Botnet Detection System: Using Machine Learning & Deep Learning to Reduce Threats in Real Time

Botnet Detection System: Using Machine Learning & Deep Learning to Reduce Threats in Real Time
Author(s):
Aditya Bhandarkar, Kanishka Sharma, Ritik Yadav, Rovina Dbritto, Dr. Yogita Mane
Keywords:
Decentralized application, Ethereum, Non-Fungible Task, Inter Planetary File system
Abstract
Widespread remote services in the distributed computing environment have been more accessible thanks to the Internet in recent years; however, a number of security concerns are impeding the integrity of data transmission in the distributed computing platform. One major concern to Internet security is the botnet phenomenon, which also poses a risk from harmful software. A vast array of illicit operations, such as distributed denial of service (DDoS) assaults, click fraud, phishing, virus distribution, spam emails, and the construction of devices for the illicit exchange of materials or information, are made possible by the botnet phenomena. As a result, creating a strong system is essential to enhancing the process of identifying, analyzing, and eliminating botnets.
Article Details
Unique Paper ID: 163777 Publication Volume & Issue: Volume 10, Issue 11 Page(s): 2533 - 2537
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