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Christopher Harth-Kitzerow

Publications and source records attributed to Christopher Harth-Kitzerow.

4 recordsLinked to original sources

High-Throughput Secure Multiparty Computation with an Honest Majority in Various Network Settings

In this work, we present novel protocols over rings for semi-honest secure three-party computation (3PC) and malicious four-party computation (4PC) with one corruption. While most existing works focus on improving total communication complexity, challenges such as network heterogeneity and computational complexity, which impact MPC performance in practice, remain underexplored. Our protocols address these issues by tolerating multiple arbitrarily weak network links between parties without any substantial decrease in performance. Additionally, they significantly reduce computational complexity by requiring up to half the number of basic instructions per gate compared to related work. These improvements lead to up to twice the throughput of state-of-the-art protocols in homogeneous network settings and up to eight times higher throughput in real-world heterogeneous settings. These advantages come at no additional cost: Our protocols maintain the best-known total communication complexity per multiplication, requiring 3 elements for 3PC and 5 elements for 4PC. We implemented our protocols alongside several state-of-the-art protocols (Replicated 3PC, ASTRA, Fantastic Four, Tetrad) in a novel open-source C++ framework optimized for high throughput. Five out of six implemented 3PC and 4PC protocols achieve more than one billion 32-bit multiplications or over 32 billion AND gates per second using our implementation in a 25 Gbit/s LAN environment. This represents the highest throughput achieved in 3PC and 4PC so far, outperforming existing frameworks like MP-SPDZ, ABY3, MPyC, and MOTION by two to three orders of magnitude.

cs.CR

Exploring privacy-enhancing technologies in the automotive value chain

Privacy-enhancing technologies (PETs) are becoming increasingly crucial for addressing customer needs, security, privacy (e.g., enhancing anonymity and confidentiality), and regulatory requirements. However, applying PETs in organizations requires a precise understanding of use cases, technologies, and limitations. This paper investigates several industrial use cases, their characteristics, and the potential applicability of PETs to these. We conduct expert interviews to identify and classify uses cases, a gray literature review of relevant open-source PET tools, and discuss how the use case characteristics can be addressed using PETs' capabilities. While we focus mainly on automotive use cases, the results also apply to other use case domains.

cs.CR

CRGC -- A Practical Framework for Constructing Reusable Garbled Circuits

In this work, we introduce two schemes to construct reusable garbled circuits (RGCs) in the semi-honest setting. Our completely reusable garbled circuit (CRGC) scheme allows the generator (party A) to construct and send an obfuscated boolean circuit along with an encoded input to the evaluator (party B). In contrast to Yao's Garbled Circuit protocol, B can securely evaluate the same CRGC with an arbitrary number of inputs. As a tradeoff, CRGCs predictably leak some input bits of A to B. We also propose a partially reusable garbled circuit (PRGC) scheme that divides a circuit into reusable and non-reusable sections. PRGCs do not leak input bits of A. We benchmark our CRGC implementation against the state-of-the-art garbled circuit libraries EMP SH2PC and TinyGarble2. Using our framework, evaluating a CRGC is up to twenty times faster, albeit with weaker privacy guarantees, than evaluating an equivalent garbled circuit constructed by the two existing libraries. Our open-source library can convert any C++ function to a CRGC at approx. 80 million gates per second and repeatedly evaluate a CRGC at approx. 350 million gates per second. Additionally, a compressed CRGC is approx. 75% smaller in file size than the unobfuscated boolean circuit.

cs.CR

Verifying Outsourced Computation in an Edge Computing Marketplace

An edge computing marketplace could enable IoT devices (Outsourcers) to outsource computation to any participating node (Contractors) in their proximity. In return, these nodes receive a reward for providing computation resources. In this work, we propose a scheme that verifies the integrity of arbitrary deterministic functions and is resistant to both dishonest Outsourcers and Contractors who try to maximize their expected payoff. We tested our verification scheme with state-of-the-art pre-trained Convolutional Neural Network models designed for object detection. On all devices, our verification scheme causes less than 1ms computational overhead and a negligible network bandwidth overhead of at most 84 bytes per frame. Our implementation can also perform our verification scheme's tasks parallel to the object detection to eliminate any latency overhead. Compared to other proposed verification schemes, our scheme resists a comprehensive set of protocol violations without sacrificing performance.

cs.CR