Incidental data: observation of privacy compromising data on social media platforms

Abstract

Social media plays an important role for a vast majority in one’s internet life. Likewise, sharing, publishing, and posting content through social media has nearly become effortless. This unleashes new threats as unintentionally shared information may be used against oneself or loved ones. With open-source intelligence data and methods, we show how unindented published data can be revealed and further analyze possibilities that can potentially compromise one’s privacy. This is backed up by a popular view of interviewed experts from various fields of expertise. We were able to show that only 2 hours of manually fetching data are sufficient to unveil private, personal information that was not intended to be published by the person. Two distinctive methods are described with several approaches. From our results, we were able to describe a 14-step awareness guideline and proposed a change of the law within Austrian legislation. Our work has shown that awareness among persons on social media needs to be raised. Critical reflections on our work has revealed several ethical implications that have made countermeasures necessary; however, it can be assumed that criminals do not to these.