TY - GEN
T1 - Self-stabilizing Byzantine Tolerant Replicated State Machine Based on Failure Detectors
AU - Dolev, Shlomi
AU - Georgiou, Chryssis
AU - Marcoullis, Ioannis
AU - Schiller, Elad M.
N1 - Publisher Copyright:
© 2018, Springer International Publishing AG, part of Springer Nature.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Byzantine Fault Tolerant (BFT) replication leverages highly available cloud services and can facilitate the implementation of distributed ledgers, e.g., the blockchain. Systems providing BFT State Machine Replication (SMR) work under severe system assumptions, for example, that less than a third of replicas may suffer a Byzantine failure. Infrequent arbitrary violations of such design assumptions, may lead the system to an unintended state, and render it unavailable thereafter, requiring human intervention. Self-stabilization is a highly desirable system property that can complement Byzantine fault tolerant systems, and allow them to both tolerate Byzantine-failures and automatically recovery from any unintended state that assumption violations may lead to. This paper contributes the first self-stabilizing State Machine Replication service that is based on failure detectors. We suggest an implementable self-stabilizing failure detector to monitor both responsiveness and the replication progress. We thus encapsulate weaker synchronization guarantees than the previous self-stabilizing BFT SMR solution. We follow the seminal paper by Castro and Liskov of Practical Byzantine Fault Tolerance and focus on the self-stabilizing perspective. This work can aid towards building distributed blockchain system infrastructure enhanced with the self-stabilization design criteria.
AB - Byzantine Fault Tolerant (BFT) replication leverages highly available cloud services and can facilitate the implementation of distributed ledgers, e.g., the blockchain. Systems providing BFT State Machine Replication (SMR) work under severe system assumptions, for example, that less than a third of replicas may suffer a Byzantine failure. Infrequent arbitrary violations of such design assumptions, may lead the system to an unintended state, and render it unavailable thereafter, requiring human intervention. Self-stabilization is a highly desirable system property that can complement Byzantine fault tolerant systems, and allow them to both tolerate Byzantine-failures and automatically recovery from any unintended state that assumption violations may lead to. This paper contributes the first self-stabilizing State Machine Replication service that is based on failure detectors. We suggest an implementable self-stabilizing failure detector to monitor both responsiveness and the replication progress. We thus encapsulate weaker synchronization guarantees than the previous self-stabilizing BFT SMR solution. We follow the seminal paper by Castro and Liskov of Practical Byzantine Fault Tolerance and focus on the self-stabilizing perspective. This work can aid towards building distributed blockchain system infrastructure enhanced with the self-stabilization design criteria.
KW - Byzantine Fault-Tolerance
KW - Fault detection
KW - Self-stabilization
KW - State Machine Replication
UR - http://www.scopus.com/inward/record.url?scp=85049014276&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-94147-9_7
DO - 10.1007/978-3-319-94147-9_7
M3 - Conference contribution
AN - SCOPUS:85049014276
SN - 9783319941462
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 84
EP - 100
BT - Cyber Security Cryptography and Machine Learning - Second International Symposium, CSCML 2018, Proceedings
A2 - Dinur, Itai
A2 - Dolev, Shlomi
A2 - Lodha, Sachin
PB - Springer Verlag
T2 - 2nd International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2018
Y2 - 21 June 2018 through 22 June 2018
ER -