SwePub
Sök i LIBRIS databas

  Utökad sökning

id:"swepub:oai:DiVA.org:uu-500256"
 

Sökning: id:"swepub:oai:DiVA.org:uu-500256" > An enhanced intrusi...

An enhanced intrusion detection method for AIM of smart grid

Zhao, H. (författare)
Liu, G. (författare)
Sun, H. (författare)
visa fler...
Zhong, G. (författare)
Pang, S. (författare)
Qiao, S. (författare)
Lv, Z. (författare)
visa färre...
2023-02-03
2023
Engelska.
Ingår i: Journal of Ambient Intelligence and Humanized Computing. - : Springer Science and Business Media Deutschland GmbH. - 1868-5137 .- 1868-5145.
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • As a highly automated power transmission network, the smart grid can monitor each user and grid node and connect different devices to improve the function of conventional power network significantly, but this heterogeneous network also brings greater security risks, attackers can use vulnerabilities existing in smart grids. Intrusion Detection System (IDS) constitutes an important means to protect critical information from being leaked. in a smart grid environment. In this paper, we proposed an AMI intrusion detection model for smart grid, which is widely distributed in the three-layer architecture of the grid system through particle swarm algorithm combined with random forest method. To improve the model’s accuracy, this paper adopts the dynamic weight formula and various adaptive mutation methods to optimize the iterative process of the algorithm. Besides, we use parallel strategy to make up for the lack of precision in the mutation of the algorithm. The AM-PPSO algorithm proposed in this paper performs well in the CEC2017 benchmark function test, effectively ensuring the improvement of the RF classifier. Finally, we use NPL-KDD, UNSW-UB15, and X-IIoTID standard intrusion detection datasets to simulate, results show that our model achieves 97–99% classification of the three datasets. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Annan elektroteknik och elektronik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Other Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)

Nyckelord

Intrusion detection
Particle swarm algorithm
Random forest
Smart grid
Classification (of information)
Electric power system protection
Electric power transmission
Electric power transmission networks
Heterogeneous networks
Iterative methods
Network security
Conventional power
Grid node
Grid-connect
Intrusion detection method
Intrusion-Detection
Power transmission networks
Random forests
User nodes
Smart power grids

Publikations- och innehållstyp

ref (ämneskategori)
art (ämneskategori)

Hitta via bibliotek

Till lärosätets databas

Sök utanför SwePub

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy