Obfuscation and Strict Online Anonymity

I consider the case for genuinely anonymous web searching. Big data seems to have it in for privacy. The story is well known, particularly since the dawn of the web. Vastly more personal information, monumental and quotidian, is gathered than in the pre-digital days. Once gathered it can be aggregated and analyzed to produce rich portraits, which in turn permit unnerving prediction of our future behavior. The new information can then be shared widely, limiting prospects and threatening autonomy. How should we respond? Following Nissenbaum (2011) and Brunton and Nissenbaum (2011 and 2013), I will argue that the proposed solutions—consent, anonymity as conventionally practiced, corporate best practices, and law—fail to protect us against routine surveillance of our online behavior. Brunton and Nissenbaum rightly maintain that, given the power imbalance between data holders and data subjects, obfuscation of one’s online activities is justified. Obfuscation works by generating “misleading, false, or ambiguous data with the intention of confusing an adversary or simply adding to the time or cost of separating good data from bad,” thus decreasing the value of the data collected (Brunton and Nissenbaum, 2011). The phenomenon is as old as the hills. Natural selection evidently blundered upon the tactic long ago. Take a savory butterfly whose markings mimic those of a toxic cousin. From the point of view of a would-be predator the data conveyed by the pattern is ambiguous. Is the bug lunch or potential last meal? In the light of the steep costs of a mistake, the savvy predator goes hungry. Online obfuscation works similarly, attempting for instance to disguise the surfer’s identity (Tor) or the nature of her queries (Howe and Nissenbaum 2009). Yet online obfuscation comes with significant social costs. First, it implies free riding. If I’ve installed an effective obfuscating program, I’m enjoying the benefits of an apparently free internet without paying the costs of surveillance, which are shifted entirely onto non-obfuscators. Second, it permits sketchy actors, from child pornographers to fraudsters, to operate with near impunity. Third, online merchants could plausibly claim that, when we shop online, surveillance is the price we pay for convenience. If we don’t like it, we should take our business to the local brick-and-mortar and pay with cash. Brunton and Nissenbaum have not fully addressed the last two costs. Nevertheless, I think the strict defender of online anonymity can meet these objections. Regarding the third, the future doesn’t bode well for offline shopping. Consider music and books. Intrepid shoppers can still find most of what they want in a book or record store. Soon, though, this will probably not be the case. And then there are those who, for perfectly good reasons, are sensitive about doing some of their shopping in person, perhaps because of their weight or sexual tastes. I argue that consumers should not have to pay the price of surveillance every time they want to buy that catchy new hit, that New York Times bestseller, or a sex toy.

Optimized Water Demand Management Through Intelligent Sensing And Analytics: The WISDOM Approach

New business and technology platforms are required to sustainably manage urban water resources [1,2]. However, any proposed solutions must be cognisant of security, privacy and other factors that may inhibit adoption and hence impact. The FP7 WISDOM project (funded by the European Commission - GA 619795) aims to achieve a step change in water and energy savings via the integration of innovative Information and Communication Technologies (ICT) frameworks to optimize water distribution networks and to enable change in consumer behavior through innovative demand management and adaptive pricing schemes [1,2,3]. The WISDOM concept centres on the integration of water distribution, sensor monitoring and communication systems coupled with semantic modelling (using ontologies, potentially connected to BIM, to serve as intelligent linkages throughout the entire framework) and control capabilities to provide for near real-time management of urban water resources. Fundamental to this framework are the needs and operational requirements of users and stakeholders at domestic, corporate and city levels and this requires the interoperability of a number of demand and operational models, fed with data from diverse sources such as sensor networks and crowsourced information. This has implications regarding the provenance and trustworthiness of such data and how it can be used in not only the understanding of system and user behaviours, but more importantly in the real-time control of such systems. Adaptive and intelligent analytics will be used to produce decision support systems that will drive the ability to increase the variability of both supply and consumption [3]. This in turn paves the way for adaptive pricing incentives and a greater understanding of the water-energy nexus. This integration is complex and uncertain yet being typical of a cyber-physical system, and its relevance transcends the water resource management domain. The WISDOM framework will be modeled and simulated with initial testing at an experimental facility in France (AQUASIM – a full-scale test-bed facility to study sustainable water management), then deployed and evaluated in in two pilots in Cardiff (UK) and La Spezia (Italy). These demonstrators will evaluate the integrated concept providing insight for wider adoption.