Malicious URL Detector for low power consumption using Blacklist

Authors

  • Nandhini S Assistant Professor ,SRM Institute of Science and Technology, Ramapuram Author
  • Nanda Kishore Assistant Professor ,SRM Institute of Science and Technology, Ramapuram Author
  • Josephus Andrew Assistant Professor ,SRM Institute of Science and Technology, Ramapuram Author
  • Shubham Godara Assistant Professor ,SRM Institute of Science and Technology, Ramapuram Author

DOI:

https://doi.org/10.61841/00q1yg93

Keywords:

URL, convoluted, Trojans, blacklist

Abstract

There have been many attacks on websites, and information has been hacked using viruses and Trojans through the URL or Universal Resource Locator of the website. This problem can be controlled by using a program called a URL detector that uses a blacklist, which basically denies access to the website when malicious activity is detected. A convoluted neural network is used to deny access to the URL if it does not match with the existing URLs in the blacklist. This method of scanning for malicious URLs is efficient and power-saving in most aspects. 

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References

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Published

31.05.2020

How to Cite

S, N., Kishore, N., Andrew, J., & Godara, S. (2020). Malicious URL Detector for low power consumption using Blacklist. International Journal of Psychosocial Rehabilitation, 24(3), 4240-4245. https://doi.org/10.61841/00q1yg93