The Mirai botnet and the IoT Zombie Armies

Kambourakis, Georgios; Kolias, Constantinos; Stavrou, Angelos

doi:10.1109/milcom.2017.8170867

Cited by 158 publications

(74 citation statements)

References 3 publications

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“…IoT devices and generated over 620 gigabits per second of traffic [10] . Notable targets included the website of cybersecurity journalist Brian Krebs, French web host OVH, and Internet performance and domain service Dyn, [10] resulting in downtime for many popular websites such as Twitter, Netflix, Reddit, and GitHub for several hours [11] .…”

Section: Security Threatsmentioning

confidence: 99%

“…Notable targets included the website of cybersecurity journalist Brian Krebs, French web host OVH, and Internet performance and domain service Dyn, [10] resulting in downtime for many popular websites such as Twitter, Netflix, Reddit, and GitHub for several hours [11] . Whereas most botnets have formed due to unsuspecting computer users downloading malware onto their computers or smartphones that connects it to the botnet, Mirai gained notoriety for targeting IoT devices and infecting them without the user knowing about it.…”

Section: Security Threatsmentioning

confidence: 99%

“…Mirai primarily targets Linux-based IoT devices that use hardware architectures such as ARM, MIPS, SPARC, and Intel x86 [10] . In particular, devices such as DVRs, webcams, and routers that run BusyBox are vulnerable to Mirai [11] .…”

Section: Security Threatsmentioning

confidence: 99%

“…Users who have a device infected with the Mirai malware would not even know their device was infected, unlike personal computers which would often experience slowdown and display erratic behavior and antivirus warnings indicating a possible malware infection. The hacker uses a Command and Control (C&C) server to control the botnet, a loader server to install the malware onto target devices, and a report server to view the bots that are online [10] . When the attacker or an infected bot launches Mirai, the program randomly scans the IP space for victim devices to install to [10] .…”

Section: Security Threatsmentioning

confidence: 99%

“…The hacker uses a Command and Control (C&C) server to control the botnet, a loader server to install the malware onto target devices, and a report server to view the bots that are online [10] . When the attacker or an infected bot launches Mirai, the program randomly scans the IP space for victim devices to install to [10] . For each IP address, the program probes Telnet ports 23 and 2323 to check for a username and password prompt, indicating that there is a device connected to that IP address that could potentially be exploited [10] .…”

Section: Security Threatsmentioning

confidence: 99%

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Internet of Things Security: Ongoing Threats and Proposed Solutions

Strba¹

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Section: Security Threatsmentioning

confidence: 99%

Section: Security Threatsmentioning

confidence: 99%

Section: Security Threatsmentioning

confidence: 99%

Section: Security Threatsmentioning

confidence: 99%

Section: Security Threatsmentioning

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Internet of Things Security: Ongoing Threats and Proposed Solutions

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Securing Internet of Things (IoT) with machine learning

Zeadally

Tsikerdekis

2019

Int J Communication

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Advances in hardware, software, communication, embedding computing technologies along with their decreasing costs and increasing performance have led to the emergence of the Internet of Things (IoT) paradigm. Today, several billions of Internet-connected devices are part of the IoT ecosystem.IoT devices have become an integral part of the information and communication technology (ICT) infrastructure that supports many of our daily activities. The security of these IoT devices has been receiving a lot of attention in recent years. Another major recent trend is the amount of data that is being produced every day which has reignited interest in technologies such as machine learning and artificial intelligence. We investigate the potential of machine learning techniques in enhancing the security of IoT devices. We focus on the deployment of supervised, unsupervised learning techniques, and reinforcement learning for both host-based and network-based security solutions in the IoT environment. Finally, we discuss some of the challenges of machine learning techniques that need to be addressed in order to effectively implement and deploy them so that they can better protect IoT devices. KEYWORDSattack, internet of things, machine learning, security

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A comprehensive study of Mozi botnet

Qin

Zhang

et al. 2022

Int J of Intelligent Sys

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With the trend of digital transformation of enterprises, the use of Internet of Things (IoT) devices is increasing. IoT devices that are not protected by security measures have gradually become targets of attackers. Attackers use weak passwords and software vulnerabilities in the device to invade the device and control it to become a node of the botnet. The Mozi botnet was discovered in December 2019, and its attention has increased day by day, and its influence once exceeded Mirai. After a preliminary reverse analysis of the Mozi samples, we have continued to track the development and changes of the Mozi botnet since February 2021. First, through the in-depth analysis of the communication principles of the Mozi botnet and the distributed sloppy hash table protocol, we have proposed an in-depth analysis of the Mozi botnet. The active detection method of Mozi, through daily and continuous tracking of the number of Mozi nodes, is infinitely close to the boundary of the Mozi network. On the basis of the collected detection data, we give our conclusions on Mozi's node size, global geographic distribution, 24-hour global activity, equipment composition, and Mozi botnet countermeasures.Through this study, we found that the security of IoT devices around the world is not optimistic, and there is an urgent need to increase the security protection

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The Mirai botnet and the IoT Zombie Armies

Cited by 158 publications

References 3 publications

Internet of Things Security: Ongoing Threats and Proposed Solutions

Internet of Things Security: Ongoing Threats and Proposed Solutions

Securing Internet of Things (IoT) with machine learning

A comprehensive study of Mozi botnet

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