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Chapter: Security in Computing : Designing Trusted Operating Systems

Models of Security

In security and elsewhere, models are often used to describe, study, or analyze a particular situation or relationship. McLean [MCL90a] gives a good overview of models for security. In particular, security models are used to · test a particular policy for completeness and consistency · document a policy · help conceptualize and design an implementation · check whether an implementation meets its requirements

Models of Security


In security and elsewhere, models are often used to describe, study, or analyze a particular situation or relationship. McLean [MCL90a] gives a good overview of models for security. In particular, security models are used to


·      test a particular policy for completeness and consistency


·      document a policy


·     help conceptualize and design an implementation


·     check whether an implementation meets its requirements


We assume that some access control policy dictates whether a given user can access a particular object. We also assume that this policy is established outside any model. That is, a policy decision determines whether a specific user should have access to a specific object; the model is only a mechanism that enforces that policy. Thus, we begin studying models by considering simple ways to control access by one user.


Multilevel Security


Ideally, we want to build a model to represent a range of sensitivities and to reflect the need to separate subjects rigorously from objects to which they should not have access. For instance, consider an election and the sensitivity of data involved in the voting process. The names of the candidates are probably not sensitive. If the results have not yet been released, the name of the winner is somewhat sensitive. If one candidate received an embarrassingly low number of votes, the vote count may be more sensitive. Finally, the way a particular individual voted is extremely sensitive. Users can also be ranked by the degree of sensitivity of information to which they can have access.


For obvious reasons, the military has developed extensive procedures for securing information. A generalization of the military model of information security has also been adopted as a model of data security within an operating system. Bell and La Padula [BEL73] were first to describe the properties of the military model in mathematical notation, and Denning [DEN76a] first formalized the structure of this model. In 2005, Bell [BEL05] returned to the original model to highlight its contribution to computer security. He observed that the model demonstrated the need to understand security requirements before beginning system design, build security into not onto the system, develop a security toolbox, and design the system to protect itself. The generalized model is called the lattice model of security because its elements form a mathematical structure called a lattice. (See Sidebar 5-1.) In this section, we describe the military example and then use it to explain the lattice model.


Lattice Model of Access Security


Many other structures are lattices. For example, we noted earlier that a commercial security policy may contain data sensitivities such as public, proprietary, and internal, with the natural ordering that public data are less sensitive than proprietary, which are less sensitive than internal. These three levels also form a lattice.


Security specialists have chosen to base security systems on a lattice because it naturally represents increasing degrees. A security system designed to implement lattice models can be used in a military environment. However, it can also be used in commercial environments with different labels for the degrees of sensitivity. Thus, lattice representation of sensitivity levels applies to many computing situations.



BellLa Padula Confidentiality Model


The Bell and La Padula model [BEL73] is a formal description of the allowable paths of information flow in a secure system. The model's goal is to identify allowable communication when maintaining secrecy is important. The model has been used to define security requirements for systems concurrently handling data at different sensitivity levels. This model is a formalization of the military security policy and was central to the U.S. Department of Defense's evaluation criteria, described later in this chapter.


We are interested in secure information flows because they describe acceptable connections between subjects and objects of different levels of sensitivity. One purpose for security-level analysis is to enable us to construct systems that can perform concurrent computation on data at two different sensitivity levels. For example, we may want to use one machine for top-secret and confidential data at the same time. The programs processing top-secret data would be prevented from leaking top-secret data to the confidential data, and the confidential users would be prevented from accessing the top-secret data. Thus, the BellLa Padula model is useful as the basis for the design of systems that handle data of multiple sensitivities.



In the military model, this property says that the contents of a sensitive object can be written only to objects at least as high.


In the military model, one interpretation of the *-property is that a person obtaining information at one level may pass that information along only to people at levels no lower than the level of the information. The *-property prevents write-down, which occurs when a subject with access to high-level data transfers that data by writing it to a low-level object.


Literally, the *-property requires that a person receiving information at one level not talk with people cleared at levels lower than the level of the informationnot even about the weather! This example points out that this property is stronger than necessary to ensure security; the same is also true in computing systems. The BellLa Padula model is extremely conservative: It ensures security even at the expense of usability or other properties.


The implications of these two properties are shown in Figure 5 -7. The classifications of subjects (represented by squares) and objects (represented by circles) are indicated by their positions: As the classification of an item increases, it is shown higher in the figure. The flow of information is generally horizontal (to and from the same level) and upward (from lower levels to higher). A downward flow is acceptable only if the highly cleared subject does not pass any high-sensitivity data to the lower-sensitivity object.


For computing systems, downward flow of information is difficult because a computer program cannot readily distinguish between having read a piece of information and having read a piece of information that influenced what was later written. (McLean [MCL90b], in work related to Goguen and Meseguer [GOG82], presents an interesting counter to the *-property of Bell and La Padula. He suggests considering noninterference, which can be loosely described as tracing the effects of inputs on outputs. If we can trace all output effects, we can determine conclusively whether a particular low-level output was "contaminated" with high-level input.)


Biba Integrity Model


The BellLa Padula model applies only to secrecy of information: The model identifies paths that could lead to inappropriate disclosure of information. However, the integrity of data is important, too. Biba [BIB77] constructed a model for preventing inappropriate modification of data.


The Biba model is the counterpart (sometimes called the dual) of the BellLa Padula model. Biba defines "integrity levels," which are analogous to the sensitivity levels of the BellLa Padula model. 

These two rules cover untrustworthy information in a natural way. Suppose John is known to be untruthful sometimes. If John can create or modify a document, other people should distrust the truth of the statements in that document. Thus, an untrusted subject who has write access to an object reduces the integrity of that object. Similarly, people are rightly skeptical of a report based on unsound evidence. The low integrity of a source object implies low integrity for any object based on the source object.


This model addresses the integrity issue that the BellLa Padula model ignores. However, in doing so, the Biba model ignores secrecy. Secrecy-based security systems have been much more fully studied than have integrity-based systems. The current trend is to join secrecy and integrity concerns in security systems, although no widely accepted formal models achieve this compromise.


Models Proving Theoretical Limitations of Security Systems


Models are also useful for demonstrating the feasibility of an approach. Consider the security properties that we want a system to have. We want to build a model that tells us (before we invest in design, code, and testing) whether the properties can actually be achieved. This new class of models is based on the general theory of computability, which you may have studied in your computer science classes.

Computability helps us determine decidability: If we pose a question, we want to know if we will ever be able to decide what the answer is. The results of these computability-based models show us the limitations of abstract security systems.


GrahamDenning Model


Lampson [LAM71] and Graham and Denning [GRA72] introduced the concept of a formal system of protection rules. Graham and Denning constructed a model having generic protection properties. This model forms the basis for two later models of security systems.


The GrahamDenning model operates on a set of subjects S, a set of objects O, a set of rights R, and an access control matrix A. The matrix has one row for each subject and one column for each subject and each object. The rights of a subject on another subject or an object are shown by the contents of an element of the matrix. For each object, one subject designated the "owner" has special rights; for each subject, another subject designated the "controller" has special rights.


The GrahamDenning model has eight primitive protection rights. These rights are phrased as commands that can be issued by subjects, with effects on other subjects or objects.


  Create object allows the commanding subject to introduce a new object to the system.


  Create subject, delete object, and delete subject have the similar effect of creating or destroying a subject or object.


Read access right allows a subject to determine the current access rights of a subject to an object.

  Grant access right allows the owner of an object to convey any access rights for an object to another subject.


  Delete access right allows a subject to delete a right of another subject for an object, provided that the deleting subject either is the owner of the object or controls the subject from which access should be deleted.


  Transfer access right allows a subject to transfer one of its rights for an object to another subject. Each right can be transferable or nontransferable. If a subject receives a transferable right, the subject can then transfer that right (either transferable or not) to other subjects. If a subject receives a nontransferable right, it can use the right but cannot transfer that right to other subjects.


These rules are shown in Table 5-2 (for more details see [GRA72] ), which shows prerequisite conditions for executing each command and its effect. The access control matrix is A [s,o], where s is a subject and o is an object. The subject executing each command is denoted x. A transferable right is denoted r*; a nontransferable right is written r.



This set of rules provides the properties necessary to model the access control mechanisms of a protection system. For example, this mechanism can represent a reference monitor or a system of sharing between two untrustworthy, mutually suspicious subsystems.


HarrisonRuzzoUllman Results


Harrison, Ruzzo, and Ullman [HAR76] proposed a variation on the GrahamDenning model. This revised model answered several questions concerning the kinds of protection a given system can offer. Suppose you are about to use a particular operating system and you want to know if a given user can ever be granted a certain kind of access. For example, you may be establishing protection levels in Windows or MVS. You set up the access controls and then ask whether user X will ever have access to object Y. The three researchers developed their model so that we might be able to answer questions like this one.


The HarrisonRuzzoUllman model (called the HRU model) is based on commands, where each command involves conditions and primitive operations. The structure of a command is as follows.


This command is structured like a procedure, with parameters o1 through ok. The notation of the HRU model is slightly different from the

GrahamDenning model; in HRU every subject is an object, too. Thus, the columns of the access control matrix are all the subjects and all the objects that are not subjects. For this reason, all the parameters of a command are labeled o, although they could be either subjects or nonsubject objects. Each r is a generic right, as in the GrahamDenning model. Each op is a primitive operation, defined in the following list. The access matrix is shown in Table 5-3.


The primitive operations op, similar to those of the GrahamDenning model, are as follows:


·      create subject s


·      create object o


·      destroy subject s


·      destroy object o


·      enter right r into A[s,o]


·      delete right r from A[s,o]


The interpretations of these operations are what their names imply. A protection system is a set of subjects, objects, rights, and commands.


Harrison et al. demonstrate that these operations are adequate to model several examples of protection systems, including the Unix protection mechanism and an indirect access mode introduced by Graham and Denning [GRA72]. Thus, like the GrahamDenning model, the HRU model can represent "reasonable" interpretations of protection.


Two important results derived by Harrison et al. have major implications for designers of protection systems. We omit the complete proofs of these results, but we outline them in Sidebar 5-2 to give you an idea of what is involved.


The first result from HRU indicates that


In the modeled system, in which commands are restricted to a single operation each, it is possible to decide whether a given subject can ever obtain a particular right to an object.


Therefore, we can decide (that is, we can know in advance) whether a low-level subject can ever obtain read access to a high-level object, for example.


The second result is less encouraging. Harrison et al. show that


If commands are not restricted to one operation each, it is not always decidable whether a given protection system can confer a given right.


Thus, we cannot determine in general whether a subject can obtain a particular right to an object.


As an example, consider protection in the Unix operating system. The Unix protection scheme is relatively simple; other protection systems are more complex. Because the Unix protection scheme requires more than one operation per command in the HRU model, there can be no general procedure to determine whether a certain access right can be given to a subject.


The HRU result is important but bleak. In fact, the HRU result can be extended. There may be an algorithm to decide the access right question for a particular collection of protection systems, but even an infinite number of algorithms cannot decide the access right question for all protection systems. However, the negative results do not say that no decision process exists for any protection system. In fact, for certain specific protection systems, it is decidable whether a given access right can be conferred.


Sidebar 5-2: Proving the HRU Results


The first HRU result applies when commands are restricted to containing just one operation each. In this case, it is possible to decide whether a given protection system, started with a given initial configuration of the access control matrix, can allow a given user a given access right to a given object. In other words, suppose you want to know whether a particular protection system can allow a subject s to obtain access right r to object o. (Harrison et al. say that such a system leaks the access right.)


As long as each command consists of only a single operation, there is an algorithm that can answer this question. The proof involves analyzing the minimum number of commands by which a right can be conferred. Certain operations, such as delete and destroy, have no effect on expanding access rights; they can be ignored. The shortest sequence of commands by which such a right can be conferred contains at most m = | r | * ( |s|+1) *( |o|+1) + 1 commands, where | r | is the number of rights, |s| is the number of subjects, and |o| is the number of objects in the protection system. The algorithm


calls for testing all sequences of commands of length up to m. (There are 2km such sequences, for some constant k.) If the right is conferred, it will be in one of the sequences.


The proof of the second HRU result uses commands of an HRU protection system to represent operations of a formal system called a Turing machine. Turing machines are general models of computing devices, expressed as a machine reading a tape that has a string of zeros and ones. The decidability problems we want to solve are often framed so that the result we seek is true if we can decide whether the Turing machine will ever halt when reading commands from the tape. Any conventional computing system and program can be modeled with a Turing machine. Several decidable results about Turing machines are well known, including one that shows it is impossible to develop a general procedure to determine whether a given Turing machine will halt when performing a given computation. The proof of the second HRU result follows by the demonstration that a decision procedure for protection systems would also solve the halting problem for Turing machines, which is known to be unsolvable.



Therefore, the HRU results are negative for general procedures but do not rule out the possibility of making decisions about particular protection systems.


TakeGrant Systems


One final model of a protection system is the takegrant system, introduced by Jones [JON78a] and expanded by Lipton and Snyder [LIP77, SNY81].


This model has only four primitive operations: create, revoke, take, and grant. Create and revoke are similar to operations from the GrahamDenning and HRU models; take and grant are new types of operations. These operations are presented most naturally through the use of graphs.


As in other systems, let S be a set of subjects and O be a set of objects; objects can be either active (subjects) or passive (nonsubject objects). Let R be a set of rights. Each subject or object is denoted by a node of a graph; the rights of a particular subject to a particular object are denoted by a labeled, directed edge from the subject to the object. Figure 5-8 shows an example of subject, object, and rights.

Let s be the subject performing each of the operations. The four operations are defined as follows. The effects of these operations are shown in Figure 5-9.



Snyder shows that in this system certain protection questions are decidable; furthermore, they are decidable in reasonable (less than  exponential) time. In [SNY81], Snyder considers two questions: 

1. Can we decide whether a given subject can share an object with another subject?   

2 .              Can we decide whether a given subject can steal access to an object from another subject?


Clearly, these are important questions to answer about a protection system, for they show whether the access control mechanisms are secure against unauthorized disclosure.


The answer to Snyder's first question is yes. Sharing can occur only if several other subjects together have the desired access to the object and the first subject is connected to each of the group of other subjects by a path of edges having a particular form. An algorithm that detects sharability runs in time proportional to the size of the graph of the particular case.


Snyder also answers the second question affirmatively, in a situation heavily dependent on the ability to share. Thus, an algorithm can decide whether access can be stolen by direct appeal to the algorithm to decide sharability.


Landwehr [LAN81] points out that the takegrant model assumes the worst about users: If a user can grant access rights, the model assumes that the user will. Suppose a user can create a file and grant access to it to everyone. In that situation, every user could allow access to every object by every other user. This worst-case assumption limits the applicability of the model to situations of controlled sharing of information. In general, however, the takegrant model is useful because it identifies conditions under which a user can obtain access to an object.


Summary of Models of Protection Systems


We study models of computer security for two reasons. First, models are important in determining the policies a secure system should enforce. For example, the BellLa Padula and Biba models identify specific conditions we must enforce so that we can ensure secrecy or integrity. Second, the study of abstract models can lead to an understanding of the properties of protection systems. For example, the HRU model states certain characteristics that can or cannot be decided by an arbitrary protection system. These characteristics are important for designers of protection systems to know.


Building and analyzing models are essential to designing a trusted operating system. We use models of protection systems to establish our security policies, determining what is feasible and desirable from what is not. From the policies we move to the operating system design itself. In the next section, we look closely at trusted operating system design.

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