ReviewSensors (Basel, Switzerland)2024
Systematic Literature Review of IoT Botnet DDOS Attacks and Evaluation of Detection Techniques.
Review in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- NIDS-Mamba: Lightweight Network Intrusion Detection for IoT Sensor Networks via State Space Models.Sensors (Basel, Switzerland) · 2026Article
- Reinforcement Learning-Enhanced Botnet Defense System in Grid Topology Networks Using the SIRO Framework.Sensors (Basel, Switzerland) · 2026Article
- Relational Framework of Cyberattacks: Empirical Evidence from Multistage Incidents.Sensors (Basel, Switzerland) · 2025Article
- Evaluating machine learning approaches for multiple attack classification with improved computational efficiency in IoT networks.Scientific reports · 2025Article
- Lightweight machine learning framework for efficient DDoS attack detection in IoT networks.Scientific reports · 2025Article
- Hybrid recurrent with spiking neural network model for enhanced anomaly prediction in IoT networks security.Frontiers in artificial intelligence · 2025Article
- A Physical-Layer Security Cooperative Framework for Mitigating Interference and Eavesdropping Attacks in Internet of Things Environments.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Internet of Things (IoT) technology has become an inevitable part of our daily lives. With the increase in usage of IoT Devices, manufacturers continuously develop IoT technology. However, the security of IoT devices is left behind in those developments due to cost, size, and computational power limitations. Since these IoT devices are connected to the Internet and have low security levels, one of the main risks of these devices is being compromised by malicious malware and becoming part of IoT botnets. IoT botnets are used for launching different types of large-scale attacks including Distributed Denial-of-Service (DDoS) attacks. These attacks are continuously evolving, and researchers have conducted numerous analyses and studies in this area to narrow security vulnerabilities. This paper systematically reviews the prominent literature on IoT botnet DDoS attacks and detection techniques. Architecture IoT botnet DDoS attacks, evaluations of those attacks, and systematically categorized detection techniques are discussed in detail. The paper presents current threats and detection techniques, and some open research questions are recommended for future studies in this field.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.