Anomaly detection and security threats in Internet of Things: A study of data integrity in the measurement process

• Autorzy: Paluch Adam , Paluch-Ferszt Monika , Kalisz Michał , Gryniewicz-Jaworska Michalina

Identyfikatory

DOI

10.12913/22998624/204321

• Języki publikacji: EN

Abstrakty

EN

The publication presents potential places of conscious or unconscious interference or degradation of data collected using a distributed system of sensors and/or other IoT devices. Places of possible interference in the measurement data are indicated from the very beginning of the measurement chain – from a single measurement element, through data conversion, transmission, processing, storage, analysis to interpretation. Threats are indicated not only of technical but also economic nature. Examples are presented that are intended to show how the flow of data can affect decision-making and how the lack of knowledge about the measurement context can affect their interpretation. Possible anomaly detection mechanisms are also indicated, considering new, developing techniques.

Słowa kluczowe

EN

big data; mesh measurement; machine learning; internet of things; IoT; influence point; telemetry

• Wydawca: Lublin University of Technology ; Polish Society of Ecological Engineering (PTIE), Branch of PTIE in Lublin
• Czasopismo: Advances in Science and Technology. Research Journal
• Rocznik: 2025
• Tom: Vol. 19, no. 7
• Strony: 415--426
• Opis fizyczny: Bibliogr. 12 poz., fig., tab.

Twórcy

autor

Paluch Adam

• Under Ant sp. z o. o. sp. k., Łączyny 4, 02-820 Warsaw, Poland

autor

Paluch-Ferszt Monika

• Heavy Ion Laboratory, University of Warsaw, ul. Pasteura 5A, 02-093, Warszawa, Poland

• https://orcid.org/0000-0003-1839-0409

autor

Kalisz Michał

• Department of the Foundations of Computer Science, Faculty of Philosophy, The John Paul II Catholic University of Lublin, Aleje Racławickie 14, 20-950 Lublin, Poland

• https://orcid.org/0000-0003-1955-1884

autor

Gryniewicz-Jaworska Michalina

• WSEI University, Projektowa 4, 20-209 Lublin, Poland

• https://orcid.org/0000-0001-5862-5749

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).