A Static Verification Framework for Secure Peer-to-Peer Applications

In this paper we present a static verification framework to support the design and verification of secure peer-to-peer applications. The framework supports the specification, modeling, and analysis of security aspects together with the general characteristics of the system, during early stages of the development life-cycle. The approach avoids security issues to be taken into consideration as a separate layer that is added to the system as an afterthought by the use of security protocols. The main functionality supported by the framework are concerned with the modeling of the system together with its security aspects by using an extension of UML, modeling of abuse cases to represent scenarios of attackers and assist with the identification of properties to be verified, specification of properties to be verified in a graphical template language, verification of the models against the properties, and visualization of the results of the verification process

Quantitative Verification: Formal Guarantees for Timeliness, Reliability and Performance

Computerised systems appear in almost all aspects of our daily lives, often in safety-critical scenarios such as embedded control systems in cars and aircraft or medical devices such as pacemakers and sensors. We are thus increasingly reliant on these systems working correctly, despite often operating in unpredictable or unreliable environments. Designers of such devices need ways to guarantee that they will operate in a reliable and efficient manner. Quantitative verification is a technique for analysing quantitative aspects of a system's design, such as timeliness, reliability or performance. It applies formal methods, based on a rigorous analysis of a mathematical model of the system, to automatically prove certain precisely specified properties, e.g. ``the airbag will always deploy within 20 milliseconds after a crash'' or ``the probability of both sensors failing simultaneously is less than 0.001''. The ability to formally guarantee quantitative properties of this kind is beneficial across a wide range of application domains. For example, in safety-critical systems, it may be essential to establish credible bounds on the probability with which certain failures or combinations of failures can occur. In embedded control systems, it is often important to comply with strict constraints on timing or resources. More generally, being able to derive guarantees on precisely specified levels of performance or efficiency is a valuable tool in the design of, for example, wireless networking protocols, robotic systems or power management algorithms, to name but a few. This report gives a short introduction to quantitative verification, focusing in particular on a widely used technique called model checking, and its generalisation to the analysis of quantitative aspects of a system such as timing, probabilistic behaviour or resource usage. The intended audience is industrial designers and developers of systems such as those highlighted above who could benefit from the application of quantitative verification,but lack expertise in formal verification or modelling

ADsafety: Type-Based Verification of JavaScript Sandboxing

Web sites routinely incorporate JavaScript programs from several sources into a single page. These sources must be protected from one another, which requires robust sandboxing. The many entry-points of sandboxes and the subtleties of JavaScript demand robust verification of the actual sandbox source. We use a novel type system for JavaScript to encode and verify sandboxing properties. The resulting verifier is lightweight and efficient, and operates on actual source. We demonstrate the effectiveness of our technique by applying it to ADsafe, which revealed several bugs and other weaknesses.Comment: in Proceedings of the USENIX Security Symposium (2011

Property specification and static verification of UML models

We present a static verification tool (SVT), a system that performs static verification on UML models composed of UML class and state machine diagrams. Additionally, the SVT allows the user to add extra behavior specification in the form of guards and effects by defining a small action language. UML models are checked against properties written in a special-purpose property language that allows the user to specify linear temporal logic formulas that explicitly reason about UML components. Thus, the SVT provides a strong foundation for the design of reliable systems and a step towards model-driven security