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    @Article{OJIOT_2025v10i1n01_Petrozziello,
        title     = {Automatic Identification and Classification of IoT Devices in Computer Networks - An Overview of Opportunities and Challenges},
        author    = {Maurizio Petrozziello and
                     Martin Kappes and
                     Christian Baun},
        journal   = {Open Journal of Internet Of Things (OJIOT)},
        issn      = {2364-7108},
        year      = {2025},
        volume    = {10},
        number    = {1},
        pages     = {1--29},
        url       = {https://www.ronpub.com/ojiot/OJIOT_2025v10i1n01_Petrozziello.html},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {Discovering IoT devices joining a network is essential for network management, security and optimization. Knowing what is happening on a computer network and finding those IoT devices is necessary to counter hacker attacks. To address the security challenges of IoT devices, we present identification (discovery) and classification. This gives the reader an overview of both areas, which need to be considered together; the very fact that there are many techniques and protocols for managing and communicating with IoT devices makes them both worth considering. Due to the differences in discovery and classification of IoT devices, we first present the provisioning part of the IoT device lifecycle and then discuss the different classification approaches. This thesis also describes the importance of feature extraction for classification and the difference between packet and flow features. In addition, this work discusses the difference between statistical, machine learning and artificial intelligence based classification methods, including large language models and quantum computing. In short, this thesis discusses relevant IoT device discovery and traffic classification techniques, applications, challenges and future directions.}
    }