Data Confidentiality and Information Credibility in On-line Ecosystems

Abstract

Recent ICTs paradigms such as cloud computing, data outsourcing, digital data markets, and the spread of multiple social media based on Web 2.0 technologies, facilitate the exchange of large data and information flows among a myriad of interconnected devices and users, for different aims and purposes. This complex scenario underlies the development of online ecosystems of interacting entities, where the concepts of community, self-organization, evolution and knowledge are fundamental.While the benefits connected to such kind of ecosystems are intuitive also to the everyday man, no lunch comes for free, and such a complex and interconnected scenario entails a number of issues connected to both data and information generation and diffusion that should be carefully addressed. For example, in the data sharing context, genuine data could be manipulated, tampered with, accessed without permission, breached, or improperly disclosed; in the Social Web context, low-quality data and/or misinformation could be diffused. With respect to the above-mentioned issues, in this paper we survey some of the possible approaches proposed in the literature for ensuring adequate data protection, with particular reference to data confidentiality, and for assessing information credibility in complex online environments. We also provide a conclusive discussion aimed at illustrating the importance of relating these concepts. CCS CONCEPTS• Information systems → World Wide Web; • Security and privacy → Pseudonymity, anonymity and untraceability; Social aspects of security and privacy; Database and storage security.

Information Credibility in the Social Web: Contexts, Approaches, and Open Issues

“…Another problem that should be addressed in the near future is how to consider, in the credibility assessment process, the amount of confidential information that is released within UGC, an aspect that has not been sufficiently investigated in the literature until now [6,27]. On the one hand, it is necessary to develop solutions to protect this type of information, on the other hand, how to use it (once properly sanitized) to have additional evidence about the reliability of the source of information and therefore of the credibility of her/his content.…”

E-Cabin: A Software Architecture for Passenger Comfort and Cruise Ship Management

“…Nevertheless, aggregated data can be used by cruise ship staff to provide a better service. The issue of adequate protection in data confidentiality is not a trivial task; as highlighted in [24], there exist two families of techniques aimed at providing datasets confidentiality: syntactic privacy definitions (i.e., techniques aimed at breaking the correspondences between a person and his/her sensitive information) and semantic privacy definitions (i.e., techniques aimed at hiding or slightly modifying informative content). E-Cabin relies on the exclusions of identifying information (names, tax identification numbers, addresses, phone numbers) and generalizes quasi-identifiers (i.e., pieces of information that could be used to univocally recognize a person, such as specific health conditions, full dates of birth, etc.)…”

Detecting Binge Drinking and Alcohol-Related Risky Behaviours from Twitter’s Users: An Exploratory Content- and Topology-Based Analysis

“…Specifically, people share online information and access contents that other subjects have posted on the Web, including their own experiences, which defines a new IT user paradigm [20,21]. This scenario, completely different from an end-user condition, enables the access to social media, where large amounts of User-Generated Content (UGC) are spread every day across virtual communities, almost without any external control [22][23][24], lowering at the same time the perception of anonymity and confidentiality issues among users [25,26]. This applies particularly to those topics that people are reluctant to discuss with healthcare professionals, including behaviours, opinions, and individual-directed actions that are difficult to track and measure in a clinical setting [27].…”