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DC Field | Value | Language |
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dc.contributor.author | NOUAR, IKRAME | - |
dc.date.accessioned | 2022-10-13T11:38:36Z | - |
dc.date.available | 2022-10-13T11:38:36Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | http://dspace.univ-guelma.dz/jspui/handle/123456789/13246 | - |
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 |
Appears in Collections: | Master |
Files in This Item:
File | Description | Size | Format | |
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NOUAR_IKRAME_F5.pdf | 2,68 MB | Adobe PDF | View/Open |
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