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Archives for February 2018

No boundaries for credentials: New password leaks to Mixpanel and Session Replay Companies

February 26, 2018 by

In this installment of the “No Boundaries” series we show how wholesale collection of user interactions by third-party analytics and session replay scripts cause inadvertent collection of passwords.
By Steve Englehardt, Gunes Acar and Arvind Narayanan

Following the recent report that Mixpanel, a popular analytics provider, had been inadvertently collecting passwords that users typed into websites, we took a deeper look [1]. While Mixpanel characterized it as a “bug, plain and simple” — one that it had fixed — we found that:

  • Mixpanel continues to grab passwords on some sites, even with the patched version of its code.
  • The problem is not limited to Mixpanel; also affected are session replay scripts, which we revealed earlier to be scooping up various other types of sensitive information.
  • There is no foolproof way for these third party scripts to prevent password collection, given their intended functionality. In some cases, password collection happens due to extremely subtle interactions between code from different entities.

Overall, we think that the approach of third-party scripts collecting the entirety of web pages or form inputs, and attempting to filter out sensitive information is incompatible with user security and privacy.

Password leaks are not limited to Mixpanel

In our research we found password leaks to four different third-party analytics providers across a number of websites. The sources are numerous: several variants of a “Show Password” feature added by site owners, an unexpected interaction with an unrelated third-party script, unanticipated changes to page structure by browser extensions, and even a bug in privacy tools of one of the analytics libraries. However, the underlying cause is the same: wholesale collection of user input data, with protection provided by set of blacklist-based heuristics to filter password fields. We argue that this heuristic approach is bound to fail, and provide a list of examples in which it does.

This summary is provided not as an exhaustive list of all possible vulnerabilities, but rather as examples of how things can go wrong. A detailed description of each vulnerability and the vendor response is available in the Appendix.

[Read more…]

Filed Under: Privacy & Security Tagged With: , , , , ,

Blockchain: What is it good for?

February 26, 2018 by

Blockchain and cryptocurrencies are surrounded by world-historic levels of hype and snake oil. For people like me who take the old-fashioned view that technical claims should be backed by sound arguments and evidence, it’s easy to fall into the trap of concluding that there is no there there–and that blockchain and cryptocurrencies are fundamentally useless. This post is my attempt to argue that if we strip away the fluff, some valuable computer science ideas remain.

Let’s start by setting aside the currency part, for now, and focusing on blockchains. The core idea goes back to at least the 1990s: replicate a system’s state across a set of machines; use some kind of distributed consensus algorithm to agree on an append-only log of events that change the state; and use cryptographic hash-chaining to make the log tamper-evident. Much of the legitimate excitement about “blockchain” is driven by the use of this approach to enhance transparency and accountability, by making certain types of actions in a system visible. If an action is recorded in your blockchain, everyone can see it. If it is not in your blockchain, it is ignored as invalid.

An example of this basic approach is certificate transparency, in which certificate authorities (“CAs,” which vouch for digital certificates connecting a cryptographic key to the owner of a DNS name) must publish the certificates they issue on a public list, and systems refuse to accept certificates that are not on the list. This ensures that if a CA issues a certificate without permission from a name’s legitimate owner, the bogus certificate cannot be used without publishing it and thereby enabling the legitimate owner to raise an alarm, potentially leading to public consequences for the misbehaving CA.

In today’s world, with so much talk about the policy advantages of technological transparency, the use of blockchains for transparency can an important tool.

What about cryptocurrencies? There is a lot of debate about whether systems like Bitcoin are genuinely useful as a money transfer technology. Bitcoin has many limitations: transactions take a long time to confirm, and the mining-based consensus mechanism burns a lot of energy. Whether and how these limitations can be overcome is a subject of current research.

Cryptocurrencies are most useful when coupled with “smart contracts,” which allow parties to define the behavior of a virtual actor in code, and have the cryptocurrency’s consensus system enforce that the virtual actor behaves according to its code. The name “smart contract” is misleading, because these mechanisms differ significantly from legal contracts.  (A legal contract is an explicit agreement among an enumerated set of parties that constrains the behavior of those parties and is enforced by ex post remedies. A “smart contract” doesn’t require explicit agreement from parties, doesn’t enumerate participating parties, doesn’t constrain behavior of existing parties but instead creates a new virtual party whose behavior is constrained, and is enforced by ex ante prevention of deviations.) It is precisely these differences that make “smart contracts” useful.

From a computer science standpoint, what is exciting about “smart contracts” is that they let us make conditional payments an integral part of the toolbox for designing distributed protocols. A party can be required to escrow a deposit as a condition of participating in some process, and the return of that deposit, in part or in whole, can be conditioned on the party performing arbitrary required steps, as long as compliance can be checked by a computation.

Another way of viewing the value of “smart contracts” is by observing that we often define correctness for a new distributed protocol by postulating a hypothetical trusted third party who “referees” the protocol, and then proving some kind of equivalence between the new referee-free protocol we have designed and the notional refereed protocol. It sure would be nice if we could just turn the notional referee into a smart contract and let the consensus system enforce correctness.

But all of this requires a “smart contract” system that is efficient and scalable–otherwise the cost of using “smart contracts” will be excessive. Existing systems like Ethereum scale poorly. This too is a problem that will need to be overcome by new research. (Spoiler alert: We’ll be writing here about a research solution in the coming months.)

These are not the only things that blockchain and cryptocurrencies are good for. But I hope they are convincing examples. It’s sad that the hype and snake oil has gotten so extreme that it can be hard to see the benefits. The benefits do exist.

 

Filed Under: Cryptocurrencies

How Tech is Failing Victims of Intimate Partner Violence: Thomas Ristenpart at CITP

February 23, 2018 by

What technology risks are faced by people who experience intimate partner violence? How is the security community failing them, and what questions might we need to ask to make progress on social and technical interventions?

Speaking Tuesday at CITP was Thomas Ristenpart (@TomRistenpart), an associate professor at Cornell Tech and a member of the Department of Computer Science at Cornell University. Before joining Cornell Tech in 2015, Thomas was an assistant professor at the University of Wisconsin-Madison. His research spans a wide range of computer security topics, including digital privacy and safety in intimate partner violence, alongside work on cloud computing security, confidentiality and privacy in machine learning, and topics in applied and theoretical cryptography.

Throughout this talk, I found myself overwhelmed by the scope of the challenges faced by so many people– and inspired by the way that Thomas and his collaborators have taken thorough, meaningful steps on this vital issue.

Understanding Intimate Partner Violence

Intimate partner violence (IPV) is a huge problem, says Thomas. 25% of women and 11% of men will experience rape, physical violence, and/or stalking by an intimate partner, according to the National Intimate Partner and Sexual Violence Survey. To put this question in context for tech companies, this means that 360 million Facebook users and 252 million Android users will experience this kind of violence.

Prior research over the years has shown that abusers are taking advantage of technology to harm victims in a wide range of ways, including spyware, harassment, and non-consensual photography. In a team with Nicki Dell, Diana Freed, Karen Levy, Damon McCoy, Rahul Chatterjee, Peri Doerfler, and Sam Havron, Thomas and his collaborators have working with the New York City Mayor’s office to Combat Domestic Violence (NYC CDV).

To start, the researchers spent a year doing qualitative research with people who experience domestic violence. The research that Thomas is sharing today draws from that work.

The research team worked with the New York City Family Justice Centers, who offer a range of services for domestic violence, sex trafficking, and elder abuse victims– from civil and legal services to access to shelters, counseling, and support from nonprofits. The centers were a crucial resource for the researchers, since they connect nonprofits, government actors, and survivors and victims. Over seriesof year-long qualitative studies (see also this paper), researchers held 11 focus groups with 39 women who speak English and Spanish from 18-165. Most of them are no longer working with the abusive partner. They also held semi-structured interviews with 50 professionals working on IPV– case managers, social workers, attorneys/paralegals, and police officers. Together, this research represents the largest and most demographically diverse study to date on IPV.

Common Technology Attacks in Intimate Partner Violence Situations

The researchers spotted a range of common themes across clients of the NYC CDV. They talked about stalkers who accessed their phones and social media, installed spyware, took compromising images through the spyware, and then impersonating them to use the account to send compromising, intimate images to employers, family, and friends. Abusers are taking advantage of every possible technology to create problems through many modes. Overall, they identified four kinds of common attacks:

  • In ownership-based attacks, the abuser owns the account that the victim is using. This gives them immediate access to controlling the device. Often people will buy a device for someone else to gain a foothold in that person’s life and home.
  • In account/device compromise, someone compels, guesses, or otherwise compromises passwords.
  • Harmful messages or posts involve calling/texting/messaging the victim. This involves harassing a victim’s friends/family, and sometimes encouraging other people to harass that person by proxy.
  • Abusers also exposed private information: blackmailing someone by threat of exposure, sharing non-consensual intimate images, and creating fake profiles/advertisements for that person on other sites.

In many of these cases, abusers are re-purposing ordinary software for some kind of unhelpful purpose. For example, abusers use two-factor authentication to prevent victims from accessing and recovering access to their own account.

Non-Technical Infrastructures Aren’t Helping Victims & Professionals with Technical Issues

Thomas tells us that despite these risks, they didn’t find a single technologist in the network of support for people facing intimate partner violence. So it’s not surprising that these services don’t have any best practices for evaluating technology risks. On top of that, victims overwhelmingly report having insufficient technology understanding to deal with tech abuse.

Abusers are typically considered to be “more tech-savvy” than victims, and professionals overwhelmingly report having insufficient technology understanding to help with tech abuse. Many of them just google as they go.

Thomas also points out that the intersection of technology and intimate partner violence raises important legal and policy issues. First, digital abuse is usually not recognized as a form of abuse that warrants a protection order. When someone goes to a family court, they have to convince a judge to get a protection order- and judges aren’t convinced by digital harassment– even though the protection order can legally restrict an abuser from sending the message. Second, when an abuser creates a fake account on a site like Tinder and creates “come rape me” style ads, the abuser is technically the legal owner of the account, so it can be difficult to take down the ads, especially for smaller websites that don’t respond to copyright takedown requests.

Technical Mechanisms are Failing Too: Context Undermines Existing Security Systems

Abusers aren’t the sophisticated cyber-operatives that people sometimes talk about at security conferences. Instead, researchers saw two classes of attacks: (a) UI-bound adversaries: an adversarial but authenticated user who interacts with the system via the normal user interface, and (b) Spyware adversaries, who installs/repurposes commodity software for surveillance of the victim. Neither of these require technical sophistication.

Why are these so effective? Thomas says that the reason is that the threat models and the assumptions in the security world don’t match threats. For example, many systems are designed to protect from a stranger on the internet who doesn’t know the victim personally and connects from elsewhere. With intimate partner violence, the attacker knows the victim personally, they can guess or compel disclosure, they may connect from the victim’s computer or same home, and may own the account or device that’s being used. The abuser is often an earner who pays for accounts and devices.

The same problems apply with fake accounts and detection of abusive content. Many fake social media profiles obviously belong to the abuser but survivors are rarely able to prove it. When abusers send hurtful, abusive messages, someone who lacks the content may not be able to detect it. Outside of the context of IPV, a picture of a gun might be just a picture of a gun- but in context, it can be very threatening.

Common Advice Also Fails Victims

Much of the common advice just won’t work. Sometimes people are urged to delete their account. You can’t just shut off contact with an abuser- you might be legally obligated to communicate (shared custody of children). You can’t get new devices because the abuser pays for phones, family plan, and/or children’s devices (which is a vector of surveillance). People can’t necessarily get off social media, because they need it to get access to their friends and family. On top of that, any of these actions could escalate abuse; victims are very worried about cutting off access or uninstalling spyware because they’re worried about further violence from the abuser.

Many Makers of Spyware Promote their Software for Intimate Partner Surveillance

Next, Thomas tells us about intimate partner surveillance (IPS) from a new paper led by Diana Freed on How Intimate Partner Abusers Exploit Technology. Shelters and family justice centers have had problems where someone shows up with software on their phone that allowed the abuser to track them, kick down a door, and endanger the victim. No one could name a single product that was used by abusers, partly because our ability to diagnose spyware from a technical perspective is limited. On the other hand, if you google “track my girlfriend,” you will find a host of companies that are peddling spyware.

To study the range of spyware systems, Thomas and his colleagues used “snowball” searching and used auto-complete to look for other queries that other people were searching. From a set of roughly 27k urls, they investigated 100 randomly sampled URLs. They found that 60% were related to intimate partner surveillance: how-to blogs, Q&A forums, news articles, app websites, and links to apps on the Google Play Store and the Apple App Store. Many of the professional-grade spyware providers provide apps directly through app stores, as well as “off-store” apps. They labeled a thousand of the apps they found and discovered that about 28% of them were potential IPS tools.

The researchers found overt tools for intimate partner surveillance apps, as well as systems for safety, theft-tracking, child tracking, and employee tracking that were repurposed for abuse. In many cases, it’s hard to point to a single piece of software and say that it’s bad. While apps sometimes purport to provide services to parents to track children, searches for intimate partner violence also surface paid ads to products that don’t directly claim to be for use within intimate partners. Ever since a ruling from the FTC, companies work to preserve plausible deniability.

In an audit study the researchers emailed customer support for 11 apps (on-store and off-store) posing as an abuser. They received nine responses. Eight of them condoned intimate partner violence and gave them advice on making the app hard to find. Only one indicated that it could be illegal.

Many of these systems have rich capabilities: location tracking, texts, call recordings, media contents, app usage, internet activity logs, keylogging, geographic tracking. All of the off-store systems have covert features to hide the fact that the app is installed. Even some of the Google Play Store apps have features to make the apps covert.

Early Steps for Supporting Victims: Detecting Spyware

What’s the current state of the art? Right now, practitioners tell people that if your battery runs unusually low, they may be a victim of spyware– not very effective. Do spyware removal tools work? They had high but not perfect detection rates for off-store intimate-purpose surveillance systems. However they did a poor job at detecting on-store spyware tools.

 

Thomas recaps what they learned from this study: There’s a large ecosystem of spyware apps, the dual use of these apps creates a significant challenge, many developers are condoning intimate partner surveillance, and existing anti-spyware technologies are insufficient at detecting tools.

Based on this work, Thomas and his collaborators are working with the NYC Mayor’s office and the National Network to end Domestic Violence to develop ways to detect spyware, to develop new surveys of technology risks, and find new kinds of interventions.

Thomas concludes with an appeal to companies and computer scientists that we pay more attention to the needs of the most vulnerable people affected by our work, volunteer for organizations that support victims, and develop new approaches to protect people in these all-too-common situations.

Filed Under: CITP Events Tagged With: , , , ,

Are voting-machine modems truly divorced from the Internet?

February 22, 2018 by

(This article is written jointly with my colleague Kyle Jamieson, who specializes in wireless networks.)

[See also: The myth of the hacker-proof voting machine]

The ES&S model DS200 optical-scan voting machine has a cell-phone modem that it uses to upload election-night results from the voting machine to the “county central” canvassing computer.  We know it’s a bad idea to connect voting machines (and canvassing computers) to the Internet, because this allows their vulnerabilities to be exploited by hackers anywhere in the world.  (In fact, a judge in New Jersey ruled in 2009 that the state must not connect its voting machines and canvassing computers to the internet, for that very reason.)  So the question is, does DS200’s cell-phone modem, in effect, connect the voting machine to the Internet?

The vendor (ES&S) and the counties that bought the machine say, “no, it’s an analog modem.”  That’s not true; it appears to be a Multitech MTSMC-C2-N3-R.1 (Verizon C2 series modem), a fairly complex digital device.  But maybe what they mean is “it’s just a phone call, not really the Internet.”  So let’s review how phone calls work:

The voting machine calls the county-central computer using its cell-phone modem to the nearest tower; this connects through Verizon’s “Autonomous System” (AS), part of the packet-switched Internet, to a cell tower (or land-line station) near the canvassing computer.

Verizon attempts to control access to the routers internal to its own AS, using firewall rules on the border routers.  Each border router runs (probably) millions of lines of software; as such it is subject to bugs and vulnerabilities.  If a hacker finds one of these vulnerabilities, he can modify messages as they transit the AS network:

Do border routers actually have vulnerabilities in practice?  Of course they do!  US-CERT has highlighted this as an issue of importance.  It would surprising if the Russian mafia or the FBI were not equipped to exploit such vulnerabilities.

Even easier than hacking through router bugs is just setting up an imposter cell-phone “tower” near the voting machine; one commonly used brand of these, used by many police departments, is called “Stingray.”

I’ve labelled the hacker as “MitM” for “man-in-the-middle.”  He is well positioned to alter vote totals as they are uploaded.  Of course, he will do better to put his Stingray near the county-central canvassing computer, so he can hack all the voting machines in the county, not just one near his Stingray:

So, in summary: phone calls are not unconnected to the Internet; the hacking of phone calls is easy (police departments with Stingray devices do it all the time); and even between the cell-towers (or land-line stations), your calls go over parts of the Internet.  If your state laws, or a court with jurisdiction, say not to connect your voting machines to the Internet, then you probably shouldn’t use telephone modems either.

Filed Under: Other Topics Tagged With: ,

(Mis)conceptions About the Impact of Surveillance

February 14, 2018 by

Does surveillance impact behavior? Or is its effect, if real, only temporary or trivial? Government surveillance is back in the news thanks to the so-called “Nunes memo”, making this is a perfect time to examine new research on the impact of surveillance. This includes my own recent work, as my doctoral research at the Oxford Internet Institute, University of Oxford  examined “chilling effects” online, that is, how online surveillance, and other regulatory activities, may impact, chill, or deter people’s activities online.

Though the controversy surrounding the Nunes memo critiquing FBI surveillance under the Foreign Intelligence Surveillance Act (FISA) is primarily political, it takes place against the backdrop of the wider debate about Congressional reauthorization of FISA’s Section 702, which allows the U.S. Government to intercept and collect emails, phone records, and other communications of foreigners residing abroad, without a warrant. On that count, civil society groups have expressed concerns about the impact of government surveillance like that available under FISA, including “chilling effects” on rights and freedoms. Indeed, civil liberties and rights activists have long argued, and surveillance experts like David Lyon long explained, that surveillance and similar threats can have these corrosive impacts.

Yet, skepticism about such claims is common and persistent. As Kaminski and Witov recently noted, many “evince skepticism over the effects of surveillance” with deep disagreements over the “effects of surveillance” on “intellectual queries” and “development”.  But why?  The answer is complicated but likely lies in the present (thin) state of research on these issues, but also common conceptions, and misconceptions, about surveillance and impact on people and broader society.

Skepticism and assumptions about impact
Skepticism about surveillance impacts like chilling effects is, as noted, persistent with commentators like Stanford Law’s Michael Sklansky insisting there is “little empirical support” for chilling effects associated with surveillance or Leslie Kendrick, of UVA Law, labeling the evidence supporting such claims “flimsy” and calling for more systematic research on point. Part of the problem is precisely this: the impact of surveillance—both mass and targeted forms—is difficult to document, measure, and explore, especially chilling effects or self-censorship. This is because demonstrating self-censorship or chill requires showing a counterfactual state of affairs: that a person would have said something or done something but for some surveillance threat or awareness.

But another challenge, just as important to address, concerns common assumptions and perceptions as to what surveillance impact or chilling effects might look like. Here, both members of the general public as well as experts, judges, and lawyers often assume or expect surveillance to have obvious, apparent, and pervasive impact on our most fundamental democratic rights and freedoms—like clear suppression of political speech or the right to peaceful assembly.

A great example of this assumption, leading to skepticism about whether surveillance may promote self-censorship or have broader societal chilling effects—is here expressed by University of Chicago Law’s Eric Posner. Posner, a leading legal scholar who also incorporates empirical methods in his work, conveys his skepticism about the “threat” posed by National Security Agency (NSA) surveillance in a New York Times “Room for Debate”  discussion, writing:

This brings me to another valuable point you made, which is that when people believe that the government exercises surveillance, they become reluctant to exercise democratic freedoms. This is a textbook objection to surveillance, I agree, but it also is another objection that I would place under “theoretical” rather than real.  Is there any evidence that over the 12 years, during the flowering of the so-called surveillance state, Americans have become less politically active? More worried about government suppression of dissent? Less willing to listen to opposing voices? All the evidence points in the opposite direction… It is hard to think of another period so full of robust political debate since the late 1960s—another era of government surveillance.

For Posner, the mere existence of “robust” political debate and activities in society is compelling evidence against claims about surveillance chill.

Similarly, Sklansky argues not only that there is “little empirical support” for the claim that surveillance would “chill independent thought, robust debate, personal growth, and intimate friendship”— what he terms “the stultification thesis”—but like Posner, he finds persuasive evidence against the claim “all around us”. He cites, for example, the widespread “sharing of personal information” online (which presumably would not happen if surveillance was having a dampening effect); how employer monitoring has not deterred employee emailing nor freedom of information laws deterred “intra-governmental communications”; and how young people, the “digital natives” that have grown up with the internet, social media, and surveillance, are far from stultified and conforming but arguably even more personally expressive and experimental than previous generations.  In light of all that, Sklansky dismisses surveillance chill as simply not “worth worrying about”.

I sometimes call this the “Orwell effect”—the common assumption, likely thanks to the immense impact Orwell’s classic novel 1984 has had on popular culture, that surveillance will have dystopian societal impact, with widespread suppression of personal sharing, expression, and political dissent. When Posner and Sklansky (and others that share these common expectations) do not see these more obvious and far reaching impacts, they then discount more subtle and less apparent impacts and effects that may, over the long term, be just as concerning for democratic rights and freedoms. Of course, theorists and scholars like Daniel Solove have long interrogated and critiqued Orwell’s impact on our understanding of privacy and Sklansky is himself wary of Orwell’s influence, so it is no surprise his work also shapes common beliefs and conceptions about the impact of surveillance.  That influence is compounded by the earlier noted lack of systematic empirical research providing more grounded insights and understanding.

This is not only an academic issue. Government surveillance powers and practices are often justified with reference to other national security concerns and threats like terrorism, as this House brief on the FISA re-authorization illustrates. If concerns about chilling effects associated with surveillance and other negative impacts are minimized or discounted based on misconceptions or thin empirical grounding, then challenging surveillance powers and their expansion is much more difficult, with real concrete implications for rights and freedoms.

So, the challenge for documenting, exploring, and understanding the impact of surveillance is really two-fold. The first is one of research methodology and design: designing research to document the impact of surveillance, and a second concerns common assumptions and perceptions as to what surveillance chilling effects might look like—with even experts like Posner or Sklansky assuming widespread speech suppression and conformity due to surveillance.

New research, new insights
Today, new systematic empirical research on the impact of surveillance is being done, with several recent studies having documented surveillance chilling effects in different contexts, including recent studies by  Stoycheff [1], Marthews and Tucker [2], as well as my own recent research.  This includes an empirical legal study[3] on how the Snowden revelations about NSA surveillance impacted Wikipedia use—which received extensive media coverage in the U.S. and internationally— and a more recent study[4], which I wrote about recently in Slate, that examined among other things how state and corporate surveillance impact or “chill” certain people or groups differently. A lot of this new work was not possible in previous times, as it is based on new forms of data being made available to researchers and insights gleaned from analyzing public leaks and disclosures concerning surveillance like the Snowden revelations.

The story these and other new studies tell when it comes to the impact of surveillance is more complicated and subtle, suggesting the common assumptions of Posner and Sklansky are actually misconceptions. Though more subtle, these impacts are no less concerning and corrosive to democratic rights and freedoms, a point consistent with the work of surveillance studies theorists like David Lyon[5] and warnings from researchers at places like the Citizen Lab[6], Berkman Klein Center[7], and here at the CITP[8].  In subsequent posts, I will discuss these studies more fully, to paint a broader picture of surveillance effects today and, in light of increasingly sophisticated targeting and emerging automation technologies, tomorrow. Stay tuned.

* Jonathon Penney is a Research Affiliate of Princeton’s CITP, a Research Fellow at the Citizen Lab, located at the University of Toronto’s Munk School of Global Affairs, and teaches law as an Assistant Professor at Dalhousie University. He is also a research collaborator with Civil Servant at the MIT Media Lab. Find him on twitter at @jon_penney. 

—

[1] Stoycheff, E. (2016). Under Surveillance: Examining Facebook’s Spiral of Silence Effects in the Wake of NSA Internet Monitoring. Journalism & Mass Communication Quarterly. doi: 10.1177/1077699016630255

[2] Marthews, A., & Tucker, C. (2014). Government Surveillance and Internet Search Behavior. MIT Sloane Working Paper No. 14380.

[3] Penney, J. (2016). Chilling Effects: Online Surveillance and Wikipedia Use. Berkeley Tech. L.J., 31, 117-182.

[4] Penney, J. (2017). Internet surveillance, regulation, and chilling effects online: A comparative case study. Internet Policy Review, forthcoming

[5] See for example: Lyon, D. (2015). Surveillance After Snowden. Cambridge, MA: Polity Press; Lyon, D. (2006). Theorizing surveillance: The panopticon and beyond. Cullompton, Devon: Willan Publishing; Lyon, D. (2003). Surveillance After September 11. Cambridge, MA: Polity. See also Marx, G.T., (2002). What’s New About the ‘New Surveillance’? Classifying for Change and Continuity. Surveillance & Society, 1(1), pp. 9-29;  Graham, S. & D. Wood. (2003). Digitising Surveillance: Categorisation, Space, Inequality, Critical Social Policy, 23(2): 227-248.

[6] See for example, recent works: Parsons, C., Israel, T., Deibert, R., Gill, L., and Robinson, B. (2018). Citizen Lab and CIPPIC Release Analysis of the Communications Security Establishment Act. Citizen Lab Research Brief No. 104, January 2018; Parsons, C. (2015). Beyond Privacy: Articulating the Broader Harms of Pervasive Mass Surveillance. Media and Communication, 3(3), 1-11; Deibert, R. (2015). The Geopolitics of Cyberspace After Snowden. Current History, (114) 768 (2015): 9-15; Deibert, R. (2013) Black Code: Inside the Battle for Cyberspace, (Toronto: McClelland & Stewart).  See also

[7] See for example, recent work on the Surveillance Project, Berkman Klein Center for Internet and Society, Harvard University.

[8] See for example, recent work: Su, J., Shukla, A., Goel, S., Narayanan, A., De-anonymizing Web Browsing Data with Social Networks. World Wide Web Conference 2017; Zeide, E. (2017). The Structural Consequences of Big Data-Driven Education. Big Data. June 2017, 5(2): 164-172, https://doi.org/10.1089/big.2016.0061;MacKinnon, R. (2012) Consent of the networked: The worldwide struggle for Internet freedom. New York: Basic Books.; Narayanan, A. & Shmatikov, V. (2009). See also multiple previous Freedom to Tinker posts discussing research/issues point.

 

Filed Under: National Security & Surveillance, Privacy & Security Tagged With: , , , , , , ,