Lazy Programs Leak Secrets

To preserve confidentiality, information-flow control (IFC) restricts how untrusted code handles secret data. While promising, IFC systems are not perfect; they can still leak sensitive information via covert channels. In this work, we describe a novel exploit of lazy evaluation to reveal secrets in IFC systems. Specifically, we show that lazy evaluation might transport information through the internal timing covert channel, a channel present in systems with concurrency and shared resources. We illustrate our claim with an attack for LIO, a concurrent IFC system for Haskell. We propose a countermeasure based on restricting the implicit sharing caused by lazy evaluation

A conference management system with verified document confidentiality

We present a case study in verified security for realistic systems: the implementation of a conference management system, whose functional kernel is faithfully represented in the Isabelle theorem prover, where we specify and verify confidentiality properties. The various theoretical and practical challenges posed by this development led to a novel security model and verification method generally applicable to systems describable as input–output automata

A Risk Management Approach to the “Insider Threat”

Recent surveys indicate that the financial impact and operating losses due to insider intrusions are increasing. But these studies often disagree on what constitutes an "insider;" indeed, many define it only implicitly. In theory, appropriate selection of, and enforcement of, properly specified security policies should prevent legitimate users from abusing their access to computer systems, information, and other resources. However, even if policies could be expressed precisely, the natural mapping between the natural language expression of a security policy, and the expression of that policy in a form that can be implemented on a computer system or network, creates gaps in enforcement. This paper defines "insider" precisely, in terms of these gaps, and explores an access-based model for analyzing threats that include those usually termed "insider threats." This model enables an organization to order its resources based on the business value for that resource and of the information it contains. By identifying those users with access to high-value resources, we obtain an ordered list of users who can cause the greatest amount of damage. Concurrently with this, we examine psychological indicators in order to determine which users are at the greatest risk of acting inappropriately. We conclude by examining how to merge this model with one of forensic logging and auditing