Recent works in social network stream analysis have shown that a user's online persona attributes (e.g., location, gender, ethnicity, political interest, etc.) can be accurately inferred from the topics the user writes about or engages with. Revealing a user's sensitive attributes could represent a privacy threat to some individuals. Microtargeting (e.g., the Cambridge Analytica scandal), surveillance, and discriminating ads are examples of threats to user privacy caused by sensitive attribute inference. In this paper, we propose Multifaceted privacy, a novel privacy model that aims to obfuscate a user's sensitive attributes while publicly preserving the user's public persona. To achieve multifaceted privacy, we build Aegis, a prototype client-centric social network stream processing system that helps preserve multifaceted privacy, and thus allowing social network users to freely express their online personas without revealing their sensitive attributes of choice. Aegis continuously suggests topics and hashtags to social network users to write about in order to obfuscate their sensitive attributes and hence confuse content-based sensitive attribute inferences. Our experiments show that adding as few as 0 to 4 obfuscation posts (depending on how revealing the original post is) successfully hides a user sensitive attributes without changing the user's public persona attributes.

The recent adoption of blockchain technologies and open permissionless networks suggest the importance of peer-to-peer atomic cross-chain transaction protocols. Users should be able to atomically exchange tokens and assets without depending on centralized intermediaries such as exchanges. Recent peer-to-peer atomic cross-chain swap protocols use hashlocks and timelocks to ensure that participants comply to the protocol. However, an expired timelock could lead to a violation of the all-or-nothing atomicity property. An honest participant who fails to execute a smart contract on time due to a crash failure, denial of service attacks or even network delays might end up losing assets. Although a crashed participant is the only participant who ends up worse off, current proposals are unsuitable for atomic cross-chain transactions in asynchronous environments where crash failures and network delays are the norm. In this paper, we present AC 3 WN, the first decentralized all-or-nothing atomic cross-chain commitment protocol. The redeem and refund events of the smart contracts that exchange assets are modeled as conflicting events. An open permissionless network of witnesses is used to guarantee that conflicting events could never simultaneously occur and either all smart contracts in an atomic cross-chain transaction are redeemed or all of them are refunded.

The uprise of Bitcoin and other peer-to-peer cryptocurrencies has opened many interesting and challenging problems in cryptography, distributed systems, and databases. The main underlying data structure is blockchain, a scalable fully replicated structure that is shared among all participants and guarantees a consistent view of all user transactions by all participants in the system. In this tutorial, we discuss the basic protocols used in blockchain, and elaborate on its main advantages and limitations. To overcome these limitations, we provide the necessary distributed systems background in managing large scale fully replicated ledgers, using Byzantine Agreement protocols to solve the consensus problem. Finally, we expound on some of the most recent proposals to design scalable and efficient blockchains in both permissionless and permissioned settings. The focus of the tutorial is on the distributed systems and database aspects of the recent innovations in blockchains.

Bitcoin is a successful and interesting example of a global scale peer-to-peer cryptocurrency that integrates many techniques and protocols from cryptography, distributed systems, and databases. The main underlying data structure is blockchain, a scalable fully replicated structure that is shared among all participants and guarantees a consistent view of all user transactions by all participants in the cryptocurrency system. In this tutorial, we discuss the basic protocols used in blockchain, and elaborate on its main advantages and limitations. To overcome these limitations, we provide the necessary distributed systems background in managing large scale fully replicated ledgers, using Byzantine Agreement protocols to solve the consensus problem. Finally, we expound on some of the most recent proposals to design scalable and efficient blockchains. The focus of the tutorial is on the distributed systems and database technical aspects of the recent innovations in blockchains.

Social media streams analysis can reveal the characteristics of people who engage with or write about different topics. Recent works show that it is possible to reveal sensitive attributes (e.g., location, gender, ethnicity, political views, etc.) of individuals by analyzing their social media streams. Although, the prediction of a user's sensitive attributes can be used to enhance the user experience in social media, revealing some attributes like the location could represent a threat on individuals. Users can obfuscate their location by posting about random topics linked to different locations. However, posting about random and sometimes contradictory topics that are not aligned with a user's online persona and posts could negatively affect the followers interested in her profile. This paper represents our vision about the future of user privacy on social media. Users can locally deploy a cyborg, an artificial intelligent system that helps people to defend their privacy on social media. We propose LocBorg, a location privacy preserving cyborg that protects users by obfuscating their location while maintaining their online persona. LocBorg analyzes the social media streams and recommends topics to write about that are similar to a user's topics of interest and aligned with the user's online persona but linked to other locations.

This demonstration introduces the database community to state-of-the-art cryptographic methods that ensure efficient oblivious access to cloud data. In particular, we explore oblivious storage systems which hide both the content of data and data access patterns from an untrusted cloud provider. The demo considers the popular and realistic setting where multiple users from a trusted group asynchronously access and edit potentially overlapping data sets through a trusted proxy. We present a detailed implementation of TaoStore (Sahin et al., S&P 2016), a new tree-based ORAM scheme that processes client requests concurrently and asynchronously in a non-blocking fashion, resulting in substantial gains in throughput, simplicity, and flexibility over previous systems. The demo is presented in the context of a pedagogical game, Guess the Access, which allows participants to play as an adversary trying to guess queries against TaoStore or ObliviStore (Stefanov and Shi, S&P 2013), a recent oblivious storage system which has been shown to leak access patterns. The proposed game will highlight the subtleties and intricacies that underlie the cryptographic methods used to design oblivious storage systems.

Today's web applications and social networks are serving billions of users around the globe. These users generate billions of key lookups and millions of data object updates per second. A single user's social network page load requires hundreds of key lookups. This scale creates many design challenges for the underlying storage systems. First, these systems have to serve user requests with low latency. Any increase in the request latency leads to a decrease in user interest. Second, storage systems have to be highly available. Failures should be handled seamlessly without affecting user requests. Third, users consume an order of magnitude more data than they produce. Therefore, storage systems have to be optimized for read-intensive workloads. To address these challenges, distributed in-memory caching services have been widely deployed on top of persistent storage. In this tutorial, we survey the recent developments in distributed caching services. We present the algorithmic and architectural efforts behind these systems focusing on the challenges in addition to open research questions.

Geo-replication is the process of maintaining copies of data at geographically dispersed datacenters for better availability and fault-tolerance. The distinguishing characteristic of geo-replication is the large wide-area latency between datacenters that varies widely depending on the location of the datacenters. Thus, choosing which datacenters to deploy a cloud application has a direct impact on the observable response time. We propose an optimization framework that automatically derives a geo-replication placement plan with the objective of minimizing latency. By running the optimization framework on real placement scenarios, we learn a set of placement optimizations for geo-replication. Some of these optimizations are surprising while others are in retrospect straight-forward. In this demonstration, we highlight the geo-replication placement optimizations through the DB-Risk game. DB-Risk invites players to create different placement scenarios while experimenting with the proposed optimizations. The placements created by the players are tested on real cloud deployments.

We consider oblivious storage systems hiding both the contents of the data as well as access patterns from an untrusted cloud provider. We target a scenario where multiple users from a trusted group (e.g., corporate employees) asynchronously access and edit potentially overlapping data sets through a trusted proxy mediating client-cloud communication. The main contribution of our paper is twofold. Foremost, we initiate the first formal study of asynchronicity in oblivious storage systems. We provide security definitions for scenarios where both client requests and network communication are asynchronous (and in fact, even adversarially scheduled). While security issues in ObliviStore (Stefanov and Shi, S&P 2013) have recently been surfaced, our treatment shows that also CURIOUS (Bindschaedler at al., CCS 2015), proposed with the exact goal of preventing these attacks, is insecure under asynchronous scheduling of network communication. Second, we develop and evaluate a new oblivious storage system, called Tree-based Asynchronous Oblivious Store, or TaoStore for short, which we prove secure in asynchronous environments. TaoStore is built on top of a new tree-based ORAM scheme that processes client requests concurrently and asynchronously in a non-blocking fashion. This results in a substantial gain in throughput, simplicity, and flexibility over previous systems.