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Biometria behawioralna i “tradycyjna“ w mobilnych usługach bankowych - stan oraz przyszłe możliwości zastosowania

100%
Kałużny P., Stolarski P.
Bezpieczny Bank
|
2019
|
vol. 74
|
issue 1
139-161
EN
The article characterizes traditional (physical) and behavioral biometrics methods, which can be applied in authentication procedures in banking on mobile devices. Moreover, the model of authentication with the use of behavioral biometric methods was presented. Such model may be used in the future banking applications. A wide overview of authentication methods in banking is presented in the article, including current state of the mobile payment market and a summary of the most important concepts and ideas connected with the authentication methods used in information systems. The text also presents practical implications resulting from the use of behavioral methods in the financial sector and the discussion over the example scenarios of proposed methods.
PL
W artykule scharakteryzowano tradycyjne (fizyczne) i behawioralne metody biometryczne, możliwe do wykorzystania w procesach uwierzytelniania w bankowości w urządzeniach mobilnych. Zaproponowano model uwierzytelniania za pomocą biometrii behawioralnej, który może zostać wdrożony w sektorze usług finansowych. Dokonano też analizy metod uwierzytelniania w bankowości, ze szczególnym uwzględnieniem metod zabezpieczeń wykorzystywanych w systemach informatycznych. Scharakteryzowano również stan rynku usług płatności mobilnych. Wreszcie wskazane zostały praktyczne implikacje zastosowania metod biometrycznych w usługach bankowych wraz z dyskusją przykładowych scenariuszy stosowania metod biometrii behawioralnej.
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Artificial intelligence-friend or foe in fake news campaigns

61%
Węcel K., Sawiński M., Stróżyna M., Lewoniewski W., Stolarski P., Księżniak E., Abramowicz W.
Economics and Business Review
|
2023
|
vol. 9
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issue 2
41-70
EN
In this paper the impact of large language models (LLM) on the fake news phenomenon is analysed. On the one hand decent text‐generation capabilities can be misused for mass fake news production. On the other, LLMs trained on huge volumes of text have already accumulated information on many facts thus one may assume they could be used for fact‐checking. Experiments were designed and conducted to verify how much LLM responses are aligned with actual fact‐checking verdicts. The research methodology consists of an experimental dataset preparation and a protocol for interacting with ChatGPT, currently the most sophisticated
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