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Malware API Calls Detection Using Hybrid Logistic Regression and RNN Model

Research article (Applied Sciences, 2023) · cited 26× · AI/ML
academia openalex:W4367181633
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Malware API Calls Detection Using Hybrid Logistic Regression and RNN Model

Summary

Malware API Calls Detection Using Hybrid Logistic Regression and RNN Model is a scholarly article[1].

Key Facts

  • Malware API Calls Detection Using Hybrid Logistic Regression and RNN Model's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Malware API Calls Detection Using Hybrid Logistic Regression and RNN Model. Retrieved May 24, 2026, from https://4ort.xyz/entity/malware-api-calls-detection-using-hybrid-logistic-regression-and-rnn-model
MLA “Malware API Calls Detection Using Hybrid Logistic Regression and RNN Model.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/malware-api-calls-detection-using-hybrid-logistic-regression-and-rnn-model.
BibTeX @misc{4ortxyz_malware-api-calls-detection-using-hybrid-logistic-regression-and-rnn-model_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Malware API Calls Detection Using Hybrid Logistic Regression and RNN Model}}, year = {2026}, url = {https://4ort.xyz/entity/malware-api-calls-detection-using-hybrid-logistic-regression-and-rnn-model}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Malware API Calls Detection Using Hybrid Logistic Regression and RNN Model — https://4ort.xyz/entity/malware-api-calls-detection-using-hybrid-logistic-regression-and-rnn-model (retrieved 2026-05-24)

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