Deriving Safety Cases for the Formal Safety Certification of Automatically Generated Code

We present an approach to systematically derive safety cases for automatically generated code from information collected during a formal, Hoare-style safety certification of the code. This safety case makes explicit the formal and informal reasoning principles, and reveals the top-level assumptions and external dependencies that must be taken into account; however, the evidence still comes from the formal safety proofs. It uses a generic goal-based argument that is instantiated with respect to the certified safety property (i.e., safety claims) and the program. This will be combined with a complementary safety case that argues the safety of the framework itself, in particular the correctness of the Hoare rules with respect to the safety property and the trustworthiness of the certification system and its individual components

Type Inference for Deadlock Detection in a Multithreaded Polymorphic Typed Assembly Language

We previously developed a polymorphic type system and a type checker for a multithreaded lock-based polymorphic typed assembly language (MIL) that ensures that well-typed programs do not encounter race conditions. This paper extends such work by taking into consideration deadlocks. The extended type system verifies that locks are acquired in the proper order. Towards this end we require a language with annotations that specify the locking order. Rather than asking the programmer (or the compiler's backend) to specifically annotate each newly introduced lock, we present an algorithm to infer the annotations. The result is a type checker whose input language is non-decorated as before, but that further checks that programs are exempt from deadlocks

Blazes: Coordination Analysis for Distributed Programs

Distributed consistency is perhaps the most discussed topic in distributed systems today. Coordination protocols can ensure consistency, but in practice they cause undesirable performance unless used judiciously. Scalable distributed architectures avoid coordination whenever possible, but under-coordinated systems can exhibit behavioral anomalies under fault, which are often extremely difficult to debug. This raises significant challenges for distributed system architects and developers. In this paper we present Blazes, a cross-platform program analysis framework that (a) identifies program locations that require coordination to ensure consistent executions, and (b) automatically synthesizes application-specific coordination code that can significantly outperform general-purpose techniques. We present two case studies, one using annotated programs in the Twitter Storm system, and another using the Bloom declarative language.Comment: Updated to include additional materials from the original technical report: derivation rules, output stream label

A Non-Null Annotation Inferencer for Java Bytecode

We present a non-null annotations inferencer for the Java bytecode language. We previously proposed an analysis to infer non-null annotations and proved it soundness and completeness with respect to a state of the art type system. This paper proposes extensions to our former analysis in order to deal with the Java bytecode language. We have implemented both analyses and compared their behaviour on several benchmarks. The results show a substantial improvement in the precision and, despite being a whole-program analysis, production applications can be analyzed within minutes

Securing Databases from Probabilistic Inference

Databases can leak confidential information when users combine query results with probabilistic data dependencies and prior knowledge. Current research offers mechanisms that either handle a limited class of dependencies or lack tractable enforcement algorithms. We propose a foundation for Database Inference Control based on ProbLog, a probabilistic logic programming language. We leverage this foundation to develop Angerona, a provably secure enforcement mechanism that prevents information leakage in the presence of probabilistic dependencies. We then provide a tractable inference algorithm for a practically relevant fragment of ProbLog. We empirically evaluate Angerona's performance showing that it scales to relevant security-critical problems.Comment: A short version of this paper has been accepted at the 30th IEEE Computer Security Foundations Symposium (CSF 2017