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Hardware security creates a hardware-based security foundation for secure and reliable operation of systems and applications used in our modern life. The presence of design for security, security assurance, and general security design life cycle practices in product life cycle of many large semiconductor design and manufacturing companies these days indicates that the importance of hardware security has been very well observed in industry. However, the high cost, time, and effort for building security into designs and assuring their security - due to using many manual processes - is still an important obstacle for economy of secure product development. This paper presents several promising directions for automation of design for security and security assurance practices to reduce the overall time and cost of secure product development. First, we present security verification challenges of SoCs, possible vulnerabilities that could be introduced inadvertently by tools mapping a design model in one level of abstraction to its lower level, and our solution to the problem by automatically mapping security properties from one level to its lower level incorporating techniques for extension and expansion of the properties. Then, we discuss the foundation necessary for further automation of formal security analysis of a design by incorporating threat model and common security vulnerabilities into an intermediate representation of a hardware model to be used to automatically determine if there is a chance for direct or indirect flow of information to compromise confidentiality or integrity of security assets. Finally, we discuss a pre-silicon-based framework for practical and time-and-cost effective power-side channel leakage analysis, root-causing the side-channel leakage by using the automatically generated leakage profile of circuit nodes, providing insight to mitigate the side-channel leakage by addressing the high leakage nodes, and assuring the effectiveness of the mitigation by reprofiling the leakage to prove its acceptable level of elimination. We hope that sharing these efforts and ideas with the security research community can accelerate the evolution of security-aware CAD tools targeted to design for security and security assurance to enrich the ecosystem to have tools from multiple vendors with more capabilities and higher performance. 

Isadora is a methodology for creating information flow specifications of hardware designs. The methodology combines information flow tracking and specification mining to produce a set of information flow properties that are suitable for use during the security validation process, and which support a better understanding of the security posture of the design. Isadora is fully automated; the user provides only the design under consideration and a testbench and need not supply a threat model nor security specifications. We evaluate Isadora on a RISC-V processor plus two designs related to SoC access control. Isadora generates security properties that align with those suggested by the Common Weakness Enumerations (CWEs), and in the case of the SoC designs, align with the properties written manually by security experts. 

Security specification mining is a relatively new line of research that aims to develop a set of security properties for use during the design validation phase of the hardware life-cycle. Prior work in this field has targeted open-source RISC architectures and relies on access to the register transfer level design, developers’ repositories, bug tracker databases, and email archives. We develop Astarte, a tool for security specification mining of closed source, CISC architectures. As with prior work, we target properties written at the instruction set architecture (ISA) level. We use a full-system fast emulator with a lightweight extension to generate trace data, and we partition the space of security properties on security-critical signals in the architecture to manage complexity. We evaluate the approach for the x86-64 ISA. The Astarte framework produces roughly 1300 properties. Our automated approach produces a categorization that aligns with prior manual efforts. We study two known security flaws in shipped x86/x86-64 processor implementations and show that our set of properties could have revealed the flaws. Our analysis provides insight into those properties that are guaranteed by the ISA, those that are required of the operating system, and those that have become de facto properties by virtue of many operating systems assuming the behavior. 

This paper presents UNDINE, a tool to automatically generate security critical Linear Temporal Logic (LTL) properties of processor architectures. UNDINE handles complex templates, such as those involving four or more variables, register equality to a constant, and terms written over register slices. We introduce the notion of event types, which allows us to reduce the complexity of the search for a given template. We build a library of nine typed property templates that capture the patterns that are common to security critical properties for RISC processors. We evaluate the performance and efficacy of UNDINE and our library of typed templates on the OR1200, Mor1kx, and RISC-V processors. 

This paper presents Coppelia, an end-to-end tool that, given a processor design and a set of security-critical invariants, automatically generates complete, replayable exploit programs to help designers find, contextualize, and assess the security threat of hardware vulnerabilities. In Coppelia, we develop a hardware-oriented backward symbolic execution engine with a new cycle stitching method and fast validation technique, along with several optimizations for exploit generation. We then add program stubs to complete the exploit. We evaluate Coppelia on three CPUs of different architectures. Coppelia is able to find and generate exploits for 29 of 31 known vulnerabilities in these CPUs, including 11 vulnerabilities that commercial and academic model checking tools can not find. All of the generated exploits are successfully replayable on an FPGA board. Moreover, Coppelia finds 4 new vulnerabilities along with exploits in these CPUs. We also use Coppelia to verify whether a security patch indeed fixed a vulnerability, and to refine a set of assertions.