Nudging the government: How open data can be used to make behavioural governance work both ways

Data-driven regulation has become a new type of governance. Identifying number plates and human faces using computer vision, and tracking the position of consumer devices deploying sensors in the public space, are facilitating new master plans for the smart country and its smart cities, where government services are provided only to those who need them (Hodgkinson 2011). Politics are struggling to keep pace and include available data and newly identified threats in the development of new policies. Behavioural governance is helping to utilise data collection in order to influence consumers and citizens without the need to enact strict penalties for unwanted behaviour and without the requirement to enforce regulations with huge bureaucratic overheads. The computer industry’s default answer to the how of politics is what could be called 'solutionism': problems are to be dealt with via apps, sensors and feedback loops - all provided by start-ups (Morozov 2014). Google's Eric Schmidt was even more optimistic in 2014: IT start-ups would provide the solution to economic inequality

Part 2: Consumer Data: Introduction

The obvious issue of consumer data in the context of consumer policy is the mass of data that consumers voluntarily or involuntarily produce and diffuse. Thereby, consumers run the risk that their data is not only being used to their benefit, but also being abused. This is particularly the case with personal and sensitive data that can clearly lead to serious harm for consumers, if this data falls into the wrong hands. Typically, in an open market economy there are commercial interests, seeking new, technical ways to access consumer data for the sake of profit maximisation. The contributions to this part show that this is an important field to be addressed by consumer policy

Smart Grid: Chancen und Risiken für Verbraucher

Im November 2015 wurde ein Gesetzesentwurf zur Digitalisierung der Energiewende beschlossen. Erneut ist damit eine Debatte um den Rollout von Smart Metern (digitalen Stromzählern) aufgeflammt. Bisher nutzen private Haushalte elektromechanische Stromzähler, die händisch abgelesen werden und keine flexible Tarifierung erlauben. Die künftigen Zähler sollen den Weg für die Digitalisierung des gesamten Stromnetzes ebnen. Das dabei entstehende Smart Grid kann bei einem regionalen Überangebot an elektrischer Energie durch Nutzung von steuerbaren Geräten einen Ausgleich vornehmen. Stromkunden bezahlen dann über variable Tarife weniger für die verbrauchte Kilowattstunde: Geräte schalten sich flexibel dazu und stabilisieren die Nachfrage. Die zu erhebenden Daten sind sehr sensibel und können Rückschlüsse auf Lebensgewohnheiten oder identifizierbare Aktivitäten zulassen. Der Gesetzesentwurf berücksichtigt zwar Hinweise, die aus Fachdiskussionen und wissenschaftlichen Untersuchungen stammen und die Schwachstellen bei vorhandenen Smart Meter-Infrastrukturen aufzeigen; es bleibt jedoch zweifelhaft, ob die zwangsweise Digitalisierung der Stromverbrauchsmessung Verbrauchern Vorteile bringt, die den Risiken und Kosten angemessen gegenüber stehen

Privacy-enhancing Aggregation of Internet of Things Data via Sensors Grouping

Big data collection practices using Internet of Things (IoT) pervasive technologies are often privacy-intrusive and result in surveillance, profiling, and discriminatory actions over citizens that in turn undermine the participation of citizens to the development of sustainable smart cities. Nevertheless, real-time data analytics and aggregate information from IoT devices open up tremendous opportunities for managing smart city infrastructures. The privacy-enhancing aggregation of distributed sensor data, such as residential energy consumption or traffic information, is the research focus of this paper. Citizens have the option to choose their privacy level by reducing the quality of the shared data at a cost of a lower accuracy in data analytics services. A baseline scenario is considered in which IoT sensor data are shared directly with an untrustworthy central aggregator. A grouping mechanism is introduced that improves privacy by sharing data aggregated first at a group level compared as opposed to sharing data directly to the central aggregator. Group-level aggregation obfuscates sensor data of individuals, in a similar fashion as differential privacy and homomorphic encryption schemes, thus inference of privacy-sensitive information from single sensors becomes computationally harder compared to the baseline scenario. The proposed system is evaluated using real-world data from two smart city pilot projects. Privacy under grouping increases, while preserving the accuracy of the baseline scenario. Intra-group influences of privacy by one group member on the other ones are measured and fairness on privacy is found to be maximized between group members with similar privacy choices. Several grouping strategies are compared. Grouping by proximity of privacy choices provides the highest privacy gains. The implications of the strategy on the design of incentives mechanisms are discussed

Enforcing Regional DRM for Multimedia Broadcasts with and without Trusted Computing

We present the problem of enforcing a Digital Rights Management (DRM) system that needs to consider location-dependent licensing policies and operates on top of existing conditional access standards. A major application for location-dependent DRM is Pay-TV broadcasting as rightsholders require different business models in different regions. A global provider\u92s enduser equipment needs to validate the user location in some way in order to enforce DRM in this scenario. We will depict several solutions to the problem and compare their security qualities. The main result is that trusted computing hardware may not be the most appropriate solution given reasonable conditions

How Pay-TV becomes E-Commerce

In this paper we highlight the fact that existing Pay-TV schemes operating on countries or world regions could be transformed into a global system as the digital television broadcasting technology offers the possibility to put different regional content (e.g., audio and subtitle information) into one transmission so that each user could decode the content according to his personal needs. As the Internet could be used for selling Pay-Per-View licenses and the digital multimedia content can be played by personal computers the existing Pay-TV systems could become a global electronic commerce solution reducing the transmission cost per content significantly

Applications of broadcast encryption schemes and related technical mechanisms for digital rights management of multimedia broadcasts

Viele Anwendungen benötigen Lösungen für das Problem, Daten an Empfänger in einer Weise zu übertragen, dass nur die spezifizierte Teilmenge diese entschlüsseln können: Pay-TV, rechteverwaltete Medien und Multicast-Kommunikation sind aktuelle Beispiele. Darüber hinaus existieren nicht vernetzte Anwendungen, insbesondere im Hinblick auf Speichermedien. Eine kryptographische Lösung stellt Broadcast Encryption (Fiat und Naor 1993) dar. Wir konzentrieren uns auf die Fragestellung, wie Inhalte unter Durchsetzung digitaler Rechte über einen globalen Dienst übertragen werden können. Eine neue Variante des Broadcast Encryption wird vorgestellt, die auf die Bereitstellung kryptographischer Mechanismen für die Realisierung eines Multimedia-DRM abzielt. Die vorgeschlagenen Verfahren stellen einen gegenseitigen Ausgleich zwischen Parametern wie Schlüssellänge und Headerlänge auf der einen Seite und der Anzahl der geduldeten unberechtigten Empfänger einer Übertragung auf der anderen Seite bereit

Satellite communication without privacy – attacker’s paradise

Abstract: In this paper we highlight the fact that a huge amount of information is sent unsecured via satellite broadcast data channels (here: encapsulated in DVB-s). By applying straightforward data analysis it is possible for any attacker equipped with a digital satellite dish and a DVB card PC to derive extensive confidential information on single users (e.g., legal name, banking details, monthly income facts, mail content etc.) as well as to hijack the user’s web identities (e.g., online auction accounts). Many users do not seem to know or to care that broadcasted data can be easily intercepted; moreover even commercial users let high confidential customer related data (e.g. tender calculation details, negotiations with military customers) be sent unsecured via broadcast channels.