Titlebook: Distributed Applications and Interoperable Systems; 15th IFIP WG 6.1 Int Alysson Bessani,Sara Bouchenak Conference proceedings 2015 IFIP In

看法等

Fully Distributed Privacy Preserving Mini-batch Gradient Descent Learning,perimentally based on churn statistics from a real smartphone trace. We derive a sufficient condition for preventing the leakage of an individual value, and we demonstrate the feasibility of the overhead of the protocol.

Missile

發(fā)酵

Dynamic Message Processing and Transactional Memory in the Actor Model,ome this limitation. This allows for efficient resource utilization as these two mechanisms can be handled in parallel. We show that we can substantially reduce the execution time of high-contention workloads in a micro-benchmark as well as in a real-world application.

hermitage

cruise

Nebulous

Leader Election Using NewSQL Database Systems,ime. The leader election protocol uses the database as distributed shared memory. Our work enables distributed systems that already use NewSQL databases to save the operational overhead of managing an additional third-party service for leader election. Our main contribution is the design, implementa

改進(jìn)

LiveCloudInspector: Towards Integrated IaaS Forensics in the Cloud,offers live remote capture of network traffic. Third, and most importantly, it provides hybrid combinations of the first two techniques, which enables enhanced analysis capabilities such as support for monitoring encrypted communication.

毗鄰

MAUVE

flamboyant

Fully Distributed Privacy Preserving Mini-batch Gradient Descent Learning,n (MPC). However, in our application domain, known MPC algorithms are not scalable or not robust enough. We propose a light-weight protocol to quickly and securely compute the sum of the inputs of a subset of participants assuming a semi-honest adversary. During the computation the participants lear