Integrating Anomaly Detection for Enhanced Data Protection in Cloud-Based Applications

Uproszczony widok
dc.contributor.authorCzerkas, Konrad
dc.contributor.authorDrozd, Michał
dc.contributor.authorDuraj, Agnieszka
dc.contributor.authorLichy, Krzysztof
dc.contributor.authorLipiński, Piotr
dc.contributor.authorMorawski, Michał
dc.contributor.authorNapieralski, Piotr
dc.contributor.authorPuchała, Dariusz
dc.contributor.authorKwapisz, Marcin
dc.contributor.authorWarcholiński, Adrian
dc.contributor.authorKarbowańczyk, Michał
dc.contributor.authorWosiak, Piotr
dc.date.accessioned2023-09-22T05:58:09Z
dc.date.available2023-09-22T05:58:09Z
dc.date.issued2023
dc.description.abstractIn this research, anomaly detection techniques and artificial neural networks were employed to address the issue of attacks on cluster computing systems. The study investigated the detection of Distributed Denial of Service (DDoS) and Partition attacks by monitoring metrics such as network latency, data transfer rate, and number of connections. Additionally, outlier detection algorithms, namely Local Outlier Factor (LOF) and COF, as well as ARIMA and SHESD models were tested for anomaly detection. Two types of neural network architectures, multi-layer perceptron (MLP) and recursive LSTM networks, were used to detect attacks by classifying events as “attack” or “no attack”. The study underscores the importance of implementing proactive security measures to protect cluster computing systems from cyber threats.en_EN
dc.identifier.citationCzerkas K., Drozd M., Duraj A., Lichy K., Lipiński P., Morawski M., Napieralski P., Puchała D., Kwapisz M., Warcholiński A., Karbowańczyk M., Wosiak P., Integrating Anomaly Detection for Enhanced Data Protection in Cloud-Based Applications. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 173-179, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.27.
dc.identifier.doi10.34658/9788366741928.27
dc.identifier.isbn978-83-66741-92-8
dc.identifier.urihttp://hdl.handle.net/11652/4803
dc.identifier.urihttps://doi.org/10.34658/9788366741928.27
dc.language.isoenen_EN
dc.page.numbers. 173-179
dc.publisherWydawnictwo Politechniki Łódzkiejpl_PL
dc.publisherLodz University of Technology Pressen_EN
dc.relation.ispartofWojciechowski A. (Ed.), Lipiński P. (Ed.)., Progress in Polish Artificial Intelligence Research 4, Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.
dc.rightsDla wszystkich w zakresie dozwolonego użytkupl_PL
dc.rightsFair use conditionen_EN
dc.rights.licenseLicencja PŁpl_PL
dc.rights.licenseLUT Licenseen_EN
dc.subjectcomputer gamesen_EN
dc.subjectartificial intelligenceen_EN
dc.subjectgry komputerowepl_PL
dc.subjectsztuczna inteligencjapl_PL
dc.titleIntegrating Anomaly Detection for Enhanced Data Protection in Cloud-Based Applicationsen_EN
dc.typeRozdział - monografiapl_PL
dc.typeChapter - monographen_EN

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