Existing Spam Filtering Methods Considering different technique: A review

Today, social media and email are become a very common and the most effective medium for communication and data transferring which has been greatly affected by undesired spam by sharing unwanted and malicious contents to Internet users which, brings financial losses to organizations as well as become a headache for individual users and leads to decrease in productivity considerably. The spam occupies storage and the communication bandwidth as well as a network threat, when it contains viruses and malicious codes. On an average a user on internet may get 10-20 spam emails per day. For solving spam problems, different counter measures need to deploy to detect and remove these unwanted messages. This paper summarizes the survey of different existing email spam filtering techniques such as how machine and non-machine learning approaches are used to detect incoming unsolicited emails. Each filtering method has their own benefits and demerits. Considering upon the requirements different kind of spam filters, however, here in this research paper, we present the classification, and comparison of various spam email filtering techniques and focusing on the accuracy rate of various existing techniques.