Performance comparison of feature selection algorithms in context of P2P botnet detection

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

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Publication Details

Journal
International Journal of Information and Computer Security
Published
2025-01-01
DOI
https://doi.org/10.1504/ijics.2025.10071239
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Performance comparison of feature selection algorithms in context of P2P botnet detection

Sangita Baruah, Vaskar Deka
International Journal of Information and Computer Security
Network Security and Intrusion Detection
article

Performance comparison of feature selection algorithms in context of P2P botnet detection

Sangita Baruah, Vaskar Deka
article en

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

International Journal of Information and Computer SecurityVol. 1(1)
Openalex Percentile: Top 89%
Network Security and Intrusion Detection
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Performance comparison of feature selection algorithms in context of P2P botnet detection — Sangita Baruah, Vaskar Deka · International Journal of Information and Computer Security (2025) | TGRS Research Map | TGRS