Cloud service providers started with Infrastructure as a Service (IaaS) offerings and over time expanded into Platform as a Service (PaaS) and Software as a Service (SaaS). Even though each provider has a rich product offering, there are many scenarios where a multi-cloud strategy is desirable: utilizing economic dynamics, preventing data lock-in with one vendor, circumventing geographic restrictions, complying with local regulations, or combining on-premise and public-cloud resources. The challenge from a consumer perspective with multi-cloud deployments is the lack of a common abstraction for the offered products and a standardized way to express all of the application requirements for the resulting deployments. In this paper, we contribute by making yet another case for multi-cloud deployments and by predicting the emergence of a new generation of application-level resource managers which will natively support multi-cloud for enterprise applications. We identify three main components of the feedback loop controlled application-level resource managers: the software life-cycle manager, the data storage and access manager, and the service execution manager.

Companies are often motivated to evaluate their environmental sustainability, and to make public pronouncements about their performance with respect to quantitative sustainability metrics. Public trust in these declarations is enhanced if the claims are certified by a recognized authority. Because accurate evaluations of environmental impacts require detailed information about industrial processes throughout a supply chain, protecting the privacy of input data in sustainability assessment is of paramount importance. We introduce a new paradigm, called privacy-preserving certification, that enables the computation of sustainability indicators in a privacy-preserving manner, allowing firms to be classified based on their individual performance without revealing sensitive information to the certifier, other parties, or the public. In this work, we describe different variants of the certification problem, highlight the necessary security requirements, and propose a provably-secure novel framework that performs the certification operations under the management of an authorized, yet untrusted, party without compromising confidential information.

Although outsourcing data to cloud storage has become popular, the increasing concerns about data security and privacy in the cloud limits broader cloud adoption. Ensuring data security and privacy, therefore, is crucial for better and broader adoption of the cloud. This tutorial provides a comprehensive analysis of the state-of-the-art in the context of data security and privacy for outsourced data. We aim to cover common security and privacy threats for outsourced data, and relevant novel schemes and techniques with their design choices regarding security, privacy, functionality, and performance. Our explicit focus is on recent schemes from both the database and the cryptography and security communities that enable query processing over encrypted data and access oblivious cloud storage systems.

Performing non-aggregate range queries on cloud stored data, while achieving both privacy and efficiency is a challenging problem. This paper proposes constructing a differentially private index to an outsourced encrypted dataset. Efficiency is enabled by using a cleartext index structure to perform range queries. Security relies on both differential privacy (of the index) and semantic security (of the encrypted dataset). Our solution, PINED-RQ develops algorithms for building and updating the differentially private index. Compared to state-of-the-art secure index based range query processing approaches, PINED-RQ executes queries in the order of at least one magnitude faster. The security of PINED-RQ is proved and its efficiency is assessed by an extensive experimental validation.

Life Cycle Assessment(LCA) is crucial for evaluating the ecological sustainability of a product or service, and the accurate evaluation of sustainability requires detailed and transparent information about industrial activities. However, such information is usually considered confidential and withheld from the public. In this paper, we present a rigorous study of privacy in the context of LCA. The main goal is to explore the privacy challenges in sustainability assessment considering the protection of trade secrets while increasing transparency of industrial activities. To overcome privacy concerns, we apply differential privacy to LCA computations considering the idiosyncratic features of LCA data. Our assessments on a specific real-life example show that it is possible to achieve privacy-preserving LCA computations without losing the utility of data completely.

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.

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.

Technology trends are not only transforming the hardware landscape of end-user devices but are also dramatically changing the types of software applications that are deployed on these devices. With the maturity of cloud computing during the past few years, users increasingly rely on networked applications that are deployed in the cloud. In particular, new applications will emerge where user interactions will be based on real-time continuous media streams instead of the traditional request-response types of interfaces. Furthermore, many of these applications will be multi-user streaming media based interactions instead of a single user interaction with an application. In this paper, we propose a geographic location-aware, hybrid, scalable cloud assisted peer-to-peer (P2P) architecture to support such applications that targets low administration cost, reduced bandwidth consumption, low latency, low initial investment cost and optimized resource usage. The main objective is to develop an efficient media delivery system that leverages locality. We propose a 3-layer novel architecture that uses at the core the cloud for application management, 2-tier edge cloud for supporting geo-dispersed user groups, and at the lowest level peer-to-peer dynamic overlays for locally clustered user groups. The proposed architecture manages multiple streaming sessions simultaneously and each streaming session is an independent entity. Our experiments on PlanetLab show that the dynamic construction and maintenance of delivering streams at both the user-level P2P overlay and edge cloud are indeed feasible and effective.