@inproceedings{MTMT:34863410,
	title = {A túlzott digitális eszközhasználat fontosabb jellemzői és oktatási vonatkozásai},
	url = {https://m2.mtmt.hu/api/publication/34863410},
	author = {Holló, Csaba},
	booktitle = {iNFODIDACT'2023},
	unique-id = {34863410},
	keywords = {nevelés; függőség; oktatás; okostelefon-függőség},
	year = {2024},
	pages = {45-63},
	orcid-numbers = {Holló, Csaba/0000-0003-0077-3153}
}

@article{MTMT:34847971,
	title = {Partial Pre-Image Attack on Proof-of-Work based Blockchains},
	url = {https://m2.mtmt.hu/api/publication/34847971},
	author = {Baniata, Hamza and Kertész, Attila},
	doi = {10.1016/j.bcra.2024.100194},
	journal-iso = {BLOCKCHAIN},
	journal = {BLOCKCHAIN: RESEARCH AND APPLICATIONS},
	volume = {X},
	unique-id = {34847971},
	issn = {2096-7209},
	year = {2024},
	eissn = {2666-9536},
	pages = {100194},
	orcid-numbers = {Baniata, Hamza/0000-0003-1978-3175; Kertész, Attila/0000-0002-9457-2928}
}

@inproceedings{MTMT:34795721,
	title = {Swarmchestrate: Towards a Fully Decentralised Framework for Orchestrating Applications in the Cloud-to-Edge Continuum},
	url = {https://m2.mtmt.hu/api/publication/34795721},
	author = {Kiss, T and Ullah, A and Terstyanszky, G and Kao, O and Becker, S and Verginadis, Y and Michalas, A and Stankovski, V and Kertész, Attila and Ricci, E and Altmann, J and Egger, B and Tusa, F and Kovács, József and Lovas, Róbert},
	booktitle = {Advanced Information Networking and Applications},
	doi = {10.1007/978-3-031-57931-8_9},
	unique-id = {34795721},
	year = {2024},
	pages = {89-100},
	orcid-numbers = {Kertész, Attila/0000-0002-9457-2928; Kovács, József/0000-0002-7293-3016; Lovas, Róbert/0000-0001-9409-2855}
}

@inproceedings{MTMT:34795664,
	title = {Towards a Simulation as a Service Platform for the Cloud-to-Things Continuum},
	url = {https://m2.mtmt.hu/api/publication/34795664},
	author = {Wilson, Valdez and Baniata, Hamza and Márkus, András and Kertész, Attila},
	booktitle = {Euro-Par 2023: Parallel Processing Workshops},
	doi = {10.1007/978-3-031-48803-0_6},
	unique-id = {34795664},
	year = {2024},
	pages = {65-75},
	orcid-numbers = {Baniata, Hamza/0000-0003-1978-3175; Kertész, Attila/0000-0002-9457-2928}
}

@article{MTMT:34753193,
	title = {"Approaches to sentiment analysis of Hungarian political news at the sentence level"},
	url = {https://m2.mtmt.hu/api/publication/34753193},
	author = {Ring, Orsolya and Szabó, Martina Katalin and Guba, Csenge and Váradi, Bendegúz and Üveges, István},
	doi = {10.1007/s10579-023-09717-5},
	journal-iso = {LANG RESOUR EVAL},
	journal = {LANGUAGE RESOURCES AND EVALUATION},
	unique-id = {34753193},
	issn = {1574-020X},
	abstract = {Automated sentiment analysis of textual data is one of the central and most challenging tasks in political communication studies. However, the toolkits available are primarily for English texts and require contextual adaptation to produce valid results—especially concerning morphologically rich languages such as Hungarian. This study introduces (1) a new sentiment and emotion annotation framework that uses inductive approaches to identify emotions in the corpus and aggregate these emotions into positive, negative, and mixed sentiment categories, (2) a manually annotated sentiment data set with 5700 political news sentences, (3) a new Hungarian sentiment dictionary for political text analysis created via word embeddings, whose performance was compared with other available sentiment dictionaries. (4) Because of the limitations of sentiment analysis using dictionaries we have also applied various machine learning algorithms to analyze our dataset, (5) Last but not least to move towards state-of-the-art approaches, we have fine-tuned the Hungarian BERT-base model for sentiment analysis. Meanwhile, we have also tested how different pre-processing steps could affect the performance of machine-learning algorithms in the case of Hungarian texts.},
	year = {2024},
	eissn = {1574-0218},
	orcid-numbers = {Ring, Orsolya/0000-0002-3710-1118; Szabó, Martina Katalin/0000-0002-4192-4352; Üveges, István/0000-0001-5897-9379}
}

@article{MTMT:34499921,
	title = {A Comparative Study of Commit Representations for JIT Vulnerability Prediction},
	url = {https://m2.mtmt.hu/api/publication/34499921},
	author = {Aladics, Tamás and Hegedűs, Péter and Ferenc, Rudolf},
	doi = {10.3390/computers13010022},
	journal-iso = {COMPUTERS},
	journal = {COMPUTERS},
	volume = {13},
	unique-id = {34499921},
	abstract = {With the evolution of software systems, their size and complexity are rising rapidly. Identifying vulnerabilities as early as possible is crucial for ensuring high software quality and security. Just-in-time (JIT) vulnerability prediction, which aims to find vulnerabilities at the time of commit, has increasingly become a focus of attention. In our work, we present a comparative study to provide insights into the current state of JIT vulnerability prediction by examining three candidate models: CC2Vec, DeepJIT, and Code Change Tree. These unique approaches aptly represent the various techniques used in the field, allowing us to offer a thorough description of the current limitations and strengths of JIT vulnerability prediction. Our focus was on the predictive power of the models, their usability in terms of false positive (FP) rates, and the granularity of the source code analysis they are capable of handling. For training and evaluation, we used two recently published datasets containing vulnerability-inducing commits: ProjectKB and Defectors. Our results highlight the trade-offs between predictive accuracy and operational flexibility and also provide guidance on the use of ML-based automation for developers, especially considering false positive rates in commit-based vulnerability prediction. These findings can serve as crucial insights for future research and practical applications in software security.},
	year = {2024},
	eissn = {2073-431X},
	pages = {22},
	orcid-numbers = {Aladics, Tamás/0000-0002-4689-8878; Hegedűs, Péter/0000-0003-4592-6504; Ferenc, Rudolf/0000-0001-8897-7403}
}

@article{MTMT:34499877,
	title = {Known Vulnerabilities of Open Source Projects: Where Are the Fixes?},
	url = {https://m2.mtmt.hu/api/publication/34499877},
	author = {Sabetta, Antonino and Ponta, Serena Elisa and Lozoya, Rocio Cabrera and Bezzi, Michele and Sacchetti, Tommaso and Greco, Matteo and Balogh, Gergő and Hegedűs, Péter and Ferenc, Rudolf and Paramitha, Ranindya and Pashchenko, Ivan and Papotti, Aurora and Milánkovich, Ákos and Massacci, Fabio},
	doi = {10.1109/MSEC.2023.3343836},
	journal-iso = {IEEE SECUR PRIV},
	journal = {IEEE SECURITY & PRIVACY},
	volume = {22},
	unique-id = {34499877},
	issn = {1540-7993},
	year = {2024},
	eissn = {1558-4046},
	pages = {49-59},
	orcid-numbers = {Sabetta, Antonino/0000-0003-3506-8374; Ponta, Serena Elisa/0000-0002-6208-4743; Lozoya, Rocio Cabrera/0000-0001-8911-7392; Bezzi, Michele/0000-0003-2084-0675; Balogh, Gergő/0000-0002-6781-5453; Hegedűs, Péter/0000-0003-4592-6504; Ferenc, Rudolf/0000-0001-8897-7403; Paramitha, Ranindya/0000-0002-6682-4243; Pashchenko, Ivan/0000-0001-8202-576X; Papotti, Aurora/0000-0003-3207-7662; Massacci, Fabio/0000-0002-1091-8486}
}

@article{MTMT:34431216,
	title = {Multilingual Analysis and Visualization of Bibliographic Metadata and Texts with the AVOBMAT Research Tool},
	url = {https://m2.mtmt.hu/api/publication/34431216},
	author = {Péter, Róbert and Szántó, Zsolt and Biacsi, Zoltán and Berend, Gábor and Bilicki, Vilmos},
	doi = {10.5334/johd.175},
	journal = {Journal of Open Humanities Data},
	volume = {10},
	unique-id = {34431216},
	year = {2024},
	eissn = {2059-481X},
	orcid-numbers = {Berend, Gábor/0000-0002-3845-4978}
}

@{MTMT:34532466,
	title = {Milyen támadások fenyegetik az egészségügyi adatok bizalmasságát?},
	url = {https://m2.mtmt.hu/api/publication/34532466},
	author = {Alexin, Zoltán},
	booktitle = {I. Alverad-Bánki Nemzetközi Kiberbiztonsági Konferencia},
	unique-id = {34532466},
	year = {2023},
	pages = {56-56},
	orcid-numbers = {Alexin, Zoltán/0000-0003-0616-2169}
}

@{MTMT:34532434,
	title = {What sorts of attacks are threatening the confidentiality of medical data?},
	url = {https://m2.mtmt.hu/api/publication/34532434},
	author = {Alexin, Zoltán},
	booktitle = {I. Alverad-Bánki Nemzetközi Kiberbiztonsági Konferencia},
	unique-id = {34532434},
	year = {2023},
	pages = {57-57},
	orcid-numbers = {Alexin, Zoltán/0000-0003-0616-2169}
}