aim of this paper is to demonstrate the potential for passive identification of PLC devices using statistical learning based on network communication, specifically the payload of the packet. Individual statistical parameters from 15 minutes of traffic based on payload entropy were used to create the features. Three scenarios were performed and the XGBoost algorithm was used for evaluation. In the best scenario, the model achieved an accuracy score of 83% to identify individual devices.
- ItemEnhancing Service Continuity in Non-Terrestrial Networks via Multi-Connectivity Offloading(IEEE, 2024-07-29) Sadovaya, Yekaterina; Vikhrova, Olga; Andreev, Sergey; Yanikomeroglu, HalimNon-terrestrial networks (NTNs) have recently emerged as a promising paradigm for computation-intensive six-generation (6G) applications, which may range from augmented reality to disaster relief. Moreover, NTNs can cater to uninterrupted connectivity needs in both rural and urban areas. In urban settings, uncrewed aerial vehicles (UAVs) and high-altitude platform stations (HAPS) play crucial roles in supporting delay-sensitive computation applications for terrestrial UEs when terrestrial networks face limitations. Given the emerging interest in multi-connectivity for NTNs, this letter investigates UAV- and HAPS-assisted multi-connectivity computation offloading in urban areas. Specifically, we propose two novel multi-connectivity offloading strategies to improve the probability of timely task computation, along with a framework for optimizing the corresponding offloading probabilities onto HAPS and UAVs. Our results demonstrate that utilizing multi-connectivity in NTN-assisted offloading can achieve a 75% reduction in task computation delay as compared to scenarios with no offloading.
- ItemSecure and Privacy-Preserving Car-Sharing Systems(ACM, 2024-07-30) Malina, Lukáš; Dzurenda, Petr; Lövinger, Norbert; Ekeh, Ijeoma Faustina; Matulevicius, RaimundasWith increasing smart transportation systems and services, potential security and privacy threats are growing. In this work, we analyze privacy and security threats in car-sharing systems, and discuss the problems with the transparency of services, users’ personal data collection, and how the legislation manages these issues. Based on analyzed requirements, we design a compact privacy-preserving solution for car-sharing systems. Our proposal combines digital signature schemes and group signature schemes, in order to protect user privacy against curious providers, increase security and non-repudiation, and be efficient even for systems with restricted devices. The evaluation of the proposed solution demonstrates its security and a practical usability for constrained devices deployed in vehicles and users’ smartphones.
- ItemEvent-based Data Collection and Analysis in the Cyber Range Environment(Association for Computing Machinery, 2024-07-30) Lazarov, Willi; Janek, Samuel; Martinásek, Zdeněk; Fujdiak, RadekThe need to educate users on cybersecurity to some extent is critical due to the ever-increasing cyber threats. A number of web presentations, books, and other study materials can be used for this purpose. In contrast to passive learning methods, hands-on training offers a deeper perspective but poses considerable technical challenges to its implementation, which can be resolved using cyber range platforms. However, in order to thoroughly evaluate the training and provide sufficient feedback, data must be collected and analyzed. Our paper addresses this problem by developing an event-based approach for data collection and analysis. The use of events allows us to keep a history of an event and reconstruct it retrospectively, especially for further analysis and evaluation. We validated the implemented approach in a cyber range environment, in which we developed an interactive interface to visualize the analyzed data.
- ItemLattice-based Multisignature Optimization for RAM Constrained Devices(Association for Computing Machinery, 2024-07-30) Ricci, Sara; Shapoval, Vladyslav; Dzurenda, Petr; Roenne, Peter; Oupicky, Jan; Malina, LukášIn the era of growing threats posed by the development of quantum computers, ensuring the security of electronic services has become fundamental. The ongoing standardization process led by the National Institute of Standards and Technology (NIST) emphasizes the necessity for quantum-resistant security measures. However, the implementation of Post-Quantum Cryptographic (PQC) schemes, including advanced schemes such as threshold signatures, faces challenges due to their large key sizes and high computational complexity, particularly on constrained devices. This paper introduces two microcontroller-tailored optimization approaches, focusing on enhancing the DS2 threshold signature scheme. These optimizations aim to reduce memory consumption while maintaining security strength, specifically enabling the implementation of DS2 on microcontrollers with only 192 KB of RAM. Experimental results and security analysis demonstrate the efficacy and practicality of our solution, facilitating the deployment of DS2 threshold signatures on resource-constrained microcontrollers.