A Privacy and Security Preservation Framework for D2D Communication Based Smart Grid Services

Bopape, Lebogang; Nleya, Bakhe; Khumalo, Philani

doi:10.1109/ictas47918.2020.233995

Cited by 1 publication

(1 citation statement)

References 14 publications

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“…All the problems above must be addressed critically to minimize and avoid possible failures or threats [6] that could affect the security of the devices or the system. As a measure to solve the previous problem, according to [7]- [9], in the field of SG, different algorithms have been tested to detect attacks on the network using Intrusion Detection System (IDS) such as Bro, Snort and Suricata or based on methods such as Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Gradient Boost Decision Trees (GBDT) and Convolutional Neural Networks (CNN).…”

Section: Introductionmentioning

confidence: 99%

Intrusion detection system in a hardware in the loop scenario

Berenice Arzate-Rueda,

Enrique Reyes-Archundia,

Juan C. Olivares-Rojas

et al. 2023

Global J. Eng. Technol. Adv.

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Detecting perturbation in electrical signals is crucial to assure power quality (PQ) and protect equipment connected to an electrical network. Some of the information generated by disturbances analysis can be communicated using Internet of Things (IoT) protocols, but it is vital to verify the integrity of the data. As a result of the lack of security presented by IoT devices, the proposal of this work is based on the implementation of an algorithm based on IDS that allows identifying attacks or failures in the security of an IoT-based PQ disturbance detection system implemented in a BeagleBone Black Wireless. The Sparta and Sqlmap programs were used as tools to perform tests and detect security flaws in the BeagleBone, verifying essential operations of the IDS.

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Section: Introductionmentioning

confidence: 99%