Language Support for Secure Software Development with Enclaves

TL;DR: JE as discussed by the authors is a programming model that seamlessly integrates a TEE, abstracting away low-level programming details such as initialization and loading of data into the TEE and allowing developers to add annotations to their programs to enable the execution within TEE.

Abstract: Confidential computing is a promising technology for securing code and data-in-use on untrusted host machines, e.g., the cloud. Many hardware vendors offer different implementations of Trusted Execution Environments (TEEs). A TEE is a hardware protected execution environment that allows performing confidential computations over sensitive data on untrusted hosts. Despite the appeal of achieving strong security guarantees against low-level attackers, two challenges hinder the adoption of TEEs. First, developing software in high-level managed languages, e.g., Java or Scala, taking advantage of existing TEEs is complex and error-prone. Second, partitioning an application into components that run inside and outside a TEE may break application-level security policies, resulting in an insecure application when facing a realistic attacker. In this work, we study both these challenges. We present J E , a programming model that seamlessly integrates a TEE, abstracting away low-level programming details such as initialization and loading of data into the TEE. J E only requires developers to add annotations to their programs to enable the execution within the TEE. Drawing on information flow control, we develop a security type system that checks confidentiality and integrity policies against realistic attackers with full control over the code running outside the TEE. We formalize the security type system for the J E core and prove it sound for a semantic characterization of security. We implement J E and the security type system, enable Java programs to run on Intel SGX with strong security guarantees. We evaluate our approach on use cases from the literature, including a battleship game, a secure event processing system, and a popular processing framework for big data, showing that we correctly handle complex cases of partitioning, information flow, declassification, and trust.