Deployment of Electricity-theft Detection Infrastructure in Chadian Smart Grid Networks

Author(s):  
Cherifa Boucetta ◽  
Olivier Flauzac ◽  
Bachar Salim Haggar ◽  
Abdel-Nassir Mahamat Nassour ◽  
Florent Nolot
Author(s):  
Cherifa Boucetta ◽  
Olivier Flauzac ◽  
Bachar Salim Haggar ◽  
Abdel-Nassir Mahamat Nassour ◽  
Florent Nolot

2021 ◽  
Vol 13 (5) ◽  
pp. 2549
Author(s):  
Shahid Mahmood ◽  
Moneeb Gohar ◽  
Jin-Ghoo Choi ◽  
Seok-Joo Koh ◽  
Hani Alquhayz ◽  
...  

Smart Grid (SG) infrastructure is an energy network connected with computer networks for communication over the internet and intranets. The revolution of SGs has also introduced new avenues of security threats. Although Digital Certificates provide countermeasures, however, one of the issues that exist, is how to efficiently distribute certificate revocation information among Edge devices. The conventional mechanisms, including certificate revocation list (CRL) and online certificate status protocol (OCSP), are subjected to some limitations in energy efficient environments like SG infrastructure. To address the aforementioned challenges, this paper proposes a scheme incorporating the advantages and strengths of the fog computing. The fog node can be used for this purpose with much better resources closer to the edge. Keeping the resources closer to the edge strengthen the security aspect of smart grid networks. Similarly, a fog node can act as an intermediate Certification Authority (CA) (i.e., Fog Node as an Intermediate Certification Authority (FONICA)). Further, the proposed scheme has reduced storage, communication, processing overhead, and latency for certificate verification at edge devices. Furthermore, the proposed scheme reduces the attack surface, even if the attacker becomes a part of the network.


2021 ◽  
Vol 11 (1) ◽  
pp. 401
Author(s):  
Rajiv Punmiya ◽  
Sangho Choe

In the near future, it is highly expected that smart grid (SG) utilities will replace existing fixed pricing with dynamic pricing, such as time-of-use real-time tariff (ToU). In ToU, the price of electricity varies throughout the whole day based on the respective utilities’ decisions. We classify the whole day into two periods with very high and low probabilities of theft activities, termed as the “theft window” and “non-theft window”, respectively. A “smart” malicious consumer can adjust his/her theft to mostly targeting the theft window, manipulate actual usage reporting to outsmart existing theft detectors, and achieve the goal of “paying reduced tariff”. Simulation results show that existing schemes do not detect well such window-based theft activities conversely exploiting ToU strategies. In this paper, we begin by introducing the core concept of window-based theft cases, which is defined at the basis of ToU pricing as well as consumption usage. A modified extreme gradient boosting (XGBoost) based machine learning (ML) technique called dynamic electricity theft detector (DETD) has been presented to detect a new type of theft cases.


IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 17896-17903 ◽  
Author(s):  
Aljawharah Alnasser ◽  
Hongjian Sun

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