What do information centric networks, trusted execution environments, and digital watermarking have to do with privacy, the data economy, and their future?

Abstract

What if instead of having to implement controversial user tracking techniques, Internet advertising & marketing companies asked explicitly to be granted access to user data by name and category, such as Alice→Mobility→05-11-2020? The technology for implementing this already exists, and is none other than the Information Centric Networks (ICN), developed for over a decade in the framework of Next Generation Internet (NGI) initiatives. Beyond named access to personal data, ICN's in-network storage capability can be used as a substrate for retrieving aggregated, anonymized data, or even for executing complex analytics within the network, with no personal data leaking outside. In this opinion article we discuss how ICNs combined with trusted execution environments and digital watermarking, can be combined to build a personal data overlay inter-network in which users will be able to control who gets access to their personal data, know where each copy of said data is, negotiate payments in exchange for data, and even claim ownership, and establish accountability for data leakages due to malfunctions or malice. Of course, coming up with concrete designs about how to achieve all the above will require a huge effort from a dedicated community willing to change how personal data are handled on the Internet. Our hope is that this opinion article can plant some initial seeds towards this direction.

A Neural Network-based Approach for Assessing the Energy Value of Regional Water Environment Pollution Losses and Its Application

“…Currently, the main indicator system assessment methods are the vector function method, the fuzzy global assessment method and the hierarchical analysis method. These methods are relatively easy to choose for quantitative assessment and analysis, and are used to quantify and understand the degree of good and bad impacts on the aquatic environment, but the choice of assessment indicators is easily influenced by the subjectivity of the selector, making the assessment results inaccurate and unreliable [9][10].…”

Regulatory Data Privacy Concerns in Proliferating IoT Era of Telecommunication Data Monetization: A Systematic Literature Review

“…Data brokerage businesses have emerged, facilitating the exchange of personal data for a price [43], [48], but "pay-for-privacy" models further erode data owners' privacy rights [9], [45]. To protect these rights, strictly regulated data monetization practices must be enforced, allowing data owners to negotiate compensation and limit the use of their data in all scenarios involving the data economy [65].…”

“…This should cover all stages, including data acquisition, data analysis, and data monetization, as well as governance over the role changes of stakeholders along the value chain. The regulations must prioritise and uphold the data owners' inalienable right to control the access, dissemination, handling, and use of their data at all times [44], [65].…”

Multi Factor Risk Assessment Algorithm in Digital Economy Platform

“…However, with the rapid development of internet platforms, their market structure has gradually evolved into a competitive effect: the winner takes all, and the stronger would become stronger. The frequency of platform monopoly phenomenon affects the sustainable and healthy development of the digital economy [20]. The existence of monopoly on digital economy platforms not only damages the health and sustainable environment of digital economy platform development, but also damages the welfare and efficiency of multi-party production.…”