Dr.Kathir.Viswalingam, G.Ayyappan
Spam is email sent in bulk wherever there's no direct agreement in situ between the recipient and also the sender to receive email solicitation. to forestall the delivery of this spam, an automatic tool named a spam filter is employed. during this paper, (OBP) “Optical Back Propagation” technique is employed as an automatic tool to spot whether or not a message is spam or not supported the content of the message. Spam-based dataset-a dataset from UCI “University of California, Irvine” machine learning repository, is employed as coaching and testing dataset to coach the network so tested it. The samples of this dataset ought to be first of all preprocessed (normalization or feature choice before normalization) to be appropriate to the network. The results OBP spam filtering is affordable in term of accuracy, precision, recall, false Positive, false negative, and speed of net.