Abstract
Secure deduplication allows removing duplicate content at third-party storage services while preserving the privacy of users' data. However, current solutions are built with strict designs that cannot be adapted to storage service and applications with different security and performance requirements. We present S2Dedup, a trusted hardware-based privacy-preserving deduplication system designed to support multiple security schemes that enable different levels of performance, security guarantees and space savings. An in-depth evaluation shows these trade-offs for the distinct Intel SGX-based secure schemes supported by our prototype. Moreover, we propose a novel Epoch and Exact Frequency scheme that prevents frequency analysis leakage attacks present in current deterministic approaches for secure deduplication while maintaining similar performance and space savings to state-of-the-art approaches.

Abstract
Secure databases have emerged to securely store and process sensitive data at untrusted infrastructures (e.g., Cloud Computing). To be secure and efficient, the encryption schemes used by these systems must be carefully chosen. Indeed, this task requires expertise both in databases and security, and is currently being done manually, which is time-consuming and error-prone and can lead to security violations, poor performance, or both. This paper presents ATOCS, a novel framework that analyses the applications' code and, from the inferred requirements, determines the best combination of encryption schemes and related configurations for the underlying secure NoSQL database. Its design is modular and extensible thus facilitating the support of different applications and database solutions. Our evaluation with real-world applications shows that ATOCS is fast (it takes 44 seconds to analyse more than 12K LoC), accurate, and simplifies the configuration of secure databases.

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Robotics is very appealing and is long recognized as a great way to teach programming, while drawing inspiring connections to other branches of engineering and science such as maths, physics or electronics. Although this symbiotic relationship between robotics and programming is perceived as largely beneficial, educational approaches often feel the need to hide the underlying complexity of the robotic system, but as a result fail to transmit the reactive essence of robot programming to the roboticists and programmers of the future. This paper presents Rosy, a novel language for teaching novice programmers through robotics. Its functional style is both familiar with a high-school algebra background and a materialization of the inherent reactive nature of robotic programming. Working at a higher-level of abstraction also teaches valuable design principles of decomposition of robotics software into collections of interacting controllers. Despite its simplicity, Rosy is completely valid Haskell code compatible with the ROS~ecosystem. We make a convincing case for our language by demonstrating how non-trivial applications can be expressed with ease and clarity, exposing its sound functional programming foundations, and developing a web-enabled robot programming environment.