{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T16:25:45Z","timestamp":1781108745428,"version":"3.54.1"},"reference-count":56,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2021,4,2]],"date-time":"2021-04-02T00:00:00Z","timestamp":1617321600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Cyber-security of modern power systems has captured a significant interest. The vulnerabilities in the cyber infrastructure of the power systems provide an avenue for adversaries to launch cyber attacks. An example of such cyber attacks is False Data Injection Attacks (FDIA). The main contribution of this paper is to analyze the impact of FDIA on the cost of power generation and the physical component of the power systems. Furthermore, We introduce a new FDIA strategy that intends to maximize the cost of power generation. The viability of the attack is shown using simulations on the standard IEEE bus systems using the MATPOWER MATLAB package. We used the genetic algorithm (GA), simulated annealing (SA) algorithm, tabu search (TS), and particle swarm optimization (PSO) to find the suitable attack targets and execute FDIA in the power systems. The proposed FDIA increases the generation cost by up to 15.6%, 45.1%, 60.12%, and 74.02% on the 6-bus, 9-bus, 30-bus, and 118-bus systems, respectively. Finally, a rule-based FDIA detection and prevention mechanism is proposed to mitigate such attacks on power systems.<\/jats:p>","DOI":"10.3390\/s21072478","type":"journal-article","created":{"date-parts":[[2021,4,2]],"date-time":"2021-04-02T10:34:09Z","timestamp":1617359649000},"page":"2478","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Rule-Based Detection of False Data Injections Attacks against Optimal Power Flow in Power Systems"],"prefix":"10.3390","volume":"21","author":[{"given":"Sani","family":"Umar","sequence":"first","affiliation":[{"name":"Computer Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6414-3391","authenticated-orcid":false,"given":"Muhamad","family":"Felemban","sequence":"additional","affiliation":[{"name":"Computer Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1726","DOI":"10.1109\/JIOT.2017.2709252","article-title":"Toward data integrity attacks against optimal power flow in smart grid","volume":"4","author":"Yang","year":"2017","journal-title":"IEEE Internet Things J."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1109\/TPWRS.2004.825888","article-title":"Analysis of electric grid security under terrorist threat","volume":"19","author":"Salmeron","year":"2004","journal-title":"IEEE Trans. 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