A Data-Reachability Model for Elucidating Privacy and Security Risks Related to the Use of Online Social Networks

Abstract

Abstract-Privacy and security within Online Social Networks (OSNs) has become a major concern over recent years. As individuals continue to actively use and engage with these mediums, one of the key questions that arises pertains to what unknown risks users face as a result of unchecked publishing and sharing of content and information in this space. There are numerous tools and methods under development that claim to facilitate the extraction of specific classes of personal data from online sources, either directly or through correlation across a range of inputs. In this paper we present a model which specifically aims to understand the potential risks faced should all of these tools and methods be accessible to a malicious entity. The model enables easy and direct capture of the data extraction methods through the encoding of a data-reachability matrix for which each row represents an inference or dataderivation step. Specifically, the model elucidates potential linkages between data typically exposed on social-media and networking sites, and other potentially sensitive data which may prove to be damaging in the hands of malicious parties, i.e., fraudsters, stalkers and other online and offline criminals. In essence, we view this work as a key method by which we might make cyber risk more tangible to users of OSNs.

Inferring social relationships from technology-level device connections

“…Assuming the individual were then to post the photograph online, they would be sharing potentially sensitive identity data and would be oblivious to it; we do note, however, that some sites (e.g., Facebook) strip metatadata to reduce file size. This highlights some of the many privacy risks associated with the use of these devices and the unchecked publishing of information; further details are available in several articles (e.g., [17,18]). …”

Cybercrime and You: How Criminals Attack and the Human Factors That They Seek to Exploit

“…Previous research has considered this issue of oversharing and modeled how social media data could be used to place individuals at great risk, both online and offline [15,50]. There are also greater impacts on security and privacy as this data is combined with that from IoT devices such as fitness trackers and smart watches [1].…”

Pathways to identity: using visualization to aid law enforcement in identification tasks

“…Society uses cyber-space for everything from very personal activities (such as engaging with friends, documenting our lives, expressing our creativity), to learning and developing opinions, to very practical concepts such as travel planning, commerce, and banking [19]. All online activities leave a trail of identity pieces scattered throughout cyber-space, whether through conscious disclosures (e.g., on social networks), subconscious disclosures (such as exploited in textual-content analysis), or through technology-level leakages (e.g., through cookies) [20]. Meta-data associated with online activities also exists, such as IP addresses, account names, etc., which can all be related to an individual's identity.…”