When: January 27th, 14h00
Where: Zoom: https://videoconf-colibri.zoom.us/j/84425943613?pwd=Tk5VU3BXY25NVGNCN3ZDbE5jcEtqQT09
Talk 1: COBRA: Dynamic Proactive Secret Sharing for Confidential BFT Services
Abstract: Byzantine Fault-Tolerant (BFT) State Machine Replication (SMR) is a classical paradigm for implementing trustworthy services that has received renewed interest with the emergence of blockchains and decentralized infrastructures. A fundamental limitation of BFT SMR is that it provides integrity and availability despite a fraction of the replicas being controlled by an active adversary, but does not offer any confidentiality protection. Previous works addressed this issue by integrating secret sharing with the consensus-based framework of BFT SMR, but without providing all features required by practical systems, which include replica recovery, group reconfiguration, and acceptable performance when dealing with a large number of secrets. We present COBRA, a new protocol stack for Dynamic Proactive Secret Sharing that allows implementing confidentiality in practical BFT SMR systems. COBRA exhibits the best asymptotic communication complexity and optimal storage overhead, being able to renew 100k shares in a group of ten replicas 5 times faster than the current state of the art.
Talk 2: Deep learning for communication optimization on autonomous vehicles
Abstract: Connected and autonomous vehicles aim to improve passenger safety and driving quality of experience. However, current self-driving solutions still constitute an entry barrier to many potential users due to their cost and the offloading of the self-driving algorithms to reduce the onboard computing requirements. At the same time, a viable alternative requires a stable connection to the cloud. This work explores deep learning concepts to forecast mobile network KPIs. These models may ultimately be used to adjust the vehicle’s operational parameters to improve network signal quality and ensure a reliable connection to the cloud servers.