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dc.contributor.author |
NOUAR, IKRAME |
|
dc.date.accessioned |
2022-10-13T11:38:36Z |
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dc.date.available |
2022-10-13T11:38:36Z |
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dc.date.issued |
2022 |
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dc.identifier.uri |
http://dspace.univ-guelma.dz/jspui/handle/123456789/13246 |
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dc.description.abstract |
The Industrial Internet of Things (IIoT) is a collection of daily interconnected devices in an industrial environment, equipped with light processors and network cards, which can be managed by web services and/or other types of interface. IIoT network vulnerabilities increase dramatically with complex cyberattacks, such as botnets. A botnet attack is a large-scale cyberattack carried out by remotely controlled, malware-infected devices. It turns compromised devices into "zombie robots" for the botnet controller. A botnet can initiate a number of activities, such as Distributed Denial of Service (DDoS) attacks, keylogging, phishing, spamming, click fraud, spoofing, etc. . The objective of this subject is to study and propose a security method to detect Botnet attacks in IIoT systems. |
en_US |
dc.language.iso |
fr |
en_US |
dc.publisher |
UNIVERSITÉ DE GUELMA |
en_US |
dc.subject |
Cybersécurité, Apprentissage en profondeur, Botnet, Système de détec- tion de botnet, Internet des objects industriel (IIoT) |
en_US |
dc.title |
La détection des attaques Botnet dans l'Industrie Internet des objets (IIoT) |
en_US |
dc.type |
Working Paper |
en_US |
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