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Machine learning on merging static and dynamic features to identify malicious mobile apps

Research article (2017 Ninth International Conference on Ubiquitous and Future Networks (ICUFN), 2017) · cited 10× · AI/ML
academia openalex:W2741895717
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Machine learning on merging static and dynamic features to identify malicious mobile apps

Summary

Machine learning on merging static and dynamic features to identify malicious mobile apps is a scholarly article[1].

Key Facts

  • Machine learning on merging static and dynamic features to identify malicious mobile apps's instance of is recorded as scholarly article[2].

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Machine learning on merging static and dynamic features to identify malicious mobile apps. Retrieved May 24, 2026, from https://4ort.xyz/entity/machine-learning-on-merging-static-and-dynamic-features-to-identify-malicious-mobile-apps
MLA “Machine learning on merging static and dynamic features to identify malicious mobile apps.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/machine-learning-on-merging-static-and-dynamic-features-to-identify-malicious-mobile-apps.
BibTeX @misc{4ortxyz_machine-learning-on-merging-static-and-dynamic-features-to-identify-malicious-mobile-apps_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Machine learning on merging static and dynamic features to identify malicious mobile apps}}, year = {2026}, url = {https://4ort.xyz/entity/machine-learning-on-merging-static-and-dynamic-features-to-identify-malicious-mobile-apps}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Machine learning on merging static and dynamic features to identify malicious mobile apps — https://4ort.xyz/entity/machine-learning-on-merging-static-and-dynamic-features-to-identify-malicious-mobile-apps (retrieved 2026-05-24)

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