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Volume 14
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Correction to Electronics 2022, 11(24), 4122.
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Correction

Correction: Osamy et al. Recent Advances and Future Prospects of Using AI Solutions for Security, Fault Tolerance, and QoS Challenges in WSNs. Electronics 2022, 11, 4122

by
Walid Osamy
1,2,*,†,
Ahmed M. Khedr
3,4,†,
Ahmed Salim
4,5,*,†,
Ahmed A. El-Sawy
2,6,†,
Mohammed Alreshoodi
1,† and
Ibrahim Alsukayti
7,†
1
Unit of Scientific Research, Applied College, Qassim University, Buraydah 52571, Saudi Arabia
2
Computer Science Department, Faculty of Computers and Artificial Intelligence, Benha University, Benha 13511, Egypt
3
Computer Science Department, University of Sharjah, Sharjah 27272, United Arab Emirates
4
Mathematics Department, Zagazig University, Zagazig 44519, Egypt
5
Department of Computer Science, College of Sciences and Arts, Al-Methnab, Qassim University, Buridah 52571, Saudi Arabia
6
Information Technology Department, Faculty of Technological Industry and Energy, Delta Technological University, Quesna 32631, Egypt
7
Department of Computer Science, College of Computer, Qassim University, Buraydah 51452, Saudi Arabia
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Electronics 2025, 14(22), 4440; https://doi.org/10.3390/electronics14224440
Submission received: 30 October 2025 / Accepted: 31 October 2025 / Published: 14 November 2025
Browse Figure
Versions Notes
In the original publication [1], concerns were raised regarding the following references, and they were removed from the reference list:
81. Vijayakumar, K.; Kumar, K.P.M.; Kottilingam, K.; Karthick, T.; Vijayakumar, P.; Ganeshkumar, P. An adaptive neuro-fuzzy logic based jamming detection system in WSN. Soft Comput. 2019, 23, 2655–2667.
109. Sumalatha, M.S.; Nandalal, V. An intelligent cross layer security based fuzzy trust calculation mechanism (CLS-FTCM) for securing wireless sensor network (WSN). J. Ambient Intell. Humaniz. Comput. 2021, 12, 4559–4573.
147. Nigam, G.K.; Dabas, C. ESO-LEACH: PSO based energy efficient clustering in LEACH. J. King Saud Univ.—Comput. Inf. Sci. 2021, 33, 947–954.
Due to the removal of the references, subsequent references and the corresponding citations in the main text have been adjusted to align with the numerical order. The following text has been updated.
In Section 2, “95 publications examined” was updated to “94 publications examined”.
In Section 5, the sentence “A fuzzy based jamming attack detection scheme by incorporating Fuzzy Inference System (FIS) (based on Takagi–Sugeno FL) and adaptive neuro-fuzzy inference system (ANFIS) is proposed in [81]. The two proposed methods make use of RSSI and packet delivery ratio (PDR) for jamming attack detection. The schemes are implemented in CH and BS to determine attacks at CMs and CH. The use of FL helps to optimize the used metrics for better identification of jammer attacks. The results indicate that the ANFIS-based scheme achieves better performance than the FIS-based scheme.” was deleted.
In Section 5, the sentence “A cross layer protection method based on fuzzy logic and trust values is proposed in [109]. It employs several parameters retrieved from cross-layer data to mitigate the impacts of safety threats in WSN. The fault tracking mechanism uses an enhanced CNN model based on trustworthiness to discover malicious nodes in WSN.” was deleted.
In Section 7, the sentence “The proposed technique improves the overall network performance by 10.00%, 23.75%, and 54.54% when compared to ESO [147], GECR [148], and LEACH [140]” was updated to “The proposed technique improves the overall network performance by 23.75% and 54.54% when compared to GECR [145] and LEACH [138].”
In Section 8, “Overall, 28% of papers applied SI followed by Hybrid by 21%, 21% for FL, then 19% for deep learning” was updated to “Overall, 29% of papers applied SI followed by Hybrid by 21%, 19% for FL, then 19% for deep learning”.
In Table 3, the row for reference [81] was removed.
Figure 3 was updated accordingly:
The authors clarify that the scientific conclusions remain unchanged despite the removal of the references from the manuscript. These corrections have been approved by the Academic Editor. The original publication has also been updated.

Reference

  1. Osamy, W.; Khedr, A.M.; Salim, A.; El-Sawy, A.A.; Alreshoodi, M.; Alsukayti, I. Recent Advances and Future Prospects of Using AI Solutions for Security, Fault Tolerance, and QoS Challenges in WSNs. Electronics 2022, 11, 4122. [Google Scholar] [CrossRef]
Electronics 14 04440 g003
Figure 3. AI approaches in relation to different WSN challenges.
Figure 3. AI approaches in relation to different WSN challenges.
Electronics 14 04440 g003
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MDPI and ACS Style

Osamy, W.; Khedr, A.M.; Salim, A.; El-Sawy, A.A.; Alreshoodi, M.; Alsukayti, I. Correction: Osamy et al. Recent Advances and Future Prospects of Using AI Solutions for Security, Fault Tolerance, and QoS Challenges in WSNs. Electronics 2022, 11, 4122. Electronics 2025, 14, 4440. https://doi.org/10.3390/electronics14224440

AMA Style

Osamy W, Khedr AM, Salim A, El-Sawy AA, Alreshoodi M, Alsukayti I. Correction: Osamy et al. Recent Advances and Future Prospects of Using AI Solutions for Security, Fault Tolerance, and QoS Challenges in WSNs. Electronics 2022, 11, 4122. Electronics. 2025; 14(22):4440. https://doi.org/10.3390/electronics14224440

Chicago/Turabian Style

Osamy, Walid, Ahmed M. Khedr, Ahmed Salim, Ahmed A. El-Sawy, Mohammed Alreshoodi, and Ibrahim Alsukayti. 2025. "Correction: Osamy et al. Recent Advances and Future Prospects of Using AI Solutions for Security, Fault Tolerance, and QoS Challenges in WSNs. Electronics 2022, 11, 4122" Electronics 14, no. 22: 4440. https://doi.org/10.3390/electronics14224440

APA Style

Osamy, W., Khedr, A. M., Salim, A., El-Sawy, A. A., Alreshoodi, M., & Alsukayti, I. (2025). Correction: Osamy et al. Recent Advances and Future Prospects of Using AI Solutions for Security, Fault Tolerance, and QoS Challenges in WSNs. Electronics 2022, 11, 4122. Electronics, 14(22), 4440. https://doi.org/10.3390/electronics14224440

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