• Publications
  • Influence
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
TensorFlow is an interface for expressing machine learning algorithms, and an implementation for executing such algorithms. A computation expressed using TensorFlow can be executed with little or noExpand
  • 7,467
  • 871
  • Open Access
A logic of authentication
Authentication protocols are the basis of security in many distributed systems, and it is therefore essential to ensure that these protocols function correctly. Unfortunately, their design has beenExpand
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  • 188
  • Open Access
Control-flow integrity
Current software attacks often build on exploits that subvert machine-code execution. The enforcement of a basic safety property, Control-Flow Integrity (CFI), can prevent such attacks fromExpand
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  • Open Access
A Theory of Objects
From the Publisher: Procedural languages are generally well understood. Their foundations have been cast in calculi that prove useful in matters of implementation and semantics. So far, an analogousExpand
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A calculus for cryptographic protocols: the spi calculus
We introduce the spi calculus, an extension of the pi calculus designed for describing and analyzing cryptographic protocols. We show how to use the spi calculus, particularly for studyingExpand
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  • Open Access
Mobile values, new names, and secure communication
We study the interaction of the "new" construct with a rich but common form of (first-order) communication. This interaction is crucial in security protocols, which are the main motivating examplesExpand
  • 942
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  • Open Access
A logic of authentication
Authentication protocols are the basis of security in many distributed systems, and it is therefore essential to ensure that these protocols function correctly. Unfortunately, their design has beenExpand
  • 1,300
  • 76
  • Open Access
Naiad: a timely dataflow system
Naiad is a distributed system for executing data parallel, cyclic dataflow programs. It offers the high throughput of batch processors, the low latency of stream processors, and the ability toExpand
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  • Open Access
The Existence of Refinement Mappings
Refinement mappings are used to prove that a lower-level specification correctly implements a higher-level one. The authors consider specifications consisting of a state machine (which may beExpand
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Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
Some machine learning applications involve training data that is sensitive, such as the medical histories of patients in a clinical trial. A model may inadvertently and implicitly store some of itsExpand
  • 348
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  • Open Access