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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: September 2023
Volume 8 | Issue 9
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 8
Issue Published : 88
Article Submitted : 8769
Article Published : 4490
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| Paper Title: | Phishing detection system using random forest algorithm |
| Authors Name: | Dr.G. Ramesh , R.B.Lokitha , R.R.Monisha , N.S.Neha |
| Download E-Certificate: | Download |
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IJRTI_185813
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| Published Paper Id: | IJRTI2304086 |
| Published In: | Volume 8 Issue 4, April-2023 |
| DOI: | |
| Abstract: | The Internet has integrated easily into our daily lives, but it has also made it possible to carry out illicit activities like hacking in secret. Phishers attempt to trick their victims by employing social engineering techniques or building fake websites to take information such as account IDs, usernames, and passwords from people and businesses. Phishing is a form of electronic online identity theft in which the attackers deceive a user into divulging sensitive information by using a mix of social engineering and website spoofing techniques. Typically, this knowledge is employed to generate an unlawful financial gain. (e.g., by online banking transactions, purchase of goods using stolen credentials, etc.). A remarkable platform for communication between regular individuals is the Internet. People with criminal intent have discovered a method to steal people's personal information with the least chance of being caught and without meeting the target. It's known as scamming. The e-commerce sector is seriously threatened by phishing. Customers' trust in online shopping is undermined, and electronic service suppliers suffer significant financial losses as a result. For this reason, understanding malware is crucial. Although many strategies have been put forth to identify scam websites, phishers have developed ways to circumvent these strategies. Machine learning is one of the best techniques for spotting these malevolent behaviors. This is because most phishing attacks share some similar traits that can be. |
| Keywords: | Phishing, Classification, Optimization, Map Reduce. |
| Cite Article: | "Phishing detection system using random forest algorithm", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 4, page no.510 - 514, April-2023, Available :http://www.ijrti.org/papers/IJRTI2304086.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2304086
Registration ID:185813
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 510 - 514 Country: Madurai, Tamilnadu, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2304086 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2304086 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016
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