This paper presents an innovative fusion based multi-classifier email classification on a ubiquitous multi-core architecture. Many approaches use text-based single classifiers or multiple weakly trained classifiers to identify spam messages from a large email corpus. We build upon our previous work on multi-core by apply our ubiquitous multi-core framework to run our fusion based multi-classifier architecture. By running each classifier process in parallel within their dedicated core, we greatly improve the performance of our proposed multi-classifier based filtering system. Our proposed architecture also provides a safeguard of user mailbox from different malicious attacks. Our experimental results show that we achieved an average of 30% speedup at the average cost of 1.4 ms. We also reduced the instance of false positive, which is one of the key challenges in spam filtering system, and increases email classification accuracy substantially compared with single classification techniques.
|Title of host publication||IFIP International Conference on Network and Parallel Computing, 2008. NPC 2008.|
|Place of Publication||USA|
|Number of pages||8|
|Publication status||Published - 2008|
|Event||IFIP International Conference on Network and Parallel Computing, 2008. NPC 2008. - Shanghai, China, China|
Duration: 18 Oct 2008 → 21 Oct 2008
|Conference||IFIP International Conference on Network and Parallel Computing, 2008. NPC 2008.|
|Period||18/10/08 → 21/10/08|
Islam, MD. R. (2008). Multi-classifier classification of spam email on a ubiquitous multi-core architecture. In IFIP International Conference on Network and Parallel Computing, 2008. NPC 2008. (pp. 210-217). IEEE.