Improving Spam Detection Based on Structural Similarity

Details Improving Spam Detection Based on Structural Similarity Improving Spam Detection Based on Structural Similarity

2005-04-05

arxiv.org/abs/cs/0504012v1

Computer Science

Cryptography and Security

Scientific paper

We propose a new detection algorithm that uses structural relationships between senders and recipients of email as the basis for the identification of spam messages. Users and receivers are represented as vectors in their reciprocal spaces. A measure of similarity between vectors is constructed and used to group users into clusters. Knowledge of their classification as past senders/receivers of spam or legitimate mail, comming from an auxiliary detection algorithm, is then used to label these clusters probabilistically. This knowledge comes from an auxiliary algorithm. The measure of similarity between the sender and receiver sets of a new message to the center vector of clusters is then used to asses the possibility of that message being legitimate or spam. We show that the proposed algorithm is able to correct part of the false positives (legitimate messages classified as spam) using a testbed of one week smtp log.

Affiliated with

Also associated with

No associations

Rating

Improving Spam Detection Based on Structural Similarity does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Improving Spam Detection Based on Structural Similarity, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Improving Spam Detection Based on Structural Similarity will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-575461