@article{TatliLucks,
  author    = {Tatli, Emin Islam and Lucks, Stefan},
  title     = {Mobile Identity Management Revisited},
  series = {Electronic Notes in Theoretical Computer Science},
  journal   = {Electronic Notes in Theoretical Computer Science},
  doi       = {10.1016/j.entcs.2009.07.044},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170426-31640},
  pages     = {125 -- 137},
  abstract  = {Identity management provides PET (privacy enhancing technology) tools for users to control privacy of their personal data. With the support of mobile location determination techniques based on GPS, WLAN, Bluetooth, etc., context-aware and location-aware mobile applications (e.g. restaurant finder, friend finder, indoor and outdoor navigation, etc.) have gained quite big interest in the business and IT world. Considering sensitive static personal information (e.g. name, address, phone number, etc.) and also dynamic personal information (e.g. current location, velocity in car, current status, etc.), mobile identity management is required to help mobile users to safeguard their personal data. In this paper, we evaluate certain required aspects and features (e.g. context-to-context dependence and relation, blurring in levels, trust management with p3p integration, extended privacy preferences, etc.) of mobile identity management},
  subject      = {Privatsph{\"a}re},
  language  = {en}
}
@article{FrommholzHaiderMPotthastetal.,
  author    = {Frommholz, Ingo and Haider M., al-Khateeb and Potthast, Martin and Ghasem, Zinnar and Shukla, Mitul and Short, Emma},
  title     = {On Textual Analysis and Machine Learning for Cyberstalking Detection},
  series = {Datenbank Spektrum},
  journal   = {Datenbank Spektrum},
  doi       = {10.1007/s13222-016-0221-x},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170418-31352},
  pages     = {127 -- 135},
  abstract  = {Cyber security has become a major concern for users and businesses alike. Cyberstalking and harassment have been identified as a growing anti-social problem. Besides detecting cyberstalking and harassment, there is the need to gather digital evidence, often by the victim. To this end, we provide an overview of and discuss relevant technological means, in particular coming from text analytics as well as machine learning, that are capable to address the above challenges. We present a framework for the detection of text-based cyberstalking and the role and challenges of some core techniques such as author identification, text classification and personalisation. We then discuss PAN, a network and evaluation initiative that focusses on digital text forensics, in particular author identification.},
  subject      = {Text Mining},
  language  = {en}
}