Big Data Analytics for Event Detection in the IoT-Multicriteria Approach

Janusz Granat, Jordi Mongay Batalla, Constandinos X. Mavromoustakis, George Mastorakis

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)


    Security requirements applicable to the Internet of Things (IoT) should aim to ensure integrity, authenticity and authorization, confidentiality/privacy, nonrepudiation, and last but not least, availability. Classic data analysis algorithms are no longer valid for assuring security at all levels and a new approach to data sciences is required, which would consider the complex heterogeneous nature of the IoT, taking also into consideration, its potential to deploy cross layer for security assessment mechanisms. Furthermore, data collected from sensors should be processed and analyzed nearly in real time. The classical algorithms have two main drawbacks: 1) they deal with unidimensional data and 2) they fail to assume limited information available in the stream data processing. In this article, new solutions are discussed and presented that detect anomalies in data streams nearly in real time. Specifically, we propose: 1) an event detection method used in unidimensional data streams and relying on the event strength function, which is an extension of the typical 'True or False' decision-making scheme; 2) multiple-criteria event detection approaches based on the Dynamic Pareto Set, introducing a time-depending decision set; and 3) an anomaly detection method based on multicriteria temporal graphs, combining the dynamics of decision making and multicriteria. All the proposed algorithms are presented by means of their formal description and are illustrated with examples.

    Original languageEnglish
    Article number8920092
    Pages (from-to)4418-4430
    Number of pages13
    JournalIEEE Internet of Things Journal
    Issue number5
    Publication statusPublished - May 2020


    • Anomaly detection
    • data mining
    • Internet of Things (IoT) security
    • multicriteria decision making


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