TY - GEN
T1 - Confidential gossip
AU - Georgiou, Chryssis
AU - Gilbert, Seth
AU - Kowalski, Dariusz R.
PY - 2011
Y1 - 2011
N2 - Epidemic gossip has proven a reliable and efficient technique for sharing information in a distributed network. Much of the reliability and efficiency derives from processes collaborating, sharing the work of distributing information. As a result of this collaboration, processes may receive information that was not originally intended for them. For example, a process may act as an intermediary, aggregating and forwarding messages from some set of sources to some set of destinations. But what if rumors are confidential? In that case, only processes that were originally intended to receive a rumor should be allowed to learn the rumor. This blatantly contradicts the basic premise of epidemic gossip, which assumes that processes can collaborate. In fact, if only processes in a rumor's "destination set" participate in gossiping that rumor, we show that high message complexity is unavoidable. In this paper, we propose a scheme in which each rumor is broken into multiple fragments using a very simple coding scheme: any given fragment provides no information about the rumor, while together, the fragments can be reassembled into the original rumor. The processes collaborate in disseminating the rumor fragments in such a way that no process outside of a rumor's destination set ever receives all the fragments of a rumor, while every process in the destination set eventually learns all the fragments. Notably, our solution operates in an environment where rumors are dynamically and continuously injected into the system and processes are subject to crashes and restarts. In addition, the scheme presented can tolerate a moderate amount of collusion among curious processes without too large an increase in cost.
AB - Epidemic gossip has proven a reliable and efficient technique for sharing information in a distributed network. Much of the reliability and efficiency derives from processes collaborating, sharing the work of distributing information. As a result of this collaboration, processes may receive information that was not originally intended for them. For example, a process may act as an intermediary, aggregating and forwarding messages from some set of sources to some set of destinations. But what if rumors are confidential? In that case, only processes that were originally intended to receive a rumor should be allowed to learn the rumor. This blatantly contradicts the basic premise of epidemic gossip, which assumes that processes can collaborate. In fact, if only processes in a rumor's "destination set" participate in gossiping that rumor, we show that high message complexity is unavoidable. In this paper, we propose a scheme in which each rumor is broken into multiple fragments using a very simple coding scheme: any given fragment provides no information about the rumor, while together, the fragments can be reassembled into the original rumor. The processes collaborate in disseminating the rumor fragments in such a way that no process outside of a rumor's destination set ever receives all the fragments of a rumor, while every process in the destination set eventually learns all the fragments. Notably, our solution operates in an environment where rumors are dynamically and continuously injected into the system and processes are subject to crashes and restarts. In addition, the scheme presented can tolerate a moderate amount of collusion among curious processes without too large an increase in cost.
KW - Collusion
KW - Confidentiality
KW - Dynamic rumor injection
KW - Fault-tolerance
KW - Message complexity
KW - Randomized gossip
UR - http://www.scopus.com/inward/record.url?scp=80051909349&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80051909349&partnerID=8YFLogxK
U2 - 10.1109/ICDCS.2011.71
DO - 10.1109/ICDCS.2011.71
M3 - Conference contribution
AN - SCOPUS:80051909349
SN - 9780769543642
T3 - Proceedings - International Conference on Distributed Computing Systems
SP - 603
EP - 612
BT - Proceedings - 31st International Conference on Distributed Computing Systems, ICDCS 2011
T2 - 31st International Conference on Distributed Computing Systems, ICDCS 2011
Y2 - 20 June 2011 through 24 July 2011
ER -