Spam Identification in cloud computing based on text filtering systems
Offor, Chibuikem Divine (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025052817551
https://urn.fi/URN:NBN:fi:amk-2025052817551
Tiivistelmä
This research displays the analysis, development, and training of a software tool designed to block or filter spam messages, preventing them from invading people privacy or stealing sensitive data. This tool is designed to help and protect firms and individual alike by flagging messages with the features and characteristics of spam.
For this to be achieved the use of ML and NLP methods were used, and it was very helpful. Previously other traditional methods were used but due to the advancement of technology attackers found new methods to use. By using tools like ML and NLP, it was able to achieve the goal of this research (Filtering spams and spam identification).
While developing the software, scalability, cost, and reliable cloud platform were all considered. The main objective of this thesis, which is developing a system that have the capacity to identify spams and filter them were achieved.
For this to be achieved the use of ML and NLP methods were used, and it was very helpful. Previously other traditional methods were used but due to the advancement of technology attackers found new methods to use. By using tools like ML and NLP, it was able to achieve the goal of this research (Filtering spams and spam identification).
While developing the software, scalability, cost, and reliable cloud platform were all considered. The main objective of this thesis, which is developing a system that have the capacity to identify spams and filter them were achieved.