2,734 research outputs found
High-level Cryptographic Abstractions
The interfaces exposed by commonly used cryptographic libraries are clumsy,
complicated, and assume an understanding of cryptographic algorithms. The
challenge is to design high-level abstractions that require minimum knowledge
and effort to use while also allowing maximum control when needed.
This paper proposes such high-level abstractions consisting of simple
cryptographic primitives and full declarative configuration. These abstractions
can be implemented on top of any cryptographic library in any language. We have
implemented these abstractions in Python, and used them to write a wide variety
of well-known security protocols, including Signal, Kerberos, and TLS.
We show that programs using our abstractions are much smaller and easier to
write than using low-level libraries, where size of security protocols
implemented is reduced by about a third on average. We show our implementation
incurs a small overhead, less than 5 microseconds for shared key operations and
less than 341 microseconds (< 1%) for public key operations. We also show our
abstractions are safe against main types of cryptographic misuse reported in
the literature
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The future of clinical leadership: evidence for physician leadership and the educational pathway for new leaders
Until recently, the title ‘physician leader’ was rarely heard particularly in the UK. But that is changing. Doctors are being drawn into leadership and management more systematically. New educational opportunities are being tailored to the specific needs of doctors. The change towards physician leadership is being driven by research showing that leaders who are experts in the core business, such as doctors, are associated with improved organisational performance. This article summarises that evidence and then reviews what we have learnt about how best to train future physician leaders
Recursive Rules with Aggregation: A Simple Unified Semantics
Complex reasoning problems are most clearly and easily specified using
logical rules, especially recursive rules with aggregation such as counts and
sums for practical applications. Unfortunately, the meaning of such rules has
been a significant challenge, leading to many different conflicting semantics.
This paper describes a unified semantics for recursive rules with
aggregation, extending the unified founded semantics and constraint semantics
for recursive rules with negation. The key idea is to support simple expression
of the different assumptions underlying different semantics, and orthogonally
interpret aggregation operations straightforwardly using their simple usual
meaning
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