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New Findings from University of Western Macedonia Describe Advances in Network and Service Management (A Unified Deep Learning Anomaly Detection and Classification Approach for Smart Grid Environments)

  • Jul 21, 2021 1:16 pm GMT
  • 86 views
Source: 
Network Daily News

2021 JUL 20 (NewsRx) -- By a News Reporter-Staff News Editor at Network Daily News -- Current study results on Networks - Network and Service Management have been published. According to news originating from Kozani, Greece, by NewsRx correspondents, research stated, “The interconnected and heterogeneous nature of the next-generation Electrical Grid (EG), widely known as Smart Grid (SG), bring severe cybersecurity and privacy risks that can also raise domino effects against other Critical Infrastructures (CIs).”

Financial support for this research came from European Unions Horizon 2020 research and innovation programme.

Our news journalists obtained a quote from the research from the University of Western Macedonia, “In this paper, we present an Intrusion Detection System (IDS) specially designed for the SG environments that use Modbus/Transmission Control Protocol (TCP) and Distributed Network Protocol 3 (DNP3) protocols. The proposed IDS called MENSA (anoMaly dEtection aNd claSsificAtion) adopts a novel Autoencoder-Generative Adversarial Network (GAN) architecture for (a) detecting operational anomalies and (b) classifying Modbus/TCP and DNP3 cyberattacks.”

According to the news editors, the research concluded: “In particular, MENSA combines the aforementioned Deep Neural Networks (DNNs) in a common architecture, taking into account the adversarial loss and the reconstruction difference.”

This research has been peer-reviewed.

For more information on this research see: A Unified Deep Learning Anomaly Detection and Classification Approach for Smart Grid Environments. IEEE Transactions on Network and Service Management, 2021;18(2):1137-1151. IEEE Transactions on Network and Service Management can be contacted at: Ieee-inst Electrical Electronics Engineers Inc, 445 Hoes Lane, Piscataway, NJ 08855-4141, USA. (Institute of Electrical and Electronics Engineers - http://www.ieee.org/; IEEE Transactions on Network and Service Management - http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4275028)

The news correspondents report that additional information may be obtained from Panagiotis Sarigiannidis, University of Western Macedonia, Dept. of Electrical and Computer Engineering, Kozani 50100, Greece. Additional authors for this research include Ilias Siniosoglou, Panagiotis Radoglou-Grammatikis, Georgios Efstathopoulos and Panagiotis Fouliras.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1109/TNSM.2021.3078381. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

 

(Our reports deliver fact-based news of research and discoveries from around the world.)

 

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