Name
Abstract | ||
|---|---|---|
Spam is a serious universal problem which causes problems for almost all computer users. This issue affects not only normal users of the internet, but also causes a big problem for companies and organizations since it costs a huge amount of money in lost productivity, wasting users' time and network bandwidth. Many studies on spam indicate that spam cost organizations billions of dollars yearly. This work presents a machine learning method inspired by the human immune system called Artificial Immune System (AIS) which is a new emerging method that still needs further exploration. Core modifications were applied on the standard AIS with the aid of the Genetic Algorithm. Also an Artificial Neural Network for spam detection is applied with a new manner. SpamAssassin corpus is used in all our simulations. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/s10462-011-9285-z | Artif. Intell. Rev. |
Keywords | Field | DocType |
Spam,Artificial immune system,Genetic algorithm | Data mining,Artificial immune system,Computer science,Bandwidth (signal processing),Artificial intelligence,Artificial neural network,Machine learning,Genetic algorithm,The Internet | Journal |
Volume | Issue | ISSN |
40 | 3 | 0269-2821 |
Citations | PageRank | References |
8 | 0.43 | 48 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Raed Abu Zitar | 1 | 87 | 10.95 |
| Adel Hamdan | 2 | 19 | 1.32 |