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Heterogeneous CPU-FPGA systems have been shown to achieve significant performance gains in domain-specific computing. However, contrary to the huge efforts invested on the performance acceleration, the community has not yet investigated the security consequences due to incorporating FPGA into the traditional CPU-based architecture. In fact, the interplay between CPU and FPGA in such a heterogeneous system may introduce brand new attack surfaces if not well controlled. We propose a hardware isolation-based secure architecture, namely HISA, to mitigate the identified new threats. HISA extends the CPU-based hardware isolation primitive to the heterogeneous FPGA components and achieves security guarantees by enforcing two types of security policies in the isolated secure environment, namely the access control policy and the output verification policy. We evaluate HISA using four reference FPGA IP cores together with a variety of reference security policies targeting representative CPU-FPGA attacks. Our implementation and experiments on real hardware prove that HISA is an effective security complement to the existing CPU-only and FPGA-only secure architectures. 

To provide strong security support for today’s applications, microprocessor manufacturers have introduced hardware isolation, an on-chip mechanism that provides secure accesses to sensitive data. Currently, hardware isolation is still difficult to use by software developers because the process to identify access points to sensitive data is error-prone and can lead to under and over protection of sensitive data. Under protection can lead to security vulnerabilities. Over protection can lead to an increased attack surface and excessive communication overhead. In this paper we describe EvoIsolator, a search-based framework to (i) automatically generate executable minimal slices that include all access points to a set of specified sensitive data; and (ii) automatically optimize (for small code block size and low communication overhead) the code modules for hardware isolation. We demonstrate, through a small feasibility study, the potential impact of our proposed code optimizer.