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Evading Botnet Detectors Based on Flows and Random Forest with Adversarial Samples

Research article (2018 IEEE 17th International Symposium on Network Computing and Applications (NCA), 2018) · cited 50× · AI/ML
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Evading Botnet Detectors Based on Flows and Random Forest with Adversarial Samples

Summary

Evading Botnet Detectors Based on Flows and Random Forest with Adversarial Samples is a scholarly article[1].

Key Facts

  • Evading Botnet Detectors Based on Flows and Random Forest with Adversarial Samples's instance of is recorded as scholarly article[2].

Related Entities

Giovanni Apruzzese

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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). Evading Botnet Detectors Based on Flows and Random Forest with Adversarial Samples. Retrieved May 24, 2026, from https://4ort.xyz/entity/evading-botnet-detectors-based-on-flows-and-random-forest-with-adversarial-samples
MLA “Evading Botnet Detectors Based on Flows and Random Forest with Adversarial Samples.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/evading-botnet-detectors-based-on-flows-and-random-forest-with-adversarial-samples.
BibTeX @misc{4ortxyz_evading-botnet-detectors-based-on-flows-and-random-forest-with-adversarial-samples_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Evading Botnet Detectors Based on Flows and Random Forest with Adversarial Samples}}, year = {2026}, url = {https://4ort.xyz/entity/evading-botnet-detectors-based-on-flows-and-random-forest-with-adversarial-samples}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Evading Botnet Detectors Based on Flows and Random Forest with Adversarial Samples — https://4ort.xyz/entity/evading-botnet-detectors-based-on-flows-and-random-forest-with-adversarial-samples (retrieved 2026-05-24)

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