Virus-induced type I interferons (IFN) have classically been considered to constitute the first line of defense against virus infections However, recent work by us and others has identified early antiviral actions that occur independently of inducible type I and III IFN expression and sometimes even prior to IFN action (e.g. Iversen,...., Paludan. Nature Immunology, 2016; Paludan. Trends in Immunology, 2016). These discoveries challenge the current thinking in the field that IFNs constitute the first line of defense. Hence, there is an urgent need for more detailed understanding of the immediate antiviral defense mechanisms. Most importantly, we remain to identify key players in IFN-independent antiviral responses, we completely lack insight into the mechanisms that govern these responses, and we also lack information on the importance of this layer of defense in mice and humans. In accord with this, my proposal follows four aims: (i) Identification of mechanisms of virus detection at epithelial surfaces, (ii) elucidation of the role of tonic IFN signaling in antiviral defense, (iii) identification and characterization of novel restriction factors, and (iv) deciphering the mechanisms that govern induction of the first wave of IFNs at epithelial surfaces. In addition, I will also explore the interactions between the early antiviral actions. To achieve the goals, I will combine unbiased genome-wide screens with hypothesis-driven approaches, and will integrate molecular biology/genetics/biochemistry with advanced cell culture systems, animal science and analysis of patient material. Strong preliminary data have been generated for all four aims, and world-leading collaborations are in place, hence minimizing the risks, and allowing fast progress. Our findings will (i) change the thinking in innate immunology by uncovering a novel layer of antiviral defense and (ii) provide new avenues for therapeutic modulation of immune responses.
MPC is a cryptographic technique that allows a set of mutually distrusting parties to compute any joint function of their private inputs in a way that preserves the confidentiality of the inputs and the correctness of the result. Examples of MPC applications include secure auctions, benchmarking, privacy-preserving data mining, etc. In the last decade, the efficiency of MPC has improved significantly, especially with respect to evaluating functions expressed as Boolean and arithmetic circuits. These advances have allowed several companies worldwide to implement and include MPC solutions in their products. Unfortunately, it now appears (and it’s partially confirmed by theoretical lower bounds) that we have reached a wall with respect to possible optimizations of current building blocks of MPC, which prevents MPC to be used in critical large-scale applications. I therefore believe that a radical paradigm-shift in MPC research is needed in order to make MPC truly practical. With this project, I intend to take a step back, challenge current assumptions in MPC research and design novel MPC solutions. My hypothesis is that taking MPC to the next level requires more realistic modelling of the way that security, privacy and efficiency are defined and measured. By combining classic MPC techniques with research in neighbouring areas of computer science I will fulfill the aim of the project and in particular: 1) Understand the limitations of current abstract models for MPC and refine them to more precisely capture real world requirements in terms of security, privacy and efficiency. 2) Use the new models to guide the developments of the next generation of MPC protocols, going beyond current performances and therefore enabling large-scale applications. 3) Investigate the necessary privacy-utility trade-offs that parties undertake when participating in distributed computations and define MPC functionalities that encourage cooperation for rational parties.
Open Access mandate for Publications and Research data
Funder: EC Project Code: 101065303
Funder Contribution: 214,934 EUR
TypeSynth: Synthetic Methods in Program Verification Software systems mediate a growing proportion of human activity, e.g. communication, transport, medicine, industrial and agricultural production, etc. As a result, it is urgent to understand and better control both the correctness and security properties of these increasingly complex software systems. The diversity of verification requirements speaks to a need for models of program execution that smoothly interpolate between many different levels of abstraction. Models of program execution vary in expressiveness along the spectrum of possible programming languages and specification logics. At one extreme, dependent type theory is a language for mathematically-inspired functional programming that is sufficiently expressive to serve as its own specification logic. Dependent type theory has struggled, however, to incorporate several computational effects that are common in every-day programming languages, such as state and concurrency. Languages that support these features require very sophisticated specification logics due to the myriad details that must be surfaced in their semantic models. In the context of dependent type theory, I have recently developed a new technique called Synthetic Tait Computability or STC that smoothly combines multiple levels of abstraction into a single language. Inspired by sophisticated mathematical techniques invented in topos theory and category theory for entirely different purposes, STC enables low-level details (even down to execution steps) to be manipulated in a simpler and more abstract way than ever before, making them easier to control mathematically. Perhaps more importantly, the STC method makes it possible to import ideas and techniques from other fields that seemed more distant prior to my intervention. The goal of the TypeSynth project is to extend the successful STC approach to a wider class of programming models, in particular programming languages with effects.