Controlling spam with SpamAssassin
Linux Journal
A study of prefix hijacking and interception in the internet
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
My botnet is bigger than yours (maybe, better than yours): why size estimates remain challenging
HotBots'07 Proceedings of the first conference on First Workshop on Hot Topics in Understanding Botnets
A case study of the rustock rootkit and spam bot
HotBots'07 Proceedings of the first conference on First Workshop on Hot Topics in Understanding Botnets
Peeking into spammer behavior from a unique vantage point
LEET'08 Proceedings of the 1st Usenix Workshop on Large-Scale Exploits and Emergent Threats
Botnet spam campaigns can be long lasting: evidence, implications, and analysis
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
Detecting Spam at the Network Level
EUNICE '09 Proceedings of the 15th Open European Summer School and IFIP TC6.6 Workshop on The Internet of the Future
Filtering spam from bad neighborhoods
International Journal of Network Management
Cleaning your house first: shifting the paradigm on how to secure networks
AIMS'11 Proceedings of the 5th international conference on Autonomous infrastructure, management, and security: managing the dynamics of networks and services
Internet bad neighborhoods: the spam case
Proceedings of the 7th International Conference on Network and Services Management
| Hi-index | 0.00 |
Spam comprises approximately 90 to 95 percent of all email traffic on the Internet nowadays, and it is a problem far from being solved. The losses caused by spam are estimated to reach up to $87 billion yearly. When fighting spam, most of the proposals focus on the receiver-side and are usually resource-intensive in terms of processing requirements. In this paper we present an approach to address these shortcomings: we propose to i) filter outgoing e-mail on the sender side and (ii) use lightweight techniques to check whether a message is spam or not. Moreover, we have evaluated the accuracy of these techniques in detecting spam on the sender side with two different data sets, obtained at a Dutch hosting provider. The results obtained with this approach suggest we can significantly reduce the amount of spam on the Internet by performing simple checks at the sender-side.