Entries Tagged "taxonomies"

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A Taxonomy of Access Control

My personal definition of a brilliant idea is one that is immediately obvious once it’s explained, but no one has thought of it before. I can’t believe that no one has described this taxonomy of access control before Ittay Eyal laid it out in this paper. The paper is about cryptocurrency wallet design, but the ideas are more general. Ittay points out that a key—or an account, or anything similar—can be in one of four states:

safe Only the user has access,
loss No one has access,
leak Both the user and the adversary have access, or
theft Only the adversary has access.

Once you know these states, you can assign probabilities of transitioning from one state to another (someone hacks your account and locks you out, you forgot your own password, etc.) and then build optimal security and reliability to deal with it. It’s a truly elegant way of conceptualizing the problem.

Posted on August 12, 2022 at 6:38 AMView Comments

New Paper on Encryption Workarounds

I have written a paper with Orin Kerr on encryption workarounds. Our goal wasn’t to make any policy recommendations. (That was a good thing, since we probably don’t agree on any.) Our goal was to present a taxonomy of different workarounds, and discuss their technical and legal characteristics and complications.

Abstract: The widespread use of encryption has triggered a new step in many criminal investigations: the encryption workaround. We define an encryption workaround as any lawful government effort to reveal an unencrypted version of a target’s data that has been concealed by encryption. This essay provides an overview of encryption workarounds. It begins with a taxonomy of the different ways investigators might try to bypass encryption schemes. We classify six kinds of workarounds: find the key, guess the key, compel the key, exploit a flaw in the encryption software, access plaintext while the device is in use, and locate another plaintext copy. For each approach, we consider the practical, technological, and legal hurdles raised by its use.

The remainder of the essay develops lessons about encryption workarounds and the broader public debate about encryption in criminal investigations. First, encryption workarounds are inherently probabilistic. None work every time, and none can be categorically ruled out every time. Second, the different resources required for different workarounds will have significant distributional effects on law enforcement. Some techniques are inexpensive and can be used often by many law enforcement agencies; some are sophisticated or expensive and likely to be used rarely and only by a few. Third, the scope of legal authority to compel third-party assistance will be a continuing challenge. And fourth, the law governing encryption workarounds remains uncertain and underdeveloped. Whether encryption will be a game-changer or a speed bump depends on both technological change and the resolution of important legal questions that currently remain unanswered.

The paper is finished, but we’ll be revising it once more before final publication. Comments are appreciated.

Posted on March 22, 2017 at 6:23 AMView Comments

"Taxonomy of Operational Cyber Security Risks"

I’m a big fan of taxonomies, and this—from Carnegie Mellon—seems like a useful one:

The taxonomy of operational cyber security risks, summarized in Table 1 and detailed in this section, is structured around a hierarchy of classes, subclasses, and elements. The taxonomy has four main classes:

  • actions of people—action, or lack of action, taken by people either deliberately or accidentally that impact cyber security
  • systems and technology failures—failure of hardware, software, and information systems
  • failed internal processes—problems in the internal business processes that impact the ability to implement, manage, and sustain cyber security, such as process design, execution, and control
  • external events—issues often outside the control of the organization, such as disasters, legal issues, business issues, and service provider dependencies

Each of these four classes is further decomposed into subclasses, and each subclass is described by its elements.

Posted on August 10, 2011 at 6:39 AMView Comments

A Revised Taxonomy of Social Networking Data

Lately I’ve been reading about user security and privacy—control, really—on social networking sites. The issues are hard and the solutions harder, but I’m seeing a lot of confusion in even forming the questions. Social networking sites deal with several different types of user data, and it’s essential to separate them.

Below is my taxonomy of social networking data, which I first presented at the Internet Governance Forum meeting last November, and again—revised—at an OECD workshop on the role of Internet intermediaries in June.

  • Service data is the data you give to a social networking site in order to use it. Such data might include your legal name, your age, and your credit-card number.
  • Disclosed data is what you post on your own pages: blog entries, photographs, messages, comments, and so on.
  • Entrusted data is what you post on other people’s pages. It’s basically the same stuff as disclosed data, but the difference is that you don’t have control over the data once you post it—another user does.
  • Incidental data is what other people post about you: a paragraph about you that someone else writes, a picture of you that someone else takes and posts. Again, it’s basically the same stuff as disclosed data, but the difference is that you don’t have control over it, and you didn’t create it in the first place.
  • Behavioral data is data the site collects about your habits by recording what you do and who you do it with. It might include games you play, topics you write about, news articles you access (and what that says about your political leanings), and so on.
  • Derived data is data about you that is derived from all the other data. For example, if 80 percent of your friends self-identify as gay, you’re likely gay yourself.

There are other ways to look at user data. Some of it you give to the social networking site in confidence, expecting the site to safeguard the data. Some of it you publish openly and others use it to find you. And some of it you share only within an enumerated circle of other users. At the receiving end, social networking sites can monetize all of it: generally by selling targeted advertising.

Different social networking sites give users different rights for each data type. Some are always private, some can be made private, and some are always public. Some can be edited or deleted—I know one site that allows entrusted data to be edited or deleted within a 24-hour period—and some cannot. Some can be viewed and some cannot.

It’s also clear that users should have different rights with respect to each data type. We should be allowed to export, change, and delete disclosed data, even if the social networking sites don’t want us to. It’s less clear what rights we have for entrusted data—and far less clear for incidental data. If you post pictures from a party with me in them, can I demand you remove those pictures—or at least blur out my face? (Go look up the conviction of three Google executives in Italian court over a YouTube video.) And what about behavioral data? It’s frequently a critical part of a social networking site’s business model. We often don’t mind if a site uses it to target advertisements, but are less sanguine when it sells data to third parties.

As we continue our conversations about what sorts of fundamental rights people have with respect to their data, and more countries contemplate regulation on social networking sites and user data, it will be important to keep this taxonomy in mind. The sorts of things that would be suitable for one type of data might be completely unworkable and inappropriate for another.

This essay previously appeared in IEEE Security & Privacy.

Edited to add: this post has been translated into Portuguese.

Posted on August 10, 2010 at 6:51 AMView Comments

Denial-of-Service Attack Against CALEA

Interesting:

The researchers say they’ve found a vulnerability in U.S. law enforcement wiretaps, if only theoretical, that would allow a surveillance target to thwart the authorities by launching what amounts to a denial-of-service (DoS) attack against the connection between the phone company switches and law enforcement.

[…]

The University of Pennsylvania researchers found the flaw after examining the telecommunication industry standard ANSI Standard J-STD-025, which addresses the transmission of wiretapped data from telecom switches to authorities, according to IDG News Service. Under the 1994 Communications Assistance for Law Enforcement Act, or Calea, telecoms are required to design their network architecture to make it easy for authorities to tap calls transmitted over digitally switched phone networks.

But the researchers, who describe their findings in a paper, found that the standard allows for very little bandwidth for the transmission of data about phone calls, which can be overwhelmed in a DoS attack. When a wiretap is enabled, the phone company’s switch establishes a 64-Kbps Call Data Channel to send data about the call to law enforcement. That paltry channel can be flooded if a target of the wiretap sends dozens of simultaneous SMS messages or makes numerous VOIP phone calls “without significant degradation of service to the targets’ actual traffic.”

As a result, the researchers say, law enforcement could lose records of whom a target called and when. The attack could also prevent the content of calls from being accurately monitored or recorded.

The paper. Comments by Matt Blaze, one of the paper’s authors.

Posted on November 20, 2009 at 6:11 AMView Comments

Sidebar photo of Bruce Schneier by Joe MacInnis.