Remote computation has numerous use cases such as cloud computing, client-side web applications or volunteer computing. Typically, these computations are executed inside a sandboxed environment for two reasons: first, to isolate the execution in order to protect the host environment from unauthorised access, and second to control and restrict resource usage. Often, there is mutual distrust between entities providing the code and the ones executing it, owing to concerns over three potential problems: (i) loss of control over code and data by the providing entity, (ii) uncertainty of the integrity of the execution environment for customers, and (iii) a missing mutually trusted accounting of resource usage.

Many organisations enhance the performance, security, and functionality of their managed networks by deploying middleboxes centrally as part of their core network. While this simplifies maintenance, it also increases cost because middlebox hardware must scale with the number of clients. A promising alternative is to outsource middlebox functions to the clients themselves, thus leveraging their CPU resources. Such an approach, however, raises security challenges for critical middlebox functions such as firewalls and intrusion detection systems. We describe EndBox, a system that securely executes middlebox functions on client machines at the network edge. Its design combines a virtual private network (VPN) with middlebox functions that are hardware-protected by a trusted execution environment (TEE), as offered by Intel's Software Guard Extensions (SGX). By maintaining VPN connection endpoints inside SGX enclaves, EndBox ensures that all client traffic, including encrypted communication, is processed by the middlebox. Despite its decentralised model, EndBox's middlebox functions remain maintainable: they are centrally controlled and can be updated efficiently. We demonstrate EndBox with two scenarios involving (i) a large company; and (ii) an Internet service provider that both need to protect their network and connected clients. We evaluate EndBox by comparing it to centralised deployments of common middlebox functions, such as load balancing, intrusion detection, firewalling, and DDoS prevention. We show that EndBox achieves up to 3.8x higher throughput and scales linearly with the number of clients.

By regularly querying Web search engines, users (unconsciously) disclose large amounts of their personal data as part of their search queries, among which some might reveal sensitive information (e.g. health issues, sexual, political or religious preferences). Several solutions exist to allow users querying search engines while improving privacy protection. However, these solutions suffer from a number of limitations: some are subject to user re-identification attacks, while others lack scalability or are unable to provide accurate results. This paper presents CYCLOSA, a secure, scalable and accurate private Web search solution. CYCLOSA improves security by relying on trusted execution environments (TEEs) as provided by Intel SGX. Further, CYCLOSA proposes a novel adaptive privacy protection solution that reduces the risk of user re-identification. CYCLOSA sends fake queries to the search engine and dynamically adapts their count according to the sensitivity of the user query. In addition, CYCLOSA meets scalability as it is fully decentralized, spreading the load for distributing fake queries among other nodes. Finally, CYCLOSA achieves accuracy of Web search as it handles the real query and the fake queries separately, in contrast to other existing solutions that mix fake and real query results.