Combining behavioural types with security analysis

Today's software systems are highly distributed and interconnected, and they increasingly rely on communication to achieve their goals; due to their societal importance, security and trustworthiness are crucial aspects for the correctness of these systems. Behavioural types, which extend data types by describing also the structured behaviour of programs, are a widely studied approach to the enforcement of correctness properties in communicating systems. This paper offers a unified overview of proposals based on behavioural types which are aimed at the analysis of security properties

Encapsulation and Dynamic Modularity in the Pi-Calculus

We describe a process calculus featuring high level constructs for component-oriented programming in a distributed setting. We propose an extension of the higher-order pi-calculus intended to capture several important mechanisms related to component-based programming, such as dynamic update, reconfiguration and code migration. In this paper, we are primarily concerned with the possibility to build a distributed implementation of our calculus. Accordingly, we define a low-level calculus, that describes how the high-level constructs are implemented, as well as details of the data structures manipulated at runtime. We also discuss current and future directions of research in relation to our analysis of component-based programming

A Typed Model for Linked Data

The term Linked Data is used to describe ubiquitous and emerging semi-structured data formats on the Web. URIs in Linked Data allow diverse data sources to link to each other, forming a Web of Data. A calculus which models concurrent queries and updates over Linked Data is presented. The calculus exhibits operations essential for declaring rich atomic actions. The operations recover emergent structure in the loosely structured Web of Data. The calculus is executable due to its operational semantics. A light type system ensures that URIs with a distinguished role are used consistently. The main theorem verifies that the light type system and operational semantics work at the same level of granularity, so are compatible. Examples show that a range of existing and emerging standards are captured. Data formats include RDF, named graphs and feeds. The primitives of the calculus model SPARQL Query and the Atom Publishing Protocol. The subtype system is based on RDFS, which improves interoperability. Examples focuss on the SPARQL Update proposal for which a fine grained operational semantics is developed. Further potential high level languages are outlined for exploiting Linked Data

Safe Session-Based Concurrency with Shared Linear State

Publisher Copyright: © 2023, The Author(s).We introduce CLASS, a session-typed, higher-order, core language that supports concurrent computation with shared linear state.publishersversionpublishe

An algebraic basis for specifying and enforcing access control in security systems

Security services in a multi-user environment are often based on access control mechanisms. Static aspects of an access control policy can be formalised using abstract algebraic models. We integrate these static aspects into a dynamic framework considering requesting access to resources as a process aiming at the prevention of access control violations when a program is executed. We use another algebraic technique, monads, as a meta-language to integrate access control operations into a functional programming language. The integration of monads and concepts from a denotational model for process algebras provides a framework for programming of access control in security systems

Verifying Information Flow Control Libraries

Information Flow Control (IFC) is a principled approach to protecting the confidentiality and integrity of data in software systems. Intuitively, IFC sys- tems associate data with security labels that track and restrict flows of information throughout a program in order to enforce security. Most IFC techniques require developers to use specific programming languages and tools that require substantial efforts to develop or to adopt. To avoid redundant work and lower the threshold for adopting secure languages, IFC has been embedded in general-purpose languages through software libraries that promote security-by-construction with their API.This thesis makes several contributions to state-of-the-art static (MAC) and dynamic IFC libraries (LIO) in three areas: expressive power, theoretical IFC foundations and protection against covert channels. Firstly, the thesis gives a functor algebraic structure to sensitive data, in a way that it can be processed through classic functional programming patterns that do not incur in security checks. Then, it establishes the formal security guarantees of MAC, using the standard proof technique of term erasure, enriched with two-steps erasure, a novel idea that simplifies reasoning about advanced programming features, such as exceptions, mutable references and concurrency. Secondly, the thesis demonstrates that the lightweight, but coarse-grained, enforcement of dynamic IFC libraries (e.g., LIO) can be as precise and permissive as the fine-grained, but heavyweight, approach of fully-fledged IFC languages. Lastly, the thesis contributes to the design of secure runtime systems that protect IFC libraries, and IFC languages as well, against internal- and external-timing covert channels that leak information through certain runtime system resources and features, such as lazy evaluation and parallelism.The results of this thesis are supported with extensive machine-checked proof scripts, consisting of 12,000 lines of code developed in the Agda proof assistant

Towards Implicit Parallel Programming for Systems

Multi-core processors require a program to be decomposable into independent parts that can execute in parallel in order to scale performance with the number of cores. But parallel programming is hard especially when the program requires state, which many system programs use for optimization, such as for example a cache to reduce disk I/O. Most prevalent parallel programming models do not support a notion of state and require the programmer to synchronize state access manually, i.e., outside the realms of an associated optimizing compiler. This prevents the compiler to introduce parallelism automatically and requires the programmer to optimize the program manually. In this dissertation, we propose a programming language/compiler co-design to provide a new programming model for implicit parallel programming with state and a compiler that can optimize the program for a parallel execution. We define the notion of a stateful function along with their composition and control structures. An example implementation of a highly scalable server shows that stateful functions smoothly integrate into existing programming language concepts, such as object-oriented programming and programming with structs. Our programming model is also highly practical and allows to gradually adapt existing code bases. As a case study, we implemented a new data processing core for the Hadoop Map/Reduce system to overcome existing performance bottlenecks. Our lambda-calculus-based compiler automatically extracts parallelism without changing the program's semantics. We added further domain-specific semantic-preserving transformations that reduce I/O calls for microservice programs. The runtime format of a program is a dataflow graph that can be executed in parallel, performs concurrent I/O and allows for non-blocking live updates

Towards Implicit Parallel Programming for Systems

Multi-core processors require a program to be decomposable into independent parts that can execute in parallel in order to scale performance with the number of cores. But parallel programming is hard especially when the program requires state, which many system programs use for optimization, such as for example a cache to reduce disk I/O. Most prevalent parallel programming models do not support a notion of state and require the programmer to synchronize state access manually, i.e., outside the realms of an associated optimizing compiler. This prevents the compiler to introduce parallelism automatically and requires the programmer to optimize the program manually. In this dissertation, we propose a programming language/compiler co-design to provide a new programming model for implicit parallel programming with state and a compiler that can optimize the program for a parallel execution. We define the notion of a stateful function along with their composition and control structures. An example implementation of a highly scalable server shows that stateful functions smoothly integrate into existing programming language concepts, such as object-oriented programming and programming with structs. Our programming model is also highly practical and allows to gradually adapt existing code bases. As a case study, we implemented a new data processing core for the Hadoop Map/Reduce system to overcome existing performance bottlenecks. Our lambda-calculus-based compiler automatically extracts parallelism without changing the program's semantics. We added further domain-specific semantic-preserving transformations that reduce I/O calls for microservice programs. The runtime format of a program is a dataflow graph that can be executed in parallel, performs concurrent I/O and allows for non-blocking live updates