A logic of negative trust

We present a logic to model the behaviour of an agent trusting or not trusting messages sent by another agent. The logic formalises trust as a consistency checking function with respect to currently available information. Negative trust is modelled in two forms: distrust, as the rejection of incoming inconsistent information; mistrust, as revision of previously held information becoming undesirable in view of new incoming inconsistent information, which the agent wishes to accept. We provide a natural deduction calculus, a relational semantics and prove soundness and completeness results. We overview a number of applications which have been investigated for the proof-theoretical formulation of the logic

Checking Trustworthiness of Probabilistic Computations in a Typed Natural Deduction System

In this paper we present the probabilistic typed natural deduction calculus TPTND, designed to reason about and derive trustworthiness properties of probabilistic computational processes, like those underlying current AI applications. Derivability in TPTND is interpreted as the process of extracting $n$ samples of possibly complex outputs with a certain frequency from a given categorical distribution. We formalize trust for such outputs as a form of hypothesis testing on the distance between such frequency and the intended probability. The main advantage of the calculus is to render such notion of trustworthiness checkable. We present a computational semantics for the terms over which we reason and then the semantics of TPTND, where logical operators as well as a Trust operator are defined through introduction and elimination rules. We illustrate structural and metatheoretical properties, with particular focus on the ability to establish under which term evolutions and logical rules applications the notion of trustworhtiness can be preserved

Cryptimeleon: A Library for Fast Prototyping of Privacy-Preserving Cryptographic Schemes

We present a cryptographic Java library called Cryptimeleon designed for prototyping and benchmarking privacy-preserving cryptographic schemes. The library is geared towards researchers wanting to implement their schemes (1) as a sanity check for their constructions, and (2) for benchmark numbers in their papers. To ease the implementation process, Cryptimeleon speaks the language of paper writers. It offers a similar degree of abstraction as is commonly used in research papers. For example, bilinear groups can be used as the familiar black-box and Schnorr-style proofs can be described on the level of Camenisch-Stadler notation. It employs several optimizations (such as multi-exponentation) transparently, allowing the developer to phrase computations as written in the paper instead of having to conform to an artificial API for better performance. Cryptimeleon implements (among others) finite fields, elliptic curve groups and pairings, hashing, Schnorr-style zero-knowledge proofs, accumulators, digital signatures, secret sharing, group signatures, attribute-based encryption, and other modern cryptographic constructions. In this paper, we present the library, its capabilities, and explain important design decisions