Academic Marginalia

Prompted by Facebook Research's recent announcement on using deep learning to help users avoid 'drunk posting' embarrassing information on the social networking platform, I wrote an article for The Conversation about deep learning and adaptive sharing.  This draws on our research on Adaptive Sharing for Online Social Networks , which was recognised as the Best Paper at the  13th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom-14).  The following is a short excerpt from the article: Facebook’s initial target appears aimed at extending its face recognition capability to automatically differentiate between a user’s face when sober and drunk, and use this to get a user to think twice before hitting the post button. Of course being detected as being drunk in photographs won’t be the only factor that determines when we want to moderate our social media sharing behaviours. The nature of the links we share, li...

Screenshot of article on The Conversation site The latest revelations from the Snowden files includes evidence that NSA and GCHQ were tapping into some of the application analytics data being gathered by popular mobile applications like Angry Birds.  I was invited by The Conversation platform to contribute to a short article titled, " Angry Birds will have angry users until privacy rules are clear " that discusses this issue and where the responsibility for privacy and security in mobile applications lies.