Programmeerimiskeeled turvalise ühisarvutuse rakenduste arendamiseks

Turvaline ühisarvutus on tehnoloogia, mis lubab mitmel sõltumatul osapoolel oma andmeid koos töödelda neis olevaid saladusi avalikustamata. Kui andmed on esitatud krüpteeritud kujul, tähendab see, et neid ei dekrüpteerita arvutuse käigus kordagi. Turvalise ühisarvutuse teoreetilised konstruktsioonid on teada olnud juba alates kaheksakümnendatest, kuid esimesed praktilised teostused ja rakendused, mis päris andmeid töötlesid, ilmusid alles natuke enam kui kümme aastat tagasi. Nüüdseks on turvalist ühisarvutust kasutatud mitmes praktilises rakenduses ning sellest on kujunenud oluline andmekaitsetehnoloogia. Turvalise ühisarvutuse rakenduste arendamine on keerukas. Vahendid, mis aitavad kaasa arendusprotsessile, on veel väga uued, ning raamistikud on sageli liiga aeglased praktiliste rakenduste jaoks. Rakendusi on endiselt võimelised arendama ainult krüptograafiaeksperdid. Käesoleva töö eesmärk on teha turvalise ühisarvutuse raamistikke paremaks ning muuta ühisarvutusrakenduste arendamist kergemaks. Väidame, et valdkon- naspetsiifiliste programmeerimiskeelte kasutamine võimaldab turvalise ühisarvu- tuse rakenduste ja raamistike ehitamist, mis on samaaegselt lihtsasti kasutatavad, hea jõudlusega, hooldatavad, usaldusväärsed ja võimelised suuri andmemahtusid töötlema. Peamise tulemusena esitleme kahte uut programmeerimiskeelt, mis on mõeldud turvalise ühisarvutuse jaoks. SecreC 2 on mõeldud turvalise ühisarvutuse rakendus- te arendamise lihtsustamiseks ja aitab kaasa sellele, et rakendused oleks turvalised ja efektiivsed. Teine keel on loodud turvalise ühisarvutuse protokollide arenda- miseks ning selle eesmärk on turvalise ühisarvutuse raamistikke paremaks muuta. Protokollide keel teeb raamistikke kiiremaks ja usaldusväärsemaks ning lihtsustab protokollide arendamist ja haldamist. Kirjeldame mõlemad keeled nii formaalselt kui mitteformaalselt. Näitame, kuidas mitmed rakendused ja prototüübid saavad neist keeltest kasu.Secure multi-party computation is a technology that allows several independent parties to cooperatively process their private data without revealing any secrets. If private inputs are given in encrypted form then the results will also be encrypted, and at no stage during processing are values ever decrypted. As a theoretical concept, the technology has been around since the 1980s, but the first practical implementations arose a bit more than a decade ago. Since then, secure multi-party computation has been used in practical applications, and has been established as an important method of data protection. Developing applications that use secure multi-party computation is challenging. The tools that help with development are still very young and the frameworks are often too slow for practical applications. Currently only experts in cryptography are able to develop secure multi-party applications. In this thesis we look how to improve secure multy-party computation frame- works and make the applications easier to develop. We claim that domain-specific programming languages enable to build secure multi-party applications and frame- works that are at the same time usable, efficient, maintainable, trustworthy, and practically scalable. The contribution of this thesis is the introduction of two new programming languages for secure multi-party computation. The SecreC 2 language makes secure multi-party computation application development easier, ensuring that the applications are secure and enabling them to be efficient. The second language is for developing low-level secure computation protocols. This language was created for improving secure multi-party computation frameworks. It makes the frameworks faster and more trustworthy, and protocols easier to develop and maintain. We give give both a formal and an informal overview of the two languages and see how they benefit multi-party applications and prototypes

Foundations of Software Science and Computation Structures

This open access book constitutes the proceedings of the 23rd International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The 31 regular papers presented in this volume were carefully reviewed and selected from 98 submissions. The papers cover topics such as categorical models and logics; language theory, automata, and games; modal, spatial, and temporal logics; type theory and proof theory; concurrency theory and process calculi; rewriting theory; semantics of programming languages; program analysis, correctness, transformation, and verification; logics of programming; software specification and refinement; models of concurrent, reactive, stochastic, distributed, hybrid, and mobile systems; emerging models of computation; logical aspects of computational complexity; models of software security; and logical foundations of data bases.

Achieving while maintaining:A logic of knowing how with intermediate constraints

In this paper, we propose a ternary knowing how operator to express that the agent knows how to achieve $\phi$ given $\psi$ while maintaining $\chi$ in-between. It generalizes the logic of goal-directed knowing how proposed by Yanjing Wang 2015 'A logic of knowing how'. We give a sound and complete axiomatization of this logic.Comment: appear in Proceedings of ICLA 201

Foundations of Software Science and Computation Structures

This open access book constitutes the proceedings of the 23rd International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The 31 regular papers presented in this volume were carefully reviewed and selected from 98 submissions. The papers cover topics such as categorical models and logics; language theory, automata, and games; modal, spatial, and temporal logics; type theory and proof theory; concurrency theory and process calculi; rewriting theory; semantics of programming languages; program analysis, correctness, transformation, and verification; logics of programming; software specification and refinement; models of concurrent, reactive, stochastic, distributed, hybrid, and mobile systems; emerging models of computation; logical aspects of computational complexity; models of software security; and logical foundations of data bases.

Mechanising an algebraic rely-guarantee refinement calculus

PhD ThesisDespite rely-guarantee (RG) being a well-studied program logic established in the 1980s, it was not until recently that researchers realised that rely and guarantee conditions could be treated as independent programming constructs. This recent reformulation of RG paved the way to algebraic characterisations which have helped to better understand the difficulties that arise in the practical application of this development approach. The primary focus of this thesis is to provide automated tool support for a rely-guarantee refinement calculus proposed by Hayes et. al., where rely and guarantee are defined as independent commands. Our motivation is to investigate the application of an algebraic approach to derive concrete examples using this calculus. In the course of this thesis, we locate and fix a few issues involving the refinement language, its operational semantics and preexisting proofs. Moreover, we extend the refinement calculus of Hayes et. al. to cover indexed parallel composition, non-atomic evaluation of expressions within specifications, and assignment to indexed arrays. These extensions are illustrated via concrete examples. Special attention is given to design decisions that simplify the application of the mechanised theory. For example, we leave part of the design of the expression language on the hands of the user, at the cost of the requiring the user to define the notion of undefinedness for unary and binary operators; and we also formalise a notion of indexed parallelism that is parametric on the type of the indexes, this is done deliberately to simplify the formalisation of algorithms. Additionally, we use stratification to reduce the number of cases in in simulation proofs involving the operational semantics. Finally, we also use the algebra to discuss the role of types in program derivation

Multiplicative latent force models

Latent force models (LFM) are a class of flexible models of dynamic systems, combining a simple mechanistic model with the flexibility of an additive inhomogeneous Gaussian process (GP) forcing term. These hybrid models achieve the dual goal of being flexible enough to be broadly applied, even for complex dynamic systems where a full mechanistic model may be hard to motivate, but by also encoding relevant properties of dynamic systems they are better able to model the underlying dynamics and so demonstrate superior generalisation. In this thesis, we consider an extension of this framework which keeps the same general form, a linear ordinary di↵erential equation with time-varying behaviour arising from a set of smooth GPs, but now we allow for multiplicative interactions between the state variables and the GP terms. The result is a semi-parametric modelling framework that allows for the embedding of rich topological structure. Following a brief review of the latent force model, which we note is a particular case of the GP regression model, we introduce our extension with multiplicative interactions which we refer to as the multiplicative latent force model (MLFM). We demonstrate that this class of models allows for the possibility of strong geometric constraints on the pathwise trajectories. This will enable the modelling of systems for which the GP trajectories of the LFM are unsatisfactory. Unfortunately, and as a direct consequence of the strong geometric constraints we have introduced, it is no longer straightforward to carry out inference in these models; therefore the remainder of this thesis is primarily devoted to constructing two methods for carrying out approximate inference for this class of models. The first is referred to as the Bayesian adaptive gradient matching method, and the second is a novel construction based on the method of successive approximations; a theoretical construct used in the standard classical existence and uniqueness theorems for ODEs. After introducing these methods, we demonstrate their accuracy on simulated data, which also allows for an investigation into the regimes in which each of the respective methods can be expected to perform well. Finally, we demonstrate the utility of the MLFM on motion capture data and show that, by using the framework developed in this thesis to allow for the sharing of a smaller number of latent forces between distinct trajectories with specific geometric constraints, we can achieve superior predictive performance than by the modelling of a single trajectory