The familiar stranger: anxiety, comfort, and play in public places
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
User-controllable learning of security and privacy policies
Proceedings of the 1st ACM workshop on Workshop on AISec
Cognitive security for personal devices
Proceedings of the 1st ACM workshop on Workshop on AISec
Enabling Technologies for Mobile Services: The MobiLife Book
Enabling Technologies for Mobile Services: The MobiLife Book
Security automation considered harmful?
NSPW '07 Proceedings of the 2007 Workshop on New Security Paradigms
Inferring privacy policies for social networking services
Proceedings of the 2nd ACM workshop on Security and artificial intelligence
Implicit authentication for mobile devices
HotSec'09 Proceedings of the 4th USENIX conference on Hot topics in security
ICDCIT'12 Proceedings of the 8th international conference on Distributed Computing and Internet Technology
Adaptive information-sharing for privacy-aware mobile social networks
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
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With the increasing popularity of personal mobile devices like smartphones, more and more ordinary users create and consume valuable, private and sensitive data such as photos, videos, messages, documents as well as access credentials for various resources and services. Without proper access control policies, such data may be disclosed in ways that the user did not intend. Although various applications and services support the possibility of fine-grained security and privacy policies, end users are not capable of understanding or adjusting the policies to suit their needs. In this position paper we argue that context information can be used to infer likely access control policies. We motivate by briefly describing three usage scenarios where context related to the location of a device can be used to set access control policies. We argue that a simple measure like the "familiarity" of a device and/or context can be calculated and used to infer appropriate policy settings. Finally, we report on our experience in using context observations collected from the devices of two test participants over a period of time.