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PublicationUniform instruction set extensions for multiplications in contemporary and post-quantum cryptography( 2024)Hybrid key encapsulation is in the process of becoming the de-facto standard for integration of post-quantum cryptography (PQC). Supporting two cryptographic primitives is a challenging task for constrained embedded systems. Both contemporary cryptography based on elliptic curves or RSA and PQC based on lattices require costly multiplications. Recent works have shown how to implement lattice-based cryptography on big-integer coprocessors. We propose a novel hardware design that natively supports the multiplication of polynomials and big integers, integrate it into a RISC-V core, and extend the RISC-V ISA accordingly. We provide an implementation of Saber and X25519 to demonstrate that both lattice- and elliptic-curve-based cryptography benefits from our extension. Our implementation requires only intermediate logic overhead, while significantly outperforming optimized ARM Cortex M4 implementations, other hardware/software codesigns, and designs that rely on contemporary accelerators.
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PublicationCybersecurity risk analysis of an automated driving system( 2023-10-25)
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PublicationCompaSeC: A Compiler-Assisted Security Countermeasure to Address Instruction Skip Fault Attacks on RISC-V( 2023-01-31)
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PublicationSecurity Risk Assessments: Modeling and Risk Level Propagation( 2023)Security risk assessment is an important task in systems engineering. It is used to derive security requirements for a secure system design and to evaluate design alternatives as well as vulnerabilities. Security risk assessment is also a complex and interdisciplinary task, where experts from the application domain and the security domain have to collaborate and understand each other. Automated and tool-supported approaches are desired to help manage the complexity. However, the models used for system engineering usually focus on functional behavior and lack security-related aspects. Therefore, we present our modeling approach that alleviates communication between the involved experts and features steps of computer-aided modeling to achieve consistency and avoid omission errors. We demonstrate our approach with an example. We also describe how to model impact rating and attack feasibility estimation in a modular fashion, along with the propagation and aggregation of these estimations through the model. As a result, experts can make local decisions or changes in the model, which in turn provides the impact of these decisions or changes on the overall risk profile. Finally, we discuss the advantages of our model-based method.
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PublicationUniversal Remote Attestation for Cloud and Edge Platforms( 2023)With more computing workloads being shifted to the cloud, verifying the integrity of remote software stacks through remote attestation becomes an increasingly important topic. During remote attestation, a prover provides attestation evidence to a verifier, backed by a hardware trust anchor. While generating this information, which is essentially a list of hashes, is easy, examining the trustworthiness of the overall platform based on the provided list of hashes without context is difficult. Furthermore, as different trust anchors use different formats, interaction between devices using different attestation technologies is a complex problem. To address this problem, we propose a universal, hardware-agnostic device-identity and attestation framework. Our framework focuses on easing attestation by having provers present meaningful metadata to verify the integrity of the attestation evidence. We implemented and evaluated the framework for Trusted Platform Modules (TPM), AMD SEV-SNP attestation, and ARM PSA Entity Attestation Tokens (EATs).
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PublicationPost-quantum Security for the Extended Access Control Protocol( 2023)The Extended Access Control (EAC) protocol for authenticated key agreement is mainly used to secure connections between machine-readable travel documents (MRTDs) and inspection terminals, but it can also be adopted as a universal solution for attribute-based access control with smart cards. The security of EAC is currently based on the Diffie-Hellman problem, which may not be hard when considering quantum computers. In this work we present PQ-EAC, a quantum-resistant version of the EAC protocol. We show how to achieve post-quantum confidentiality and authentication without sacrificing real-world usability on smart cards. To ease adoption, we present two main versions of PQ-EAC: One that uses signatures for authentication and one where authentication is facilitated using long-term KEM keys. Both versions can be adapted to achieve forward secrecy and to reduce round complexity. To ensure backwards-compatibility, PQ-EAC can be implemented using only Application Protocol Data Units (APDUs) specified for EAC in standard BSI TR-03110. Merely the protocol messages needed to achieve forward secrecy require an additional APDU not specified in TR-03110. We prove security of all versions in the real-or-random model of Bellare and Rogaway. To show real-world practicality of PQ-EAC we have implemented a version using signatures on an ARM SC300 security controller, which is typically deployed in MRTDs. We also implemented PQ-EAC on a VISOCORE® terminal for border control. We then conducted several experiments to evaluate the performance of PQ-EAC executed between chip and terminal under various real-world conditions. Our results strongly suggest that PQ-EAC is efficient enough for use in border control.
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PublicationR2-AD2: Detecting Anomalies by Analysing the Raw Gradient( 2023)Neural networks follow a gradient-based learning scheme, adapting their mapping parameters by back-propagating the output loss. Samples unlike the ones seen during training cause a different gradient distribution. Based on this intuition, we design a novel semi-supervised anomaly detection method called R2-AD2. By analysing the temporal distribution of the gradient over multiple training steps, we reliably detect point anomalies in strict semi-supervised settings. Instead of domain dependent features, we input the raw gradient caused by the sample under test to an end-to-end recurrent neural network architecture. R2-AD2 works in a purely data-driven way, thus is readily applicable in a variety of important use cases of anomaly detection.
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PublicationHWASanIO: Detecting C/C++ Intra-object Overflows with Memory Shading( 2023)
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PublicationCryptSan: Leveraging ARM Pointer Authentication for Memory Safety in C/C++( 2023)Memory safety bugs remain in the top ranks of security vulnerabilities, even after decades of research on their detection and prevention. Various mitigations have been proposed for C/C++, ranging from language dialects to instrumentation. Among these, compiler-based instrumentation is particularly promising, not requiring manual code modifications and being able to achieve precise memory safety. Unfortunately, existing compiler-based solutions compromise in many areas, including performance but also usability and memory safety guarantees. New developments in hardware can help improve performance and security of compiler-based memory safety. ARM Pointer Authentication, added in the ARMv8.3 architecture, is intended to enable hardware-assisted Control Flow Integrity (CFI). But since its operations are generic, it also enables other, more comprehensive hardware-supported runtime integrity approaches. As such, we propose CryptSan, a memory safety approach based on ARM Pointer Authentication. CryptSan uses pointer signatures to retrofit memory safety to C/C++ programs, protecting heap, stack, and globals against temporal and spatial vulnerabilities. We present a full LLVM-based prototype implementation, running on an M1 MacBook Pro, i.e., on actual ARMv8.3 hardware. Our prototype evaluation shows that the system outperforms similar approaches under real-world conditions. This, together with its interoperability with uninstrumented libraries and cryptographic protection against attacks on metadata, makes CryptSan a viable solution for retrofitting memory safety to C/C++ programs.
