Rights management Vicky Weissman

Policies A policy is a set of a conditions under which an action is permitted or forbidden. Simple examples: CS 502 students cannot edit the course website. A student can only modify a course web page with the instructor’s permission. More complicated examples: To borrow a book from the library, you must have a library card and you must either bring the book back in 2 weeks or pay a fine. A license is a type of policy; it says what a client needs to do to access a resource legitimately.

Goals Write policies unambiguously. Reason about the policies in a provably correct way. Is a particular action such as Alice editing the CS 502 web site allowed? Forbidden? Are the policies consistent? In other words,do they allow and forbid the same action? Enforce the policies in a provably correct way. We want to: A policy is a set of a conditions under which an action is permitted or forbidden.

Writing unambiguous policies Policies written in natural languages, like English, are often ambiguous. Ex: A student can only modify a course web page with the instructor’s permission.

Writing unambiguous policies Policies written in natural languages, like English, are often ambiguous. Ex: A student can only modify a course web page with the instructor’s permission. If the student has the instructor’s permission, can the student edit the page?

Writing unambiguous policies Policies written in natural languages, like English, are often ambiguous. Ex: A student can only modify a course web page with the instructor’s permission. If the student has the instructor’s permission, can the student edit the page? Does the policy apply to courses with multiple instructors? If so, whose permission do you need?

Isn’t this an old problem? Well, yes. But policies for digital objects can be more complex. Consider a library patron borrowing a book If it’s a digital object, pictures can be blurred or hidden, according to a policy agreement. Certain portions of the text can be blocked out. If it’s a physical book, the library either needs a copy for each type of policy or can only regulate who sees the book as a single unit.

Automatic enforcement Digital works typically are protected by automatic means (e.g. software), so there’s no person we can trust. We can tell a librarian what the policies are and, if we haven’t considered a scenario, then the librarian can ‘do something reasonable’. If a computer program gets input that it wasn’t expecting, what’s the likelihood that it will do something reasonable?

Bottom line We want to state, reason, and enforce policies. The policies we’re interested in are more complex than we’ve had before. The standard solution of relying on a trusted person to ‘act reasonably’ is no longer an option.

Current solutions in industry Make policies VERY simple. For example, digital libraries often only have digital objects that are in the public domain. Alternatively, many libraries only differentiate between subscribers and non- subscribers. Use a commercial right’s language (eg. XrML, ODRL, …).

XrML Looks like HTML. Has tons of predefined tags like: Allows people to make new tags for their specific needs.

Benefits of using XrML Popular. Policy makers don’t have to learn too much ‘new lingo’ when going from app to app. Allows common enforcement mechanisms across apps. Fairly easy to use. Extremely flexible.

Disadvantages of XrML No formal semantics. Semantics tell us what the symbols in a language mean. The only meaning I’ve found given to the predefined tags are in English – which we’ve already argued is ambiguous. If we don’t have unambiguous semantics, then we cannot hope to reason about policies or enforce them in a provably correct way. People who use XrML are writing policies that ‘seem right’ without anyone knowing precisely what is intended or exactly what is allowed.

Other options- use logic Policies can be expressed in first-order logic. Example: students cannot edit the website  i (student(i) => ¬Permitted(i, edit website))

Pros and Cons of using logic Benefits Well-understood. Extremely flexible. Has formal semantics. Disadvantages Not user-friendly -> needs intuitive GUI. Most interesting questions are provably undecidable -> need to find a fragment of first-order logic that is expressive and tractable. Semantics tell us what the symbols in a language mean.

Another option: Regular expressions Policies are captured by automatons. Start State give CUID use photocopier give acct # pay fee Above automaton says the photocopier can be used by anyone whose paid the fee or has given both a CUID and an acct number.

Pros and cons of reg. expr. Pros Well-understood. Easy to give formal semantics. Easy to reason about. Cons Not as expressive as first-order logic. Not as user-friendly as natural languages or commercial rights languages like XrML. Semantics tell us what the symbols in a language mean.

Reasoning about policies for policies written in any language without formal semantics – this includes natural languages like English, XrML, ODRL – reasoning requires a judge for policies written as regular expressions – reasoning strategy depends on the chosen formal semantics.

Reasoning about policies in first-order logic Can Alice edit 502 web site? Given: policies p 1, …, p n (written in fol) and facts about the world E (e.g. Senior(Alice)  (  i (Senior(i) => Student(i)))  …) Alice can edit if: E  p 1  …  p n => Permitted(Alice, edit 502 site) is valid (i.e. if E and all the policies hold, then Alice may edit the site, regardless of any other policies and facts).

Enforcement There are lots of mechanisms to enforce policies. For an overview, take Prof. Schneider’s CS 513: System Security course or read the course’s notes. One interesting mechanism that is particularly well-suited to digital objects is in-line reference monitors (IRM).

IRM idea Suppose you wanted to write a code fragment A that could only be executed by students. You could write: if (student) {A} But if you did this, then the policy and ‘real code’ are mushed together so its hard to see what either is doing and it’s hard to modify either component (e.g. change ‘students’ to ‘students and faculty’). The IRM idea is to write and maintain the policy and code separately. Immediately before execution, the IRM monitor interleaves them.

Conclusion Policies are becoming increasingly complex and the solution in the physical world doesn’t translate to cyberspace. There are a lot of ways to write policies, but none is a clear winner. Need formal semantics if you’re going to reason and/or enforce policies in a provably correct way. Formal semantics may not be enough to do this. There are a ton of open questions, got research?