Network Intrusion Detection With a Hashing Based Apriori Algorithm Using Hadoop Mapreduce

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Date

2019

Journal Title

Journal ISSN

Volume Title

Publisher

Mdpi

Open Access Color

GOLD

Green Open Access

No

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No
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Top 10%
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Top 10%
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Top 10%

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Abstract

Ubiquitous nature of Internet services across the globe has undoubtedly expanded the strategies and operational mode being used by cybercriminals to perpetrate their unlawful activities through intrusion on various networks. Network intrusion has led to many global financial loses and privacy problems for Internet users across the globe. In order to safeguard the network and to prevent Internet users from being the regular victims of cyber-criminal activities, new solutions are needed. This research proposes solution for intrusion detection by using the improved hashing-based Apriori algorithm implemented on Hadoop MapReduce framework; capable of using association rules in mining algorithm for identifying and detecting network intrusions. We used the KDD dataset to evaluate the effectiveness and reliability of the solution. Our results obtained show that this approach provides a reliable and effective means of detecting network intrusion.

Description

Misra, Sanjay/0000-0002-3556-9331; Maskeliunas, Rytis/0000-0002-2809-2213; Damaševičius, Robertas/0000-0001-9990-1084; azeez, nureni ayofe/0000-0002-1475-2612

Keywords

association rule mining, intrusion detection, cyberattack, network security, apriori, MapReduce, apriori, association rule mining, cyberattack, intrusion detection, network security, MapReduce

Turkish CoHE Thesis Center URL

Fields of Science

0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Citation

WoS Q

Q2

Scopus Q

Q2
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OpenCitations Citation Count
34

Source

Computers

Volume

8

Issue

4

Start Page

86

End Page

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Citations

CrossRef : 34

Scopus : 39

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Mendeley Readers : 49

SCOPUS™ Citations

39

checked on Jan 22, 2026

Web of Science™ Citations

24

checked on Jan 22, 2026

Page Views

8

checked on Jan 22, 2026

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6.21327101

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