Internet Surveillance after Snowden: A Critical Empirical Study of Computer Experts' Attitudes on Commercial and State Surveillance of the Internet and Social Media post-Edward Snowden

Acknowledgement: The research presented in this paper was conducted as part of the EU FP7 research project PACT (http://www.projectpact.eu), grant agreement number 285635.

Image usefulness of compressed surveillance footage with different scene contents

The police use both subjective (i.e. police staff) and automated (e.g. face recognition systems) methods for the completion of visual tasks (e.g person identification). Image quality for police tasks has been defined as the image usefulness, or image suitability of the visual material to satisfy a visual task. It is not necessarily affected by any artefact that may affect the visual image quality (i.e. decrease fidelity), as long as these artefacts do not affect the relevant useful information for the task. The capture of useful information will be affected by the unconstrained conditions commonly encountered by CCTV systems such as variations in illumination and high compression levels. The main aim of this thesis is to investigate aspects of image quality and video compression that may affect the completion of police visual tasks/applications with respect to CCTV imagery. This is accomplished by investigating 3 specific police areas/tasks utilising: 1) the human visual system (HVS) for a face recognition task, 2) automated face recognition systems, and 3) automated human detection systems. These systems (HVS and automated) were assessed with defined scene content properties, and video compression, i.e. H.264/MPEG-4 AVC. The performance of imaging systems/processes (e.g. subjective investigations, performance of compression algorithms) are affected by scene content properties. No other investigation has been identified that takes into consideration scene content properties to the same extend. Results have shown that the HVS is more sensitive to compression effects in comparison to the automated systems. In automated face recognition systems, `mixed lightness' scenes were the most affected and `low lightness' scenes were the least affected by compression. In contrast the HVS for the face recognition task, `low lightness' scenes were the most affected and `medium lightness' scenes the least affected. For the automated human detection systems, `close distance' and `run approach' are some of the most commonly affected scenes. Findings have the potential to broaden the methods used for testing imaging systems for security applications.

Information ethics in the age of digital labour and the surveillance-industrial complex

Thee rise of computing and the internet have brought about an ethical eld of studies that some term information ethics, computer ethics, digital media ethics, or internet ethics e aim of this contribution is to discuss information ethics’ foundations in the context of the internet’s political economy e chapter rst looks to ground the analysis in a comparison of two information ethics approaches, namely those outlined by Rafael Capurro and Luciano Floridi It then develops, based on these foundations, analyses of the information ethical dimensions of two important areas of social media: one concerns the framing of social media by a surveillance-industrial complex in the context of Edward Snowden’s revelations and the other deals with issues of digital labour processes and issues of class that arises in this context e contribution asks ethical questions about these two phenomena that bring up issues of power, exploitation, and control in the information age It asks if, and if so, how, the approaches of Capurro and Floridi can help us to understand ethico-political aspects of the surveillance-industrial complex and digital labour