5. TECHNOLOGIES & MATERIALS
» Detection technologies
» Sensor equipment and technologies
6. INFORMATION & COMMUNICATION TECHNOLOGIES
» Intelligence systems
» Artificial intelligence/robotics
» Cyber security
Early-Warning System for Botnets
This project was initiated by Dr. Alexander K. Seewald and was conducted at the Research Lab Computational Technologies and Applications of the faculty for computer science of the University of Vienna under the leadership of Dr. Wilfried Gansterer.
Previous research initiatives are focussed on the recognition and defense against unwanted or potentially harmful E-Mail messages (for simplification purposes named as Spam). Within this project we will focus on an important complementary area - the proactive identification and early recognition of the souce of spam.
Most of todays spam is sent from big networks of captured computers of innocent users, which were infected with malware by spammers (so called bot nets). The aim is an early-warning system for botnets to secure the Austrian internet.
Automated Score Tuning for SpamAssassin
During the creation of an institute-wide spamfilter system based on SpamAssassin we have collected a set of 77,286 ham and spam mails from eight users, developed our own training methods and evaluated them against commercial and free spam filtering systems, including Symantec BrightMail. A more recent report puts the work in larger context, adds new empirical results and proposes a convenient approach for mail data collection.