An Enhanced Approach for Intrusion Detection Modeling to Secure IoT Network by Using Big Data Analytics

IF 2 4区计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

IET Information Security Pub Date : 2026-06-17 DOI:10.1049/ise2/1301034

Ahmad Bilal, Huma Jamshed, Muhammad Ayoub Kamal, Qurat-ul-ain Mastoi, Toqeer Ali Syed, It Ee Lee

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引用次数: 0

Abstract

Since 1980, the arrival of the internet has made fabulous changes, and presently, the Internet of Things (IoT) is having the same track. IoT becomes more attractive due to its potential, but on the other hand, the IoT network is targeted to be demolished. IoT networks are always under the risk of denial of services (DoSs) attacks, which have shocking significance. Under this situation, the need for cybersecurity actions like intrusion detection systems (IDSs) are very much essential. The scope of this article is to propose an IDS for big data architecture. The IoT dataset (BoT-IoT) was used with libraries of Apache Spark, and experimental work was evaluated on the F1 measure. The dataset was divided into few parts; the partial part of dataset was examined by random forest for binary classification resulted in 98.6% F1 measure. Main categorical phase was resulted in 98.4% and subcategory classification resulted in 84.1% F1 measure. For overall classification of dataset decision tree resulted in 96.4 for binary classification, 78.6 for major category and 74% for categorical classification.

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利用大数据分析增强入侵检测建模以保护物联网网络

自1980年以来，互联网的到来带来了惊人的变化，目前，物联网（IoT）正走在同样的轨道上。物联网因其潜力而变得更具吸引力，但另一方面，物联网网络也成为了被拆除的目标。物联网网络始终处于拒绝服务（dos）攻击的风险之下，其意义令人震惊。在这种情况下，对入侵检测系统（ids）等网络安全行动的需求是非常必要的。本文的范围是为大数据架构提出一个IDS。将物联网数据集（BoT-IoT）与Apache Spark库结合使用，并在F1测度上对实验工作进行了评估。数据集被分成几个部分；对部分数据集进行随机森林检验进行二值分类，得到98.6%的F1测度。主分类阶段占98.4%，亚分类阶段占84.1%。对于数据集决策树的总体分类，二元分类的准确率为96.4，主要类别的准确率为78.6，类别分类的准确率为74%。

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来源期刊

IET Information Security 工程技术-计算机：理论方法

CiteScore

3.80

自引率

7.10%

发文量

审稿时长

8.6 months

期刊介绍： IET Information Security publishes original research papers in the following areas of information security and cryptography. Submitting authors should specify clearly in their covering statement the area into which their paper falls. Scope: Access Control and Database Security Ad-Hoc Network Aspects Anonymity and E-Voting Authentication Block Ciphers and Hash Functions Blockchain, Bitcoin (Technical aspects only) Broadcast Encryption and Traitor Tracing Combinatorial Aspects Covert Channels and Information Flow Critical Infrastructures Cryptanalysis Dependability Digital Rights Management Digital Signature Schemes Digital Steganography Economic Aspects of Information Security Elliptic Curve Cryptography and Number Theory Embedded Systems Aspects Embedded Systems Security and Forensics Financial Cryptography Firewall Security Formal Methods and Security Verification Human Aspects Information Warfare and Survivability Intrusion Detection Java and XML Security Key Distribution Key Management Malware Multi-Party Computation and Threshold Cryptography Peer-to-peer Security PKIs Public-Key and Hybrid Encryption Quantum Cryptography Risks of using Computers Robust Networks Secret Sharing Secure Electronic Commerce Software Obfuscation Stream Ciphers Trust Models Watermarking and Fingerprinting Special Issues. Current Call for Papers: Security on Mobile and IoT devices - https://digital-library.theiet.org/files/IET_IFS_SMID_CFP.pdf