Byzantine fault tolerance

It bridges the gap between sensor fusion and Byzantine fault tolerance.

Szabo argues that all three properties can be achieved up to the limits of Byzantine fault tolerance.

Examples of related problems include consensus problems, Byzantine fault tolerance, and self-stabilisation.

Byzantine fault tolerance can be achieved, if the loyal (non-faulty) generals have a unanimous agreement on their strategy.

When a Byzantine failure has occurred, the system may respond in any unpredictable way, unless it is designed to have Byzantine fault tolerance.

She leads the Programming Methodology Group at MIT, with a current research focus in Byzantine fault tolerance and distributed computing.

Byzantine fault tolerance is a sub-field of fault tolerance research inspired by the Byzantine Generals' Problem, which is a generalized version of the Two Generals' Problem.

Dolev has published many highly cited papers, including works on public-key cryptography, non-malleable cryptography, consensus in asynchronous distributed systems, atomic broadcasting, high availability and high-availability clusters, and Byzantine fault tolerance.

A second solution requires unforgeable signatures (in modern computer systems, this may be achieved in practice using public-key cryptography), but maintains Byzantine fault tolerance in the presence of an arbitrary number of traitorous generals.

The other aspect of overlay networks is to support uncontrolled environment, also known as Byzantine Fault Tolerance, through algorithms which assume a fraction of the nodes may be malicious in the way that they may not follow the protocol.

Then in 1999, Miguel Castro and Barbara Liskov introduced the "Practical Byzantine Fault Tolerance" (PBFT) algorithm, which provides high-performance Byzantine state machine replication, processing thousands of requests per second with sub-millisecond increases in latency.

Recent work by Miguel Castro and Barbara Liskov used the state machine approach in what they call a "Practical Byzantine fault tolerance" architecture that replicates especially sensitive services using a version of Lamport's original state machine approach, but with optimizations that substantially improve performance.

The objective of Byzantine fault tolerance is to be able to defend against Byzantine failures, in which components of a system fail in arbitrary ways (i.e., not just by stopping or crashing but by processing requests incorrectly, corrupting their local state, and/or producing incorrect or inconsistent outputs.)