Potential mass surveillance and privacy violations in proximity-based social applications

Proximity-based social applications let users interact with people that are currently close to them, by revealing some information about their preferences and whereabouts. This information is acquired through passive geo-localisation and used to build a sense of serendipitous discovery of people, places and interests. Unfortunately, while this class of applications opens different interactions possibilities for people in urban settings, obtaining access to certain identity information could lead a possible privacy attacker to identify and follow a user in their movements in a specific period of time. The same information shared through the platform could also help an attacker to link the victim's online profiles to physical identities. We analyse a set of popular dating application that shares users relative distances within a certain radius and show how, by using the information shared on these platforms, it is possible to formalise a multilateration attack, able to identify the user actual position. The same attack can also be used to follow a user in all their movements within a certain period of time, therefore identifying their habits and Points of Interest across the city. Furthermore we introduce a social attack which uses common Facebook likes to profile a person and finally identify their real identity

Smart City Development with Urban Transfer Learning

Nowadays, the smart city development levels of different cities are still unbalanced. For a large number of cities which just started development, the governments will face a critical cold-start problem: 'how to develop a new smart city service with limited data?'. To address this problem, transfer learning can be leveraged to accelerate the smart city development, which we term the urban transfer learning paradigm. This article investigates the common process of urban transfer learning, aiming to provide city planners and relevant practitioners with guidelines on how to apply this novel learning paradigm. Our guidelines include common transfer strategies to take, general steps to follow, and case studies in public safety, transportation management, etc. We also summarize a few research opportunities and expect this article can attract more researchers to study urban transfer learning

Social media as a data gathering tool for international business qualitative research: opportunities and challenges

Lusophone African (LA) multinational enterprises (MNEs) are becoming a significant pan-African and global economic force regarding their international presence and influence. However, given the extreme poverty and lack of development in their home markets, many LA enterprises seeking to internationalize lack resources and legitimacy in international markets. Compared to higher income emerging markets, Lusophone enterprises in Africa face more significant challenges in their internationalization efforts. Concomitantly, conducting significant international business (IB) research in these markets to understand these MNEs internationalization strategies can be a very daunting task. The fast-growing rise of social media on the Internet, however, provides an opportunity for IB researchers to examine new phenomena in these markets in innovative ways. Unfortunately, for various reasons, qualitative researchers in IB have not fully embraced this opportunity. This article studies the use of social media in qualitative research in the field of IB. It offers an illustrative case based on qualitative research on internationalization modes of LAMNEs conducted by the authors in Angola and Mozambique using social media to identify and qualify the population sample, as well as interact with subjects and collect data. It discusses some of the challenges of using social media in those regions of Africa and suggests how scholars can design their studies to capitalize on social media and corresponding data as a tool for qualitative research. This article underscores the potential opportunities and challenges inherent in the use of social media in IB-oriented qualitative research, providing recommendations on how qualitative IB researchers can design their studies to capitalize on data generated by social media.https://doi.org/10.1080/15475778.2019.1634406https://doi.org/10.1080/15475778.2019.1634406https://doi.org/10.1080/15475778.2019.1634406https://doi.org/10.1080/15475778.2019.1634406Accepted manuscriptPublished versio

Young People and Digital Intimacies. What is the evidence and what does it mean? Where next?

The digital age makes new forms of connection possible, enabling ‘digital intimacies’ including the many practices of communicating, producing and sharing intimate content (‘sexting’; selfies; making, viewing and circulating sexual content; using hook-up apps; and searching online for advice about sex). Where young people engage in digital intimacies, policymakers have tended to respond with alarm and commissioned research premised on demonstrating negative outcomes. Young people’s take up of technologies is contrasted with previous generations and ideas of ‘healthy’, ‘natural’ and ‘normal’ sexual development which ignores and marginalises diversity of sexuality and sexual expression, and leads to campaigns that seek to supervise and regulate youth sexuality. This in turn results in legislation and censorship with consequences including blocking websites for sexual abuse support and sexual education. The government has suspended introduction of Age Verification for pornographic websites but is pressing ahead with its ‘Online Harms’ White Paper which plans for broader and more comprehensive regulatory frameworks in the interests of protecting children and young people in online spaces. The UK government has positioned itself as a world leader in developing new regulatory approaches to tackle online harms but the evidence base for those approaches is neither robust nor nuanced enough to respond to the increasing mediatisation of everyday life and sexual identity. This briefing advocates for a broader recognition of young people’s investments in digital intimacies, acknowledging what growing up and learning about sex in the digital age means for young people in order to inform future policy and practice. Policies that are informed by robust research and understandings that accommodate the nuanced practices of digital intimacy will provide the support that young people need and deserve as they navigate their media lives, develop awareness of ethical and unethical behaviour, and what is right for them

Privacy Intelligence: A Survey on Image Sharing on Online Social Networks

Image sharing on online social networks (OSNs) has become an indispensable part of daily social activities, but it has also led to an increased risk of privacy invasion. The recent image leaks from popular OSN services and the abuse of personal photos using advanced algorithms (e.g. DeepFake) have prompted the public to rethink individual privacy needs when sharing images on OSNs. However, OSN image sharing itself is relatively complicated, and systems currently in place to manage privacy in practice are labor-intensive yet fail to provide personalized, accurate and flexible privacy protection. As a result, an more intelligent environment for privacy-friendly OSN image sharing is in demand. To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing. Specifically, we present a high-level analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field. The framework is divided into three main stages: local management, online management and social experience. At each stage, we identify typical sharing-related user behaviors, the privacy issues generated by those behaviors, and review representative intelligent solutions. The resulting analysis describes an intelligent privacy-enhancing chain for closed-loop privacy management. We also discuss the challenges and future directions existing at each stage, as well as in publicly available datasets.Comment: 32 pages, 9 figures. Under revie