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A Extensive Study on DDosBotnet Attacks in Multiple Environments Using Deep Learning and Machine Learning Techniques
Every organization provides security for their systems, servers, and other I.T. infrastructure resources using regular anti-viruses and malware detection software. With the increase of access to smart devices and appliances through secured and unsecured networks, there is a requirement to design an...
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Published in: | ECS transactions 2022-04, Vol.107 (1), p.15181-15193 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Citations: | Items that cite this one |
Online Access: | Get full text |
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Summary: | Every organization provides security for their systems, servers, and other I.T. infrastructure resources using regular anti-viruses and malware detection software. With the increase of access to smart devices and appliances through secured and unsecured networks, there is a requirement to design an intelligent detection tool using deep learning techniques to handle complex vulnerabilities efficiently. The system should have the capability to prevent and control attacks from unreliable sources. The system administrator should immediately notify the system administrator—the proposed research studies about the DDoSBot net attacks in IoT devices. BotNets are Zombie servers, which can attack an extensive network with its automation process by designing a combination of prevention and detection mechanisms in a virtual environment that can access the cloud environment. |
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ISSN: | 1938-5862 1938-6737 |
DOI: | 10.1149/10701.15181ecst |