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Zero-Day Attack Identification in Streaming Data Using Semantics and Spark

Research article (2017 IEEE International Congress on Big Data (BigData Congress), 2017) · cited 16× · AI/ML
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Zero-Day Attack Identification in Streaming Data Using Semantics and Spark

Summary

Zero-Day Attack Identification in Streaming Data Using Semantics and Spark is a scholarly article[1].

Key Facts

  • Zero-Day Attack Identification in Streaming Data Using Semantics and Spark's instance of is recorded as scholarly article[2].

Related Entities

Ceorge Karabatis

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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). Zero-Day Attack Identification in Streaming Data Using Semantics and Spark. Retrieved May 24, 2026, from https://4ort.xyz/entity/zero-day-attack-identification-in-streaming-data-using-semantics-and-spark
MLA “Zero-Day Attack Identification in Streaming Data Using Semantics and Spark.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/zero-day-attack-identification-in-streaming-data-using-semantics-and-spark.
BibTeX @misc{4ortxyz_zero-day-attack-identification-in-streaming-data-using-semantics-and-spark_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Zero-Day Attack Identification in Streaming Data Using Semantics and Spark}}, year = {2026}, url = {https://4ort.xyz/entity/zero-day-attack-identification-in-streaming-data-using-semantics-and-spark}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Zero-Day Attack Identification in Streaming Data Using Semantics and Spark — https://4ort.xyz/entity/zero-day-attack-identification-in-streaming-data-using-semantics-and-spark (retrieved 2026-05-24)

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