TY  - JOUR
A1  - Tatli, Emin Islam
A1  - Lucks, Stefan
T1  - Mobile Identity Management Revisited
JF  - Electronic Notes in Theoretical Computer Science
N2  - 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
KW  - Privatsphäre
KW  - Anwendung
KW  - P3P
KW  - privacy, mobile identity management, location-based applications, p3p
Y1  - 2009
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20170426-31640
SP  - 125
EP  - 137
ER  - 
TY  - JOUR
A1  - Frommholz, Ingo
A1  - Haider M., al-Khateeb
A1  - Potthast, Martin
A1  - Ghasem, Zinnar
A1  - Shukla, Mitul
A1  - Short, Emma
T1  - On Textual Analysis and Machine Learning for Cyberstalking Detection
JF  - Datenbank Spektrum
N2  - 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.
KW  - Text Mining
KW  - Maschinelles Lernen
Y1  - 2016
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20170418-31352
SP  - 127
EP  - 135
ER  -