The journal has corrected the article “Android Malware Detection Based on Behavioral-Level Features with Graph Convolutional Networks” [1].
Following publication, concerns were brought to the attention of the Editorial Office that parts of the article [2] were replicated in another Electronics publication [1].
Adhering to our complaint’s procedure, an investigation was conducted by the Editorial Office and Editorial Board. This investigation confirmed instances of replication, including the use of the MsDroid function. To address this issue and provide proper credit, the following citation has been added:
Ref. [2] He, Y.; Liu, Y.; Wu, L.; Yang, Z.; Ren, K.; Qin, Z. MsDroid: Identifying Malicious Snippets for Android Malware Detection. IEEE Trans. Dependable Secur. Comput. 2023, 20, 2025–2039.
This reference has been cited as ref. [12] in the following sections: 1. Introduction; 3. Methodology; 3.4.2. Loss Function; and 4.5. Detection Performance Comparison with Existing Methods.
Moreover, to enhance clarity, the term “MsDroid” was added to Table 10.
The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.
References
- Xu, Q.; Zhao, D.; Yang, S.; Xu, L.; Li, X. Android Malware Detection Based on Behavioral-Level Features with Graph Convolutional Networks. Electronics 2023, 12, 4817. [Google Scholar] [CrossRef]
- He, Y.; Liu, Y.; Wu, L.; Yang, Z.; Ren, K.; Qin, Z. MsDroid: Identifying Malicious Snippets for Android Malware Detection. IEEE Trans. Dependable Secur. Comput. 2023, 20, 2025–2039. [Google Scholar] [CrossRef]
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