@inproceedings{BenderFabianLessmannetal.2016,
  author    = {Bender, Benedict and Fabian, Benjamin and Lessmann, Stefan and Haupt, Johannes},
  title     = {E-Mail Tracking},
  series = {Proceedings of the 37th International Conference on Information Systems (ICIS)},
  booktitle = {Proceedings of the 37th International Conference on Information Systems (ICIS)},
  pages     = {19},
  year      = {2016},
  abstract  = {E-mail advertisement, as one instrument in the marketing mix, allows companies to collect fine-grained behavioural data about individual users' e-mail reading habits realised through sophisticated tracking mechanisms. Such tracking can be harmful for user privacy and security. This problem is especially severe since e-mail tracking techniques gather data without user consent. Striving to increase privacy and security in e-mail communication, the paper makes three contributions. First, a large database of newsletter e-mails is developed. This data facilitates investigating the prevalence of e- mail tracking among 300 global enterprises from Germany, the United Kingdom and the United States. Second, countermeasures are developed for automatically identifying and blocking e-mail tracking mechanisms without impeding the user experience. The approach consists of identifying important tracking descriptors and creating a neural network-based detection model. Last, the effectiveness of the proposed approach is established by means of empirical experimentation. The results suggest a classification accuracy of 99.99\%.},
  language  = {en}
}