Aggregating Information About CView

cryingcopyrightOver the past little while there has been considerable attention focused on Virgin Media’s decision to trial Detica’s CView copyright monitoring system. This system uses Deep Packet Inspection (DPI) technology to identify data protocols and likely files that are being transferred in order to generate a Copyright Infringement Index (i.e. a ‘Piracy Index’). As outlined by Detica, CView will let ISPs work with content creators to determine whether ISPs providing content through their portals lead to reductions in ‘infringing’ transfers of content through P2P file sharing.

The story about Detica’s involvement really broke with Chris Williams’ piece over at the Register entitled, “Virgin Media to trial filesharing monitoring system.” In the piece, he recognized that the trial will encompass roughly 40% of Virgin’s customers, that the aim is to measure overall levels of filesharing rather than identify individual customers, and (at least initially) will focus on music. After I read the piece, I send some questions off to Detica and posted them (“Virgin to Use DPI to ID Copyright Infringement“) based on my reading of Williams’ piece and Detica’s consultation paper, and shortly thereafter followed up with Detica’s responses and thoughts on CView and privacy infringements (“Update to Virgin Media and Copyright DPI“). Between the posting of my questions, and the response from Detica, Richard Clayton had a meeting with representatives from Detica and posted the information they released to him over at Light Blue Touchpaper in a posting “What does Detica Detect?” The Register was also able to get face time with people working at Detica, leading Williams to produce his second piece “Spook firm readies Virgin Media filesharing probes.”

In the rest of this post, I want to pull together the information that has come to light so that we can get a better picture of what is known about CView. As such, this is very much a summary rather than an analytic post; hopefully I’ll have time to delve the information more critically in the near future.

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Update to Virgin Media and Copyright DPI

virginmedialogoRecently, I’ve heard back from Detica about CView and wanted to share the information that Detica has been provided. CView is the copyright detection Deep Packet Inspection (DPI) appliance that Virgin Media will be trialling, and is intended to measure the amount of copyright infringing files that cross Virgin’s network. This index will let Virgin determine whether the content deals they sign with content producers have a noticeable impact on the amount of infringing P2P traffic on their network. Where such deals reduce infringements, then we might expect Virgin to invest resources in agreements with content producers, and if such agreements have no impact then Virgin’s monies will likely be spent on alternate capital investments. I’ll note up front that I’ve sent some followup questions to seek additional clarity where the answers I received were somewhat hazy; such haziness appears to have been from a miscommunication, and is likely attributable to a particular question that was poorly phrased. Up front, I will state that I’m not willing to release the name of who I’m speaking with at Detica, as I don’t think that their name is needed for public consumption and would be an inappropriate disclosure of personal information.

The key question that is lurking in my own mind – if not that of others interested in the CView product – is whether or not the appliance can associate inspected data flows with individuals. In essence, I’m curious about whether or not CView has the ability to collect ‘personally identifiable information’ as outlined by the Privacy Commissioner of Canada in her recent findings on Bell’s use of DPI. In her findings, the Commissioner argues that because Bell customers’ subscriber ID and IP address are temporarily collated that personal information is being collected that Bell does collect personal information.

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Virgin Media to Monitor Copyright Infringement

truthliesandbroadbandLate last week The Register reported that Virgin Media is going to be trialling Detica’s Deep Packet Inspection (DPI) appliances to measure the levels of copyright-infringing file sharing that is occurring along Virgin Media’s networks. It’s important to note a few things right up front:

  1. I have a request in to the company manufacturing these appliances, Detica, and have been promised responses to my questions. In light of this, I’m not accusing Detica or Virgin Media of engaging in any ‘privacy invasive’ uses of DPI, at least not at the moment.
  2. The information that I’ll drawing on is, largely, from a consultation paper that Detica presented in late September of 2009.
  3. This post is largely meant as a ‘let’s calm down, and wait to hear about the technology’s details’ before suggesting that a massive campaign be mounted against what might be a relatively innocuous surveillance technology.

With that stated…

Detica describes themselves as a “business and technology consultancy specialising in helping clients collect, manage and exploit information to reveal actionable intelligence. As the digital revolution causes massive amounts of data to converge with a new generation of threats, many of our clients see this as one of their greatest challenges.” Their CView DPI system is meant to let ISPs better identify the amount of copyright infringing work that is coursing across their networks, in an effort to give ISPs better metrics as well as to determine whether arrangements between ISPs and content providers has a significant, measurable effect on the transfer of copyright infringing files.

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Tracing the Network, Tracing the NSA

NSA EagleIn many ways, I can credit the NSA along with the excellent reporting of Nate Anderson for why I’m so interested in surveillance technologies. In particular, when the story broke in 2005 that the NSA was likely engaged in massive wiretaps of domestic and international data traffic I was drawn to the power and capacity for the ‘net to be used for truly broad-based surveillance efforts. This interest was heightened when Nate published the first of a set of articles on deep packet inspection (DPI) for Ars Technica. Without these two key moments, along perhaps with some interesting reporting on copyright, I’d probably still be thinking through the conditions of ontological psychology through a Heideggerian or Hegellian lens.

Given that I am engaged in research into surveillance technologies, and have the absolute pleasure to be associated with truly excellent scholars, activists, advocates, collaborators, and friends who share similar research interests, I wanted to take a moment to ask you, my readers, to help us map data traffic. As you may be aware, the NSA is reputed to have installed systems in various networking hubs that lets them examine massive amounts of data traffic. It’s not entirely known how they inspect this traffic, or the algorithms that are used to parse the fire hose of data they must be inundated by, but researchers at the University of Toronto have a decent idea of what ‘carrier hotels’, or major Internet exchange/collocation points, have likely been compromised by NSA surveillance instruments.

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Privacy Norms in the Bio-Digital World

pixelatedworldThe Western world is pervaded by digital information, to the point where we might argue that most Western citizens operate in a bio-digital field that is constituted by the conditions of life and life’s (now intrinsic) relationships to digital code. While historically (if 30 years or so can withstand the definitional intonations of ‘historically) such notions of code would dominantly pertain to government databanks and massive corporate uses of code and data, with the advent of the ‘social web’ and ease of mashups we are forced to engage with questions of how information, code, and privacy norms and regulations pertain to individual’s usage of data sources. While in some instances we see penalties being handed down to individuals that publicly release sensitive information (such as Sweden’s Bodil Lindqvist, who was fined for posting personal data about fellow church parishioners without consent), what is the penalty when public information is situated outside of its original format and mashed-up with other data sources? What happens when we correlate data to ‘map’ it?

Let’s get into some ‘concrete’ examples to engage with this matter. First, I want to point to geo-locating trace route data, the information that identifies the origin of website visitors’ data traffic, to start thinking about mashups and privacy infringements. Second, I’ll briefly point to some of the challenges arising with the meta-coding of the world using Augmented Reality (AR) technologies. The overall aim is not to ‘resolve’ any privacy questions, but to try and reflect on differences between ‘specificity’ of geolocation technology, the implications of specificity, and potential need to establish a new set of privacy norms given the bio-digital fields that we find ourself immersed in.

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Rendering CCTV (Somewhat) More Transparent

CCTV meets consumerismIn a conversation with Prof. Andrew Clement this summer we got talking about the ever-increasing deployment of CCTV cameras throughout Canada. The conversation was, at least in part, motivated by the massive number of cameras that are being deployed throughout Vancouver with the leadup to the 2010 Olympic games; these cameras were one of the key focuses of the 10th Annual Security and Privacy Conference, where the BC Privacy Commissioner said that he might resign if the surveillance infrastructure is not taken down following the games.

I don’t want to delve into what, in particular, Prof. Clement is thinking of doing surrounding CCTV given that I don’t think he’s publicly announced his intentions. What I will do, however, is outline my own two-pronged approach to rendering CCTV a little more transparent. At the onset, I’ll note that:

  1. My method will rely on technology (augmented reality) that is presently only in the hands of a small minority of the population;
  2. My method is meant to be more and more useful as the years continue (and as the technology becomes increasingly accessible to consumers).

The broad goal is the following: develop a set of norms and processes to categorize different CCTV installations. Having accomplished this task, a framework would be developed for an augmented reality program (here’s a great blog on AR) that could ‘label’ where CCTV installations are and ‘grade’ them based on the already established norms and processes.

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