Aslan Askarov

Tight Enforcement of Information-Release Policies for Dynamic Languages

This paper studies the problem of securing information release in dynamic languages. We propose (i) an intuitive framework for information-release policies expressing both what can be released by an application and where in the code this release may take place and (ii) tight and modular enforcement by hybrid mechanisms that combine monitoring with on-the-fly static analysis for a language with dynamic code evaluation and communication primitives. The policy framework and enforcement mechanisms support both termination-sensitive and insensitive security policies.

Gradual Release: Unifying Declassification, Encryption and Key Release Policies

Information security has a challenge to address: enabling information-flow controls with expressive information release (or declassification) policies. Existing approaches tend to address some aspects of information release, exposing the other aspects for possible attacks. It is striking that these approaches fall into two mostly separate categories: revelation-based (as in information purchase, aggregate computation, moves in a game, etc.) and encryption-based declassification (as in sending encrypted secrets over an untrusted network, storing passwords, etc.). This paper introduces gradual release, a policy that unifies declassification, encryption, and key release policies. We model an attackers knowledge by the sets of possible secret inputs as functions of publicly observable outputs. The essence of gradual release is that this knowledge must remain constant between releases. Gradual release turns out to be a powerful foundation for release policies, which we demonstrate by formally connecting revelation-based and encryption-based declassification. Furthermore, we show that gradual release can be provably enforced by security types and effects.

Predictive black-box mitigation of timing channels

We investigate techniques for general black-box mitigation of timing channels. The source of events is wrapped by a timing mitigator that delays output events so that they contain only a bounded amount of information. We introduce a general class of timing mitigators that can achieve any given bound on timing channel leakage, with a tradeoff in system performance. We show these mitigators compose well with other mechanisms for information flow control, and demonstrate they are effective against some known timing attacks.

Predictive mitigation of timing channels in interactive systems

Timing channels remain a difficult and important problem for information security. Recent work introduced predictive mitigation, a new way to mitigating leakage through timing channels; this mechanism works by predicting timing from past behavior, and then enforcing the predictions. This paper generalizes predictive mitigation to a larger and important class of systems: systems that receive input requests from multiple clients and deliver responses. The new insight is that timing predictions may be a function of any public information, rather than being a function simply of output events. Based on this insight, a more general mechanism and theory of predictive mitigation becomes possible. The result is that bounds on timing leakage can be tightened, achieving asymptotically logarithmic leakage under reasonable assumptions. By applying it to web applications, the generalized predictive mitigation mechanism is shown to be effective in practice.

A lattice-based approach to mashup security

A web mashup is a web application that integrates content from different providers to create a new service, not offered by the content providers. As mashups grow in popularity, the problem of securing information flow between mashup components becomes increasingly important. This paper presents a security lattice-based approach to mashup security, where the origins of the different components of the mashup are used as levels in the security lattice. Declassification allows controlled information release between the components. We formalize a notion of composite delimited release policy and provide considerations for practical (static as well as runtime) enforcement of mashup information-flow security policies in a web browser.

Security-typed languages for implementation of cryptographic protocols: a case study

Security protocols are critical for protecting modern communication infrastructures and are therefore subject to thorough analysis. However practical implementations of these protocols lack the same level of attention and thus may be more exposed to attacks. This paper discusses security assurance provided by security-typed languages when implementing cryptographic protocols. Our results are based on a case study using Jif, a Java-based security-typed language, for implementing a non-trivial cryptographic protocol that allows playing online poker without a trusted third party. The case study deploys the largest program written in a security-typed language to date and identifies insights ranging from security guarantees to useful patterns of secure programming.

Sharing Mobile Code Securely with Information Flow Control

Mobile code is now a nearly inescapable component of modern computing, thanks to client-side code that runs within web browsers. The usual tension between security and functionality is particularly acute in a mobile-code setting, and current platforms disappoint on both dimensions. We introduce a new architecture for secure mobile code, with which developers can use, publish, and share mobile code securely across trust domains. This architecture enables new kinds of distributed applications, and makes it easier to reuse and evolve code from untrusted providers. The architecture gives mobile code considerable expressive power: it can securely access distributed, persistent, shared information from multiple trust domains, unlike web applications bound by the same-origin policy. The core of our approach is analyzing how flows of information within mobile code affect confidentiality and integrity. Because mobile code is untrusted, this analysis requires novel constraints on information flow and authority. We show that these constraints offer principled enforcement of strong security while avoiding the limitations of current mobile-code security mechanisms. We evaluate our approach by demonstrating a variety of mobile-code applications, showing that new functionality can be offered along with strong security.

A semantic framework for declassification and endorsement

Language-based information flow methods offer a principled way to enforce strong security properties, but enforcing noninterference is too inflexible for realistic applications. Security-typed languages have therefore introduced declassification mechanisms for relaxing confidentiality policies, and endorsement mechanisms for relaxing integrity policies. However, a continuing challenge has been to define what security is guaranteed when such mechanisms are used. This paper presents a new semantic framework for expressing security policies for declassification and endorsement in a language-based setting. The key insight is that security can be described in terms of the power that declassification and endorsement give the attacker. The new framework specifies how attacker controlled code affects program execution and what the attacker is able to learn from observable effects of this code. This approach yields novel security conditions for checked endorsements and robust integrity. The framework is flexible enough to recover and to improve on the previously introduced notions of robustness and qualified robustness. Further, the new security conditions can be soundly enforced by a security type system. The applicability and enforcement of the new policies is illustrated through various examples, including data sanitization and authentication.

Cryptographically-masked flows

Cryptographic operations are essential for many security-critical systems. Reasoning about information flow in such systems is challenging because typical (noninterference-based) information-flow definitions allow no flow from secret to public data. Unfortunately, this implies that programs with encryption are ruled out because encrypted output depends on secret inputs: the plaintext and the key. However, it is desirable to allow flows arising from encryption with secret keys provided that the underlying cryptographic algorithm is strong enough. In this article we conservatively extend the noninterference definition to allow safe encryption, decryption, and key generation. To illustrate the usefulness of this approach, we propose (and implement) a type system that guarantees noninterference for a small imperative language with primitive cryptographic operations. The type system prevents dangerous program behavior (e.g., giving away a secret key or confusing keys and nonkeys), which we exemplify with secure implementations of cryptographic protocols. Because the model is based on a standard noninterference property, it allows us to develop some natural extensions. In particular, we consider public-key cryptography and integrity, which accommodate reasoning about primitives that are vulnerable to chosen-ciphertext attacks.

Learning is Change in Knowledge: Knowledge-Based Security for Dynamic Policies

In systems that handle confidential information, the security policy to enforce on information frequently changes: new users join the system, old users leave, and sensitivity of data changes over time. It is challenging, yet important, to specify what it means for such systems to be secure, and to gain assurance that a system is secure. We present a language-based model for specifying, reasoning about, and enforcing information security in systems that dynamically change the security policy. We specify security for such systems as a simple and intuitive extensional knowledge-based semantic condition: an attacker can only learn information in accordance with the current security policy. Importantly, the semantic condition is parameterized by the ability of the attacker. Learning is about change in knowledge, and an observation that allows one attacker to learn confidential information may provide a different attacker with no new information. A program that is secure against an attacker with perfect recall may not be secure against a more realistic, weaker, attacker. We introduce a compositional model of attackers that simplifies enforcement of security, and demonstrate that standard information-flow control mechanisms, such as security-type systems and information-flow monitors, can be easily adapted to enforce security for a broad and useful class of attackers.