As surveillance-oriented security technologies (SOSTs) are considered security enhancing but also privacy infringing, citizens are expected to trade part of their privacy for higher security. Drawing from the PRISE project, this study casts some light on how citizens actually assess SOSTs through a combined analysis of focus groups and survey data. First, the outcomes suggest that people did not assess SOSTs in abstract terms but in relation to the specific institutional and social context of implementation. Second, from this embedded viewpoint, citizens either expressed concern about government's surveillance intentions and considered SOSTs mainly as privacy infringing, or trusted political institutions and believed that SOSTs effectively enhanced their security. None of them, however, seemed to trade privacy for security because concerned citizens saw their privacy being infringed without having their security enhanced, whilst trusting citizens saw their security being increased without their privacy being affected.

Among the numerous implications of digitalization, the debate about 'big data' has gained momentum. The central idea capturing attention is that digital data represents the newest key asset organizations should use to gain a competitive edge. Data can be sold, matched with other data, mined, and used to make inferences about anything, from people's behavior to weather conditions. Particularly, what is known as 'big data analytics'-i.e. the modeling and analysis of big data-has become the capability which differentiates, from the rest of the market, the most successful companies. An entire business ecosystem has emerged around the digital data asset, and new types of companies, such as analytical competitors and analytical deputies, are proliferating as a result of the analysis of digital data. However, virtually absent from the big data debate is any mention of one of its constitutive mechanisms-that is, dataveillance. Dataveillance-which refers to the systematic monitoring of people or groups, by means of personal data systems in order to regulate or govern their behavior-sets the stage and reinforces the development of the data economy celebrated in the big data debate. This article aims to make visible the interdependence between dataveillance, big data and analytics by providing real examples of how companies collect, process, analyze and use data to achieve their business objectives.

This article examines the relationship between the institutional trustworthiness of security agencies in the context of data‐intensive security practices. It focuses on the public's acceptance of the way digital surveillance technologies feed into large‐scale security data analytics. Using the case of deep packet inspection (DPI), survey data gathered in six European countries (n = 1,202) demonstrates that security agencies' institutional trustworthiness directly and indirectly influences public acceptance of DPI. Against a backdrop of declining public trust in government and a climate of intense international terrorist threat, governments around the world are appealing to citizens to trade privacy for enhanced security. This article supports calls for security agencies and their respective governments to engage with the democratic process to enrich security and privacy at all levels of public security governance and for the common good.

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