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    Real-Time Monitoring and Scalable Messaging of SCADA Networks Data: A Case Study on Cyber-Physical Attack Detection in Water Distribution System
    (Springer Science and Business Media Deutschland GmbH, 2022) Balta, Seda; Zavrak, S.; Eken, S.
    SCADA networks, which are widely used by governments around the world to run computers and applications that perform a wide range of important functions and provide critical services to their infrastructure, are becoming increasingly popular among organizations. Because of their critical role in the infrastructure, as well as the fact that they are a potential target for cyberattacks, they must be secured and protected in some way at all times. In this study, we propose a topic-based pub/sub messaging system based on Apache Spark and Apache Kafka for real-time monitoring and detection of cyber-physical attacks in SCADA systems, which can be used in conjunction with other currently available systems. There are a variety of traditional machine learning approaches used in conjunction with a deep learning encoded decoder algorithm to create the mechanism for attack detection. The performance results demonstrate that our system outperforms the current state of the art described in the literature in this field. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
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    Retrraction note: Leakage detection and localization on water transportation pipelines: a multi-label classification approach (Neural Computing and Applications, (2017), 28, 10, (2905-2914), 10.1007/s00521-017-2872-4)
    (Springer Science and Business Media Deutschland GmbH, 2024) Kayaalp, F.; Zengin, A.; Kara, R.; Zavrak, S.
    The Editor-in-Chief and the publisher have retracted this article. The article was submitted to be part of a guest-edited issue. An investigation by the publisher found a number of articles, including this one, with a number of concerns, including but not limited to compromised editorial handling and peer review process, inappropriate or irrelevant references or not being in scope of the journal or guest-edited issue. Based on the investigation's findings the Editor-in-Chief therefore no longer has confidence in the results and conclusions of this article. Fatih Kayaalp and Sultan Zavrak disagree with this retraction. Ahmet Zengin has not clearly stated whether or not they agree with this retraction. Resul Kara did not respond to correspondence from the publisher about this retraction. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.