NeuroMesh

Falco, Gregory; Li, Caleb; Fedorov, P. O.; Caldera, Carlos; Arora, Rahul; Jackson, Kelly

doi:10.1145/3312614.3312615

Cited by 25 publications

(8 citation statements)

References 4 publications

(3 reference statements)

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“…The researchers of [72] created a lightweight security IoT solution that uses hacker tools against hackers, an IoT vaccine, in essence. The solution provides IoT devices with managed protection and intelligence using a "friendly" botnet powered by the Bitcoin blockchain, a validated existing communication framework for distributed systems.…”

Section: Methods Based On Blockchain Technologymentioning

confidence: 99%

“…Most of the studies herein proposed techniques based on employing artificial intelligence (AI). AI is considered as an interesting approach in detecting IoT botnets because it can accelerate the process of making decisions, and these approaches and techniques could be integrated with different trendy technologies to form more powerful techniques, such as SDN [97][98][99] or blockchain [72]. Hence, more studies are required in this area.…”

Section: Methods and Techniquesmentioning

confidence: 99%

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Internet of Things Botnet Detection Approaches: Analysis and Recommendations for Future Research

et al. 2021

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Internet of Things (IoT) is promising technology that brings tremendous benefits if used optimally. At the same time, it has resulted in an increase in cybersecurity risks due to the lack of security for IoT devices. IoT botnets, for instance, have become a critical threat; however, systematic and comprehensive studies analyzing the importance of botnet detection methods are limited in the IoT environment. Thus, this study aimed to identify, assess and provide a thoroughly review of experimental works on the research relevant to the detection of IoT botnets. To accomplish this goal, a systematic literature review (SLR), an effective method, was applied for gathering and critically reviewing research papers. This work employed three research questions on the detection methods used to detect IoT botnets, the botnet phases and the different malicious activity scenarios. The authors analyzed the nominated research and the key methods related to them. The detection methods have been classified based on the techniques used, and the authors investigated the botnet phases during which detection is accomplished. This research procedure was used to create a source of foundational knowledge of IoT botnet detection methods. As a result of this study, the authors analyzed the current research gaps and suggest future research directions.

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Section: Methods Based On Blockchain Technologymentioning

confidence: 99%

Section: Methods and Techniquesmentioning

confidence: 99%

Internet of Things Botnet Detection Approaches: Analysis and Recommendations for Future Research

et al. 2021

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“…[ [22][23][24][25][26][27] Limited scope of botnet detection techniques ( Includes a larger breadth of more recent detection papers, such as [28,29] and more than 100 more papers compared to [22]. [30] Focuses specifically on DDoS botnet attacks without covering detection strategies.…”

Section: Paper Main Contribution and Reference Metricsmentioning

confidence: 99%

“…N/A. [29] Neural network-based detection of botnets is just one of many proposed methods of botnet detection. X.G.…”

Section: Neural Network Detection Mechanismsmentioning

confidence: 99%

“…More nontraditional methods like [96] seek to identify botnets through the usage of power consumption as the parameter for their CNN model. In [29] a similar lightweight solution is also mentioned for use in small memory capacity devices with low-power processors, since these are not able to have reliable anti-malware systems. It is based on the use of NeuroMesh, which is a combination of neural and mesh detection networks used to secure the devices.…”

Section: Neural Network Detection Mechanismsmentioning

confidence: 99%

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A Survey on Botnets: Incentives, Evolution, Detection and Current Trends

Stege

El-Habr

et al. 2021

Future Internet

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Botnets, groups of malware-infected hosts controlled by malicious actors, have gained prominence in an era of pervasive computing and the Internet of Things. Botnets have shown a capacity to perform substantial damage through distributed denial-of-service attacks, information theft, spam and malware propagation. In this paper, a systematic literature review on botnets is presented to the reader in order to obtain an understanding of the incentives, evolution, detection, mitigation and current trends within the field of botnet research in pervasive computing. The literature review focuses particularly on the topic of botnet detection and the proposed solutions to mitigate the threat of botnets in system security. Botnet detection and mitigation mechanisms are categorised and briefly described to allow for an easy overview of the many proposed solutions. The paper also summarises the findings to identify current challenges and trends within research to help identify improvements for further botnet mitigation research.

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BlockRAT: An Enhanced Remote Access Trojan Framework via Blockchain

Kang

Meng

et al. 2022

Science of Cyber Security

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NeuroMesh

Cited by 25 publications

References 4 publications

Internet of Things Botnet Detection Approaches: Analysis and Recommendations for Future Research

Internet of Things Botnet Detection Approaches: Analysis and Recommendations for Future Research

A Survey on Botnets: Incentives, Evolution, Detection and Current Trends

BlockRAT: An Enhanced Remote Access Trojan Framework via Blockchain

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