DDoS in the IoT: Mirai and Other Botnets

By Constantinos Kolias, Georgios Kambourakis, Angelos Stavrou, J. Voas. Computer, 2017

1,637 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/d9b3fa2627813fe92323a7a8d25cd12e4197ead6

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Citations in the corpus

A Supervised Intrusion Detection System for Smart Home IoT Devices (2019, background): “2) DDoS/Botnets: An attacker aims to compromise a large amount of vulnerable IoT devices in order to be able to deploy a significantly more severe DoS or other attacks [44].”
A Roadmap Toward the Resilient Internet of Things for Cyber-Physical Systems (2018, methodology): “An example is the MIRAI botnet that in 2016 have exploited more than 400000 devices connected through the IoT as a vehicle to launch some of the most potent distributed denial-of-service (DDoS) in history [18].”
FLAME: Taming Backdoors in Federated Learning (2022, methodology): “We test backdoor attacks on IoT anomaly-based intrusion detection systems that often represent critical security applications [5, 16, 27, 30, 44, 45, 55].”
DÏoT: A Federated Self-learning Anomaly Detection System for IoT (2018, methodology): “3) Attack dataset: For evaluating the effectiveness of DÏOT at detecting attacks, we collected a dataset comprising malicious traffic of IoT devices infected with Mirai malware [1], [3] in all four different attack stages discussed below: preinfection, infection, scanning and DoS attacks (as a monet”
The Future of Healthcare Internet of Things: A Survey of Emerging Technologies (2020, background): “…critical threat to an IoT system Malwares such as Mirai ﬂood the network with a massive amount of data, therefore rendering the system unresponsive [57] Securing the sensor devices acts as the ﬁrst line of defense against the security threats as the access to the sensor allows an attacker many…”
Cyber-physical systems security: Limitations, issues and future trends (2020, positive): “– Botnets: this includes exploiting CPS devices vulnerabilities to turn them into bots or zombies, mainly to conduct hardly-traceable DDoS attacks (i.e Ram-nit (2015) [188], Mirai (2016) [189], Smominru botnet (2017) [188], Mootbot (2020) [190], Wild-Pressure and VictoryGate (2020).)”
Security and Privacy in Smart Farming: Challenges and Opportunities (2020, methodology): “IoT devices used in smart farming environments can always be used to launch large scale denial of service (DoS) attacks [69] similar to what happened in 2016 using Mirai botnet [70].”
A Survey on IoT Security: Application Areas, Security Threats, and Solution Architectures (2019, methodology): “The Mirai botnet attack as discussed in Section I used this vulnerability and blocked various servers by constantly propagating requests to the weakly conﬁgured IoT devices [28].”
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security (2018, background): “Mirai is an exceptional type of botnets that has recently caused large-scale DDoS attacks by using IoT devices [7], [9].”
The industrial internet of things (IIoT): An analysis framework (2018, methodology): “The operating system, software type and updatability are relevant given the launch of IoT botnets, for example the Mirai botnet [58,59], as they represent a potential vulnerability and if not updateable may limit the ability to respond to botnet malware.”
Smart Anomaly Detection in Sensor Systems (2020, background): “This is the case of the recent botnet Mirai [146], based on a infectious propagation mechanism aimed at poisoning IP-cameras systems.”
Applications of Blockchains in the Internet of Things: A Comprehensive Survey (2019, methodology): “After the source code of the Mirai botnet was publicly released, more attacks followed, most notably the attack in October 2016, which took many mainstream websites for several hours [145].”
Security of smart manufacturing systems (2018, background): “The Mirai botnet and its variants [20,21] show how attacks could leverage the lack of security in IoT devices and conduct successful attacks that could cause production downtime and equipment failure, or reputational damage as the source of the attack on other systems.”
Towards the Development of Realistic Botnet Dataset in the Internet of Things for Network Forensic Analytics: Bot-IoT Dataset (2018, background): “The DDoS and DoS attack types included in the dataset are described as follows: Distributed Denial of Service (DDoS) and Denial of Service (DoS) attacks are performed by a group of compromised machines called Bots, and target a remote machine, usually a server[26][20][3].”