LENS: LEveraging anti-social Networking for preventing Spam: Difference between revisions
| (One intermediate revision by the same user not shown) | |||
| Line 8: | Line 8: | ||
== Description == | == Description == | ||
In recent years several techniques | In recent years several techniques have been presented using social networks to fight spam. Unfortunately their services are only limited within the social network of an email user. At Computer Netwoks groups, in collaboration with Deutsche Telekom labs, we are actively working on LENS, a new spam protection system, which leverages anti-social networking paradigm based on an underlying trust infrastructure to both ''extend spam protection beyond a user’s social circle'' and ''fundamentally prevent the transmission of spam across the network at the first place''. The goal of this thesis is to design and implement a prototype of LENS on mail transfer agent (MTA) as an email routing facility, and evaluate the system performances (e.g. delays, and overhead) on large scale tesbeds like PlanetLab. | ||
== Resources == | |||
* [http://user.informatik.uni-goettingen.de/~shameed/LENS.pdf Thesis Description] | |||
Latest revision as of 15:55, 22 February 2010
Details
| Supervisor: | Sufian Hameed |
| Duration: | 6 months |
| Type: | Master Thesis or Student Project |
| Status: | open |
Description
In recent years several techniques have been presented using social networks to fight spam. Unfortunately their services are only limited within the social network of an email user. At Computer Netwoks groups, in collaboration with Deutsche Telekom labs, we are actively working on LENS, a new spam protection system, which leverages anti-social networking paradigm based on an underlying trust infrastructure to both extend spam protection beyond a user’s social circle and fundamentally prevent the transmission of spam across the network at the first place. The goal of this thesis is to design and implement a prototype of LENS on mail transfer agent (MTA) as an email routing facility, and evaluate the system performances (e.g. delays, and overhead) on large scale tesbeds like PlanetLab.